diff --git a/testdata/dnn/ResNet-50-deploy.prototxt b/testdata/dnn/ResNet-50-deploy.prototxt deleted file mode 100644 index cc50de4cc..000000000 --- a/testdata/dnn/ResNet-50-deploy.prototxt +++ /dev/null @@ -1,2320 +0,0 @@ -name: "ResNet-50" -input: "data" -input_dim: 1 -input_dim: 3 -input_dim: 224 -input_dim: 224 - -layer { - bottom: "data" - top: "conv1" - name: "conv1" - type: "Convolution" - convolution_param { - num_output: 64 - kernel_size: 7 - pad: 3 - stride: 2 - } -} - -layer { - bottom: "conv1" - top: "conv1" - name: "bn_conv1" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "conv1" - top: "conv1" - name: "scale_conv1" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "conv1" - top: "conv1" - name: "conv1_relu" - type: "ReLU" -} - -layer { - bottom: "conv1" - top: "pool1" - name: "pool1" - type: "Pooling" - pooling_param { - kernel_size: 3 - stride: 2 - pool: MAX - } -} - -layer { - bottom: "pool1" - top: "res2a_branch1" - name: "res2a_branch1" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res2a_branch1" - top: "res2a_branch1" - name: "bn2a_branch1" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res2a_branch1" - top: "res2a_branch1" - name: "scale2a_branch1" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "pool1" - top: "res2a_branch2a" - name: "res2a_branch2a" - type: "Convolution" - convolution_param { - num_output: 64 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res2a_branch2a" - top: "res2a_branch2a" - name: "bn2a_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res2a_branch2a" - top: "res2a_branch2a" - name: "scale2a_branch2a" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res2a_branch2a" - top: "res2a_branch2a" - name: "res2a_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res2a_branch2a" - top: "res2a_branch2b" - name: "res2a_branch2b" - type: "Convolution" - convolution_param { - num_output: 64 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res2a_branch2b" - top: "res2a_branch2b" - name: "bn2a_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res2a_branch2b" - top: "res2a_branch2b" - name: "scale2a_branch2b" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res2a_branch2b" - top: "res2a_branch2b" - name: "res2a_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res2a_branch2b" - top: "res2a_branch2c" - name: "res2a_branch2c" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res2a_branch2c" - top: "res2a_branch2c" - name: "bn2a_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res2a_branch2c" - top: "res2a_branch2c" - name: "scale2a_branch2c" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res2a_branch1" - bottom: "res2a_branch2c" - top: "res2a" - name: "res2a" - type: "Eltwise" -} - -layer { - bottom: "res2a" - top: "res2a" - name: "res2a_relu" - type: "ReLU" -} - -layer { - bottom: "res2a" - top: "res2b_branch2a" - name: "res2b_branch2a" - type: "Convolution" - convolution_param { - num_output: 64 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res2b_branch2a" - top: "res2b_branch2a" - name: "bn2b_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res2b_branch2a" - top: "res2b_branch2a" - name: "scale2b_branch2a" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res2b_branch2a" - top: "res2b_branch2a" - name: "res2b_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res2b_branch2a" - top: "res2b_branch2b" - name: "res2b_branch2b" - type: "Convolution" - convolution_param { - num_output: 64 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res2b_branch2b" - top: "res2b_branch2b" - name: "bn2b_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res2b_branch2b" - top: "res2b_branch2b" - name: "scale2b_branch2b" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res2b_branch2b" - top: "res2b_branch2b" - name: "res2b_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res2b_branch2b" - top: "res2b_branch2c" - name: "res2b_branch2c" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res2b_branch2c" - top: "res2b_branch2c" - name: "bn2b_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res2b_branch2c" - top: "res2b_branch2c" - name: "scale2b_branch2c" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res2a" - bottom: "res2b_branch2c" - top: "res2b" - name: "res2b" - type: "Eltwise" -} - -layer { - bottom: "res2b" - top: "res2b" - name: "res2b_relu" - type: "ReLU" -} - -layer { - bottom: "res2b" - top: "res2c_branch2a" - name: "res2c_branch2a" - type: "Convolution" - convolution_param { - num_output: 64 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res2c_branch2a" - top: "res2c_branch2a" - name: "bn2c_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res2c_branch2a" - top: "res2c_branch2a" - name: "scale2c_branch2a" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res2c_branch2a" - top: "res2c_branch2a" - name: "res2c_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res2c_branch2a" - top: "res2c_branch2b" - name: "res2c_branch2b" - type: "Convolution" - convolution_param { - num_output: 64 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res2c_branch2b" - top: "res2c_branch2b" - name: "bn2c_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res2c_branch2b" - top: "res2c_branch2b" - name: "scale2c_branch2b" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res2c_branch2b" - top: "res2c_branch2b" - name: "res2c_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res2c_branch2b" - top: "res2c_branch2c" - name: "res2c_branch2c" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res2c_branch2c" - top: "res2c_branch2c" - name: "bn2c_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res2c_branch2c" - top: "res2c_branch2c" - name: "scale2c_branch2c" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res2b" - bottom: "res2c_branch2c" - top: "res2c" - name: "res2c" - type: "Eltwise" -} - -layer { - bottom: "res2c" - top: "res2c" - name: "res2c_relu" - type: "ReLU" -} - -layer { - bottom: "res2c" - top: "res3a_branch1" - name: "res3a_branch1" - type: "Convolution" - convolution_param { - num_output: 512 - kernel_size: 1 - pad: 0 - stride: 2 - bias_term: false - } -} - -layer { - bottom: "res3a_branch1" - top: "res3a_branch1" - name: "bn3a_branch1" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res3a_branch1" - top: "res3a_branch1" - name: "scale3a_branch1" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res2c" - top: "res3a_branch2a" - name: "res3a_branch2a" - type: "Convolution" - convolution_param { - num_output: 128 - kernel_size: 1 - pad: 0 - stride: 2 - bias_term: false - } -} - -layer { - bottom: "res3a_branch2a" - top: "res3a_branch2a" - name: "bn3a_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res3a_branch2a" - top: "res3a_branch2a" - name: "scale3a_branch2a" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res3a_branch2a" - top: "res3a_branch2a" - name: "res3a_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res3a_branch2a" - top: "res3a_branch2b" - name: "res3a_branch2b" - type: "Convolution" - convolution_param { - num_output: 128 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res3a_branch2b" - top: "res3a_branch2b" - name: "bn3a_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res3a_branch2b" - top: "res3a_branch2b" - name: "scale3a_branch2b" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res3a_branch2b" - top: "res3a_branch2b" - name: "res3a_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res3a_branch2b" - top: "res3a_branch2c" - name: "res3a_branch2c" - type: "Convolution" - convolution_param { - num_output: 512 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res3a_branch2c" - top: "res3a_branch2c" - name: "bn3a_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res3a_branch2c" - top: "res3a_branch2c" - name: "scale3a_branch2c" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res3a_branch1" - bottom: "res3a_branch2c" - top: "res3a" - name: "res3a" - type: "Eltwise" -} - -layer { - bottom: "res3a" - top: "res3a" - name: "res3a_relu" - type: "ReLU" -} - -layer { - bottom: "res3a" - top: "res3b_branch2a" - name: "res3b_branch2a" - type: "Convolution" - convolution_param { - num_output: 128 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res3b_branch2a" - top: "res3b_branch2a" - name: "bn3b_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res3b_branch2a" - top: "res3b_branch2a" - name: "scale3b_branch2a" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res3b_branch2a" - top: "res3b_branch2a" - name: "res3b_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res3b_branch2a" - top: "res3b_branch2b" - name: "res3b_branch2b" - type: "Convolution" - convolution_param { - num_output: 128 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res3b_branch2b" - top: "res3b_branch2b" - name: "bn3b_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res3b_branch2b" - top: "res3b_branch2b" - name: "scale3b_branch2b" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res3b_branch2b" - top: "res3b_branch2b" - name: "res3b_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res3b_branch2b" - top: "res3b_branch2c" - name: "res3b_branch2c" - type: "Convolution" - convolution_param { - num_output: 512 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res3b_branch2c" - top: "res3b_branch2c" - name: "bn3b_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res3b_branch2c" - top: "res3b_branch2c" - name: "scale3b_branch2c" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res3a" - bottom: "res3b_branch2c" - top: "res3b" - name: "res3b" - type: "Eltwise" -} - -layer { - bottom: "res3b" - top: "res3b" - name: "res3b_relu" - type: "ReLU" -} - -layer { - bottom: "res3b" - top: "res3c_branch2a" - name: "res3c_branch2a" - type: "Convolution" - convolution_param { - num_output: 128 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res3c_branch2a" - top: "res3c_branch2a" - name: "bn3c_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res3c_branch2a" - top: "res3c_branch2a" - name: "scale3c_branch2a" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res3c_branch2a" - top: "res3c_branch2a" - name: "res3c_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res3c_branch2a" - top: "res3c_branch2b" - name: "res3c_branch2b" - type: "Convolution" - convolution_param { - num_output: 128 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res3c_branch2b" - top: "res3c_branch2b" - name: "bn3c_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res3c_branch2b" - top: "res3c_branch2b" - name: "scale3c_branch2b" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res3c_branch2b" - top: "res3c_branch2b" - name: "res3c_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res3c_branch2b" - top: "res3c_branch2c" - name: "res3c_branch2c" - type: "Convolution" - convolution_param { - num_output: 512 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res3c_branch2c" - top: "res3c_branch2c" - name: "bn3c_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res3c_branch2c" - top: "res3c_branch2c" - name: "scale3c_branch2c" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res3b" - bottom: "res3c_branch2c" - top: "res3c" - name: "res3c" - type: "Eltwise" -} - -layer { - bottom: "res3c" - top: "res3c" - name: "res3c_relu" - type: "ReLU" -} - -layer { - bottom: "res3c" - top: "res3d_branch2a" - name: "res3d_branch2a" - type: "Convolution" - convolution_param { - num_output: 128 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res3d_branch2a" - top: "res3d_branch2a" - name: "bn3d_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res3d_branch2a" - top: "res3d_branch2a" - name: "scale3d_branch2a" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res3d_branch2a" - top: "res3d_branch2a" - name: "res3d_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res3d_branch2a" - top: "res3d_branch2b" - name: "res3d_branch2b" - type: "Convolution" - convolution_param { - num_output: 128 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res3d_branch2b" - top: "res3d_branch2b" - name: "bn3d_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res3d_branch2b" - top: "res3d_branch2b" - name: "scale3d_branch2b" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res3d_branch2b" - top: "res3d_branch2b" - name: "res3d_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res3d_branch2b" - top: "res3d_branch2c" - name: "res3d_branch2c" - type: "Convolution" - convolution_param { - num_output: 512 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res3d_branch2c" - top: "res3d_branch2c" - name: "bn3d_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res3d_branch2c" - top: "res3d_branch2c" - name: "scale3d_branch2c" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res3c" - bottom: "res3d_branch2c" - top: "res3d" - name: "res3d" - type: "Eltwise" -} - -layer { - bottom: "res3d" - top: "res3d" - name: "res3d_relu" - type: "ReLU" -} - -layer { - bottom: "res3d" - top: "res4a_branch1" - name: "res4a_branch1" - type: "Convolution" - convolution_param { - num_output: 1024 - kernel_size: 1 - pad: 0 - stride: 2 - bias_term: false - } -} - -layer { - bottom: "res4a_branch1" - top: "res4a_branch1" - name: "bn4a_branch1" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res4a_branch1" - top: "res4a_branch1" - name: "scale4a_branch1" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res3d" - top: "res4a_branch2a" - name: "res4a_branch2a" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 1 - pad: 0 - stride: 2 - bias_term: false - } -} - -layer { - bottom: "res4a_branch2a" - top: "res4a_branch2a" - name: "bn4a_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res4a_branch2a" - top: "res4a_branch2a" - name: "scale4a_branch2a" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res4a_branch2a" - top: "res4a_branch2a" - name: "res4a_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res4a_branch2a" - top: "res4a_branch2b" - name: "res4a_branch2b" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res4a_branch2b" - top: "res4a_branch2b" - name: "bn4a_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res4a_branch2b" - top: "res4a_branch2b" - name: "scale4a_branch2b" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res4a_branch2b" - top: "res4a_branch2b" - name: "res4a_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res4a_branch2b" - top: "res4a_branch2c" - name: "res4a_branch2c" - type: "Convolution" - convolution_param { - num_output: 1024 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res4a_branch2c" - top: "res4a_branch2c" - name: "bn4a_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res4a_branch2c" - top: "res4a_branch2c" - name: "scale4a_branch2c" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res4a_branch1" - bottom: "res4a_branch2c" - top: "res4a" - name: "res4a" - type: "Eltwise" -} - -layer { - bottom: "res4a" - top: "res4a" - name: "res4a_relu" - type: "ReLU" -} - -layer { - bottom: "res4a" - top: "res4b_branch2a" - name: "res4b_branch2a" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res4b_branch2a" - top: "res4b_branch2a" - name: "bn4b_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res4b_branch2a" - top: "res4b_branch2a" - name: "scale4b_branch2a" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res4b_branch2a" - top: "res4b_branch2a" - name: "res4b_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res4b_branch2a" - top: "res4b_branch2b" - name: "res4b_branch2b" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res4b_branch2b" - top: "res4b_branch2b" - name: "bn4b_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res4b_branch2b" - top: "res4b_branch2b" - name: "scale4b_branch2b" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res4b_branch2b" - top: "res4b_branch2b" - name: "res4b_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res4b_branch2b" - top: "res4b_branch2c" - name: "res4b_branch2c" - type: "Convolution" - convolution_param { - num_output: 1024 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res4b_branch2c" - top: "res4b_branch2c" - name: "bn4b_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res4b_branch2c" - top: "res4b_branch2c" - name: "scale4b_branch2c" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res4a" - bottom: "res4b_branch2c" - top: "res4b" - name: "res4b" - type: "Eltwise" -} - -layer { - bottom: "res4b" - top: "res4b" - name: "res4b_relu" - type: "ReLU" -} - -layer { - bottom: "res4b" - top: "res4c_branch2a" - name: "res4c_branch2a" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res4c_branch2a" - top: "res4c_branch2a" - name: "bn4c_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res4c_branch2a" - top: "res4c_branch2a" - name: "scale4c_branch2a" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res4c_branch2a" - top: "res4c_branch2a" - name: "res4c_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res4c_branch2a" - top: "res4c_branch2b" - name: "res4c_branch2b" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res4c_branch2b" - top: "res4c_branch2b" - name: "bn4c_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res4c_branch2b" - top: "res4c_branch2b" - name: "scale4c_branch2b" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res4c_branch2b" - top: "res4c_branch2b" - name: "res4c_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res4c_branch2b" - top: "res4c_branch2c" - name: "res4c_branch2c" - type: "Convolution" - convolution_param { - num_output: 1024 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res4c_branch2c" - top: "res4c_branch2c" - name: "bn4c_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res4c_branch2c" - top: "res4c_branch2c" - name: "scale4c_branch2c" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res4b" - bottom: "res4c_branch2c" - top: "res4c" - name: "res4c" - type: "Eltwise" -} - -layer { - bottom: "res4c" - top: "res4c" - name: "res4c_relu" - type: "ReLU" -} - -layer { - bottom: "res4c" - top: "res4d_branch2a" - name: "res4d_branch2a" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res4d_branch2a" - top: "res4d_branch2a" - name: "bn4d_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res4d_branch2a" - top: "res4d_branch2a" - name: "scale4d_branch2a" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res4d_branch2a" - top: "res4d_branch2a" - name: "res4d_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res4d_branch2a" - top: "res4d_branch2b" - name: "res4d_branch2b" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res4d_branch2b" - top: "res4d_branch2b" - name: "bn4d_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res4d_branch2b" - top: "res4d_branch2b" - name: "scale4d_branch2b" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res4d_branch2b" - top: "res4d_branch2b" - name: "res4d_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res4d_branch2b" - top: "res4d_branch2c" - name: "res4d_branch2c" - type: "Convolution" - convolution_param { - num_output: 1024 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res4d_branch2c" - top: "res4d_branch2c" - name: "bn4d_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res4d_branch2c" - top: "res4d_branch2c" - name: "scale4d_branch2c" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res4c" - bottom: "res4d_branch2c" - top: "res4d" - name: "res4d" - type: "Eltwise" -} - -layer { - bottom: "res4d" - top: "res4d" - name: "res4d_relu" - type: "ReLU" -} - -layer { - bottom: "res4d" - top: "res4e_branch2a" - name: "res4e_branch2a" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res4e_branch2a" - top: "res4e_branch2a" - name: "bn4e_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res4e_branch2a" - top: "res4e_branch2a" - name: "scale4e_branch2a" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res4e_branch2a" - top: "res4e_branch2a" - name: "res4e_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res4e_branch2a" - top: "res4e_branch2b" - name: "res4e_branch2b" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res4e_branch2b" - top: "res4e_branch2b" - name: "bn4e_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res4e_branch2b" - top: "res4e_branch2b" - name: "scale4e_branch2b" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res4e_branch2b" - top: "res4e_branch2b" - name: "res4e_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res4e_branch2b" - top: "res4e_branch2c" - name: "res4e_branch2c" - type: "Convolution" - convolution_param { - num_output: 1024 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res4e_branch2c" - top: "res4e_branch2c" - name: "bn4e_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res4e_branch2c" - top: "res4e_branch2c" - name: "scale4e_branch2c" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res4d" - bottom: "res4e_branch2c" - top: "res4e" - name: "res4e" - type: "Eltwise" -} - -layer { - bottom: "res4e" - top: "res4e" - name: "res4e_relu" - type: "ReLU" -} - -layer { - bottom: "res4e" - top: "res4f_branch2a" - name: "res4f_branch2a" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res4f_branch2a" - top: "res4f_branch2a" - name: "bn4f_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res4f_branch2a" - top: "res4f_branch2a" - name: "scale4f_branch2a" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res4f_branch2a" - top: "res4f_branch2a" - name: "res4f_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res4f_branch2a" - top: "res4f_branch2b" - name: "res4f_branch2b" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res4f_branch2b" - top: "res4f_branch2b" - name: "bn4f_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res4f_branch2b" - top: "res4f_branch2b" - name: "scale4f_branch2b" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res4f_branch2b" - top: "res4f_branch2b" - name: "res4f_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res4f_branch2b" - top: "res4f_branch2c" - name: "res4f_branch2c" - type: "Convolution" - convolution_param { - num_output: 1024 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res4f_branch2c" - top: "res4f_branch2c" - name: "bn4f_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res4f_branch2c" - top: "res4f_branch2c" - name: "scale4f_branch2c" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res4e" - bottom: "res4f_branch2c" - top: "res4f" - name: "res4f" - type: "Eltwise" -} - -layer { - bottom: "res4f" - top: "res4f" - name: "res4f_relu" - type: "ReLU" -} - -layer { - bottom: "res4f" - top: "res5a_branch1" - name: "res5a_branch1" - type: "Convolution" - convolution_param { - num_output: 2048 - kernel_size: 1 - pad: 0 - stride: 2 - bias_term: false - } -} - -layer { - bottom: "res5a_branch1" - top: "res5a_branch1" - name: "bn5a_branch1" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res5a_branch1" - top: "res5a_branch1" - name: "scale5a_branch1" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res4f" - top: "res5a_branch2a" - name: "res5a_branch2a" - type: "Convolution" - convolution_param { - num_output: 512 - kernel_size: 1 - pad: 0 - stride: 2 - bias_term: false - } -} - -layer { - bottom: "res5a_branch2a" - top: "res5a_branch2a" - name: "bn5a_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res5a_branch2a" - top: "res5a_branch2a" - name: "scale5a_branch2a" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res5a_branch2a" - top: "res5a_branch2a" - name: "res5a_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res5a_branch2a" - top: "res5a_branch2b" - name: "res5a_branch2b" - type: "Convolution" - convolution_param { - num_output: 512 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res5a_branch2b" - top: "res5a_branch2b" - name: "bn5a_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res5a_branch2b" - top: "res5a_branch2b" - name: "scale5a_branch2b" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res5a_branch2b" - top: "res5a_branch2b" - name: "res5a_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res5a_branch2b" - top: "res5a_branch2c" - name: "res5a_branch2c" - type: "Convolution" - convolution_param { - num_output: 2048 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res5a_branch2c" - top: "res5a_branch2c" - name: "bn5a_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res5a_branch2c" - top: "res5a_branch2c" - name: "scale5a_branch2c" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res5a_branch1" - bottom: "res5a_branch2c" - top: "res5a" - name: "res5a" - type: "Eltwise" -} - -layer { - bottom: "res5a" - top: "res5a" - name: "res5a_relu" - type: "ReLU" -} - -layer { - bottom: "res5a" - top: "res5b_branch2a" - name: "res5b_branch2a" - type: "Convolution" - convolution_param { - num_output: 512 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res5b_branch2a" - top: "res5b_branch2a" - name: "bn5b_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res5b_branch2a" - top: "res5b_branch2a" - name: "scale5b_branch2a" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res5b_branch2a" - top: "res5b_branch2a" - name: "res5b_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res5b_branch2a" - top: "res5b_branch2b" - name: "res5b_branch2b" - type: "Convolution" - convolution_param { - num_output: 512 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res5b_branch2b" - top: "res5b_branch2b" - name: "bn5b_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res5b_branch2b" - top: "res5b_branch2b" - name: "scale5b_branch2b" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res5b_branch2b" - top: "res5b_branch2b" - name: "res5b_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res5b_branch2b" - top: "res5b_branch2c" - name: "res5b_branch2c" - type: "Convolution" - convolution_param { - num_output: 2048 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res5b_branch2c" - top: "res5b_branch2c" - name: "bn5b_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res5b_branch2c" - top: "res5b_branch2c" - name: "scale5b_branch2c" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res5a" - bottom: "res5b_branch2c" - top: "res5b" - name: "res5b" - type: "Eltwise" -} - -layer { - bottom: "res5b" - top: "res5b" - name: "res5b_relu" - type: "ReLU" -} - -layer { - bottom: "res5b" - top: "res5c_branch2a" - name: "res5c_branch2a" - type: "Convolution" - convolution_param { - num_output: 512 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res5c_branch2a" - top: "res5c_branch2a" - name: "bn5c_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res5c_branch2a" - top: "res5c_branch2a" - name: "scale5c_branch2a" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res5c_branch2a" - top: "res5c_branch2a" - name: "res5c_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res5c_branch2a" - top: "res5c_branch2b" - name: "res5c_branch2b" - type: "Convolution" - convolution_param { - num_output: 512 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res5c_branch2b" - top: "res5c_branch2b" - name: "bn5c_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res5c_branch2b" - top: "res5c_branch2b" - name: "scale5c_branch2b" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res5c_branch2b" - top: "res5c_branch2b" - name: "res5c_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res5c_branch2b" - top: "res5c_branch2c" - name: "res5c_branch2c" - type: "Convolution" - convolution_param { - num_output: 2048 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } -} - -layer { - bottom: "res5c_branch2c" - top: "res5c_branch2c" - name: "bn5c_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } -} - -layer { - bottom: "res5c_branch2c" - top: "res5c_branch2c" - name: "scale5c_branch2c" - type: "Scale" - scale_param { - bias_term: true - } -} - -layer { - bottom: "res5b" - bottom: "res5c_branch2c" - top: "res5c" - name: "res5c" - type: "Eltwise" -} - -layer { - bottom: "res5c" - top: "res5c" - name: "res5c_relu" - type: "ReLU" -} - -layer { - bottom: "res5c" - top: "pool5" - name: "pool5" - type: "Pooling" - pooling_param { - kernel_size: 7 - stride: 1 - pool: AVE - } -} - -layer { - bottom: "pool5" - top: "fc1000" - name: "fc1000" - type: "InnerProduct" - inner_product_param { - num_output: 1000 - } -} - -layer { - bottom: "fc1000" - top: "prob" - name: "prob" - type: "Softmax" -} - diff --git a/testdata/dnn/axpy.prototxt b/testdata/dnn/axpy.prototxt deleted file mode 100644 index 310b092e4..000000000 --- a/testdata/dnn/axpy.prototxt +++ /dev/null @@ -1,38 +0,0 @@ -name: "TestAxpy" - -input: "scale" -input_shape -{ - dim: 1 - dim: 2 - dim: 1 - dim: 1 -} - - -input: "shift" -input_shape -{ - dim: 1 - dim: 2 - dim: 3 - dim: 4 -} - -input: "data" -input_shape -{ - dim: 1 - dim: 2 - dim: 3 - dim: 4 -} - -layer { - name: "axpy" - type: "Axpy" - bottom: "scale" - bottom: "shift" - bottom: "data" - top: "axpy" -} diff --git a/testdata/dnn/bvlc_alexnet.prototxt b/testdata/dnn/bvlc_alexnet.prototxt deleted file mode 100644 index b51fb737e..000000000 --- a/testdata/dnn/bvlc_alexnet.prototxt +++ /dev/null @@ -1,276 +0,0 @@ -name: "AlexNet" -input: "data" -input_dim: 1 -input_dim: 3 -input_dim: 227 -input_dim: 227 -layer { - name: "conv1" - type: "Convolution" - bottom: "data" - top: "conv1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 96 - kernel_size: 11 - stride: 4 - } -} -layer { - name: "relu1" - type: "ReLU" - bottom: "conv1" - top: "conv1" -} -layer { - name: "norm1" - type: "LRN" - bottom: "conv1" - top: "norm1" - lrn_param { - local_size: 5 - alpha: 0.0001 - beta: 0.75 - } -} -layer { - name: "pool1" - type: "Pooling" - bottom: "norm1" - top: "pool1" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 2 - } -} -layer { - name: "conv2" - type: "Convolution" - bottom: "pool1" - top: "conv2" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 2 - kernel_size: 5 - group: 2 - } -} -layer { - name: "relu2" - type: "ReLU" - bottom: "conv2" - top: "conv2" -} -layer { - name: "norm2" - type: "LRN" - bottom: "conv2" - top: "norm2" - lrn_param { - local_size: 5 - alpha: 0.0001 - beta: 0.75 - } -} -layer { - name: "pool2" - type: "Pooling" - bottom: "norm2" - top: "pool2" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 2 - } -} -layer { - name: "conv3" - type: "Convolution" - bottom: "pool2" - top: "conv3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 384 - pad: 1 - kernel_size: 3 - } -} -layer { - name: "relu3" - type: "ReLU" - bottom: "conv3" - top: "conv3" -} -layer { - name: "conv4" - type: "Convolution" - bottom: "conv3" - top: "conv4" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 384 - pad: 1 - kernel_size: 3 - group: 2 - } -} -layer { - name: "relu4" - type: "ReLU" - bottom: "conv4" - top: "conv4" -} -layer { - name: "conv5" - type: "Convolution" - bottom: "conv4" - top: "conv5" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - group: 2 - } -} -layer { - name: "relu5" - type: "ReLU" - bottom: "conv5" - top: "conv5" -} -layer { - name: "pool5" - type: "Pooling" - bottom: "conv5" - top: "pool5" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 2 - } -} -layer { - name: "fc6" - type: "InnerProduct" - bottom: "pool5" - top: "fc6" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - inner_product_param { - num_output: 4096 - } -} -layer { - name: "relu6" - type: "ReLU" - bottom: "fc6" - top: "fc6" -} -layer { - name: "drop6" - type: "Dropout" - bottom: "fc6" - top: "fc6" - dropout_param { - dropout_ratio: 0.5 - } -} -layer { - name: "fc7" - type: "InnerProduct" - bottom: "fc6" - top: "fc7" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - inner_product_param { - num_output: 4096 - } -} -layer { - name: "relu7" - type: "ReLU" - bottom: "fc7" - top: "fc7" -} -layer { - name: "drop7" - type: "Dropout" - bottom: "fc7" - top: "fc7" - dropout_param { - dropout_ratio: 0.5 - } -} -layer { - name: "fc8" - type: "InnerProduct" - bottom: "fc7" - top: "fc8" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - inner_product_param { - num_output: 1000 - } -} -layer { - name: "prob" - type: "Softmax" - bottom: "fc8" - top: "prob" -} diff --git a/testdata/dnn/bvlc_googlenet.prototxt b/testdata/dnn/bvlc_googlenet.prototxt deleted file mode 100644 index 414e3559c..000000000 --- a/testdata/dnn/bvlc_googlenet.prototxt +++ /dev/null @@ -1,2156 +0,0 @@ -name: "GoogleNet" -input: "data" -input_dim: 1 -input_dim: 3 -input_dim: 224 -input_dim: 224 -layer { - name: "conv1/7x7_s2" - type: "Convolution" - bottom: "data" - top: "conv1/7x7_s2" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - pad: 3 - kernel_size: 7 - stride: 2 - weight_filler { - type: "xavier" - std: 0.1 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "conv1/relu_7x7" - type: "ReLU" - bottom: "conv1/7x7_s2" - top: "conv1/7x7_s2" -} -layer { - name: "pool1/3x3_s2" - type: "Pooling" - bottom: "conv1/7x7_s2" - top: "pool1/3x3_s2" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 2 - } -} -layer { - name: "pool1/norm1" - type: "LRN" - bottom: "pool1/3x3_s2" - top: "pool1/norm1" - lrn_param { - local_size: 5 - alpha: 0.0001 - beta: 0.75 - } -} -layer { - name: "conv2/3x3_reduce" - type: "Convolution" - bottom: "pool1/norm1" - top: "conv2/3x3_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.1 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "conv2/relu_3x3_reduce" - type: "ReLU" - bottom: "conv2/3x3_reduce" - top: "conv2/3x3_reduce" -} -layer { - name: "conv2/3x3" - type: "Convolution" - bottom: "conv2/3x3_reduce" - top: "conv2/3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 192 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - std: 0.03 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "conv2/relu_3x3" - type: "ReLU" - bottom: "conv2/3x3" - top: "conv2/3x3" -} -layer { - name: "conv2/norm2" - type: "LRN" - bottom: "conv2/3x3" - top: "conv2/norm2" - lrn_param { - local_size: 5 - alpha: 0.0001 - beta: 0.75 - } -} -layer { - name: "pool2/3x3_s2" - type: "Pooling" - bottom: "conv2/norm2" - top: "pool2/3x3_s2" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 2 - } -} -layer { - name: "inception_3a/1x1" - type: "Convolution" - bottom: "pool2/3x3_s2" - top: "inception_3a/1x1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.03 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_3a/relu_1x1" - type: "ReLU" - bottom: "inception_3a/1x1" - top: "inception_3a/1x1" -} -layer { - name: "inception_3a/3x3_reduce" - type: "Convolution" - bottom: "pool2/3x3_s2" - top: "inception_3a/3x3_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 96 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.09 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_3a/relu_3x3_reduce" - type: "ReLU" - bottom: "inception_3a/3x3_reduce" - top: "inception_3a/3x3_reduce" -} -layer { - name: "inception_3a/3x3" - type: "Convolution" - bottom: "inception_3a/3x3_reduce" - top: "inception_3a/3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - std: 0.03 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_3a/relu_3x3" - type: "ReLU" - bottom: "inception_3a/3x3" - top: "inception_3a/3x3" -} -layer { - name: "inception_3a/5x5_reduce" - type: "Convolution" - bottom: "pool2/3x3_s2" - top: "inception_3a/5x5_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 16 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.2 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_3a/relu_5x5_reduce" - type: "ReLU" - bottom: "inception_3a/5x5_reduce" - top: "inception_3a/5x5_reduce" -} -layer { - name: "inception_3a/5x5" - type: "Convolution" - bottom: "inception_3a/5x5_reduce" - top: "inception_3a/5x5" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 32 - pad: 2 - kernel_size: 5 - weight_filler { - type: "xavier" - std: 0.03 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_3a/relu_5x5" - type: "ReLU" - bottom: "inception_3a/5x5" - top: "inception_3a/5x5" -} -layer { - name: "inception_3a/pool" - type: "Pooling" - bottom: "pool2/3x3_s2" - top: "inception_3a/pool" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - name: "inception_3a/pool_proj" - type: "Convolution" - bottom: "inception_3a/pool" - top: "inception_3a/pool_proj" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 32 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.1 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_3a/relu_pool_proj" - type: "ReLU" - bottom: "inception_3a/pool_proj" - top: "inception_3a/pool_proj" -} -layer { - name: "inception_3a/output" - type: "Concat" - bottom: "inception_3a/1x1" - bottom: "inception_3a/3x3" - bottom: "inception_3a/5x5" - bottom: "inception_3a/pool_proj" - top: "inception_3a/output" -} -layer { - name: "inception_3b/1x1" - type: "Convolution" - bottom: "inception_3a/output" - top: "inception_3b/1x1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.03 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_3b/relu_1x1" - type: "ReLU" - bottom: "inception_3b/1x1" - top: "inception_3b/1x1" -} -layer { - name: "inception_3b/3x3_reduce" - type: "Convolution" - bottom: "inception_3a/output" - top: "inception_3b/3x3_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.09 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_3b/relu_3x3_reduce" - type: "ReLU" - bottom: "inception_3b/3x3_reduce" - top: "inception_3b/3x3_reduce" -} -layer { - name: "inception_3b/3x3" - type: "Convolution" - bottom: "inception_3b/3x3_reduce" - top: "inception_3b/3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 192 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - std: 0.03 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_3b/relu_3x3" - type: "ReLU" - bottom: "inception_3b/3x3" - top: "inception_3b/3x3" -} -layer { - name: "inception_3b/5x5_reduce" - type: "Convolution" - bottom: "inception_3a/output" - top: "inception_3b/5x5_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 32 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.2 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_3b/relu_5x5_reduce" - type: "ReLU" - bottom: "inception_3b/5x5_reduce" - top: "inception_3b/5x5_reduce" -} -layer { - name: "inception_3b/5x5" - type: "Convolution" - bottom: "inception_3b/5x5_reduce" - top: "inception_3b/5x5" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 96 - pad: 2 - kernel_size: 5 - weight_filler { - type: "xavier" - std: 0.03 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_3b/relu_5x5" - type: "ReLU" - bottom: "inception_3b/5x5" - top: "inception_3b/5x5" -} -layer { - name: "inception_3b/pool" - type: "Pooling" - bottom: "inception_3a/output" - top: "inception_3b/pool" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - name: "inception_3b/pool_proj" - type: "Convolution" - bottom: "inception_3b/pool" - top: "inception_3b/pool_proj" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.1 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_3b/relu_pool_proj" - type: "ReLU" - bottom: "inception_3b/pool_proj" - top: "inception_3b/pool_proj" -} -layer { - name: "inception_3b/output" - type: "Concat" - bottom: "inception_3b/1x1" - bottom: "inception_3b/3x3" - bottom: "inception_3b/5x5" - bottom: "inception_3b/pool_proj" - top: "inception_3b/output" -} -layer { - name: "pool3/3x3_s2" - type: "Pooling" - bottom: "inception_3b/output" - top: "pool3/3x3_s2" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 2 - } -} -layer { - name: "inception_4a/1x1" - type: "Convolution" - bottom: "pool3/3x3_s2" - top: "inception_4a/1x1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 192 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.03 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4a/relu_1x1" - type: "ReLU" - bottom: "inception_4a/1x1" - top: "inception_4a/1x1" -} -layer { - name: "inception_4a/3x3_reduce" - type: "Convolution" - bottom: "pool3/3x3_s2" - top: "inception_4a/3x3_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 96 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.09 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4a/relu_3x3_reduce" - type: "ReLU" - bottom: "inception_4a/3x3_reduce" - top: "inception_4a/3x3_reduce" -} -layer { - name: "inception_4a/3x3" - type: "Convolution" - bottom: "inception_4a/3x3_reduce" - top: "inception_4a/3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 208 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - std: 0.03 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4a/relu_3x3" - type: "ReLU" - bottom: "inception_4a/3x3" - top: "inception_4a/3x3" -} -layer { - name: "inception_4a/5x5_reduce" - type: "Convolution" - bottom: "pool3/3x3_s2" - top: "inception_4a/5x5_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 16 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.2 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4a/relu_5x5_reduce" - type: "ReLU" - bottom: "inception_4a/5x5_reduce" - top: "inception_4a/5x5_reduce" -} -layer { - name: "inception_4a/5x5" - type: "Convolution" - bottom: "inception_4a/5x5_reduce" - top: "inception_4a/5x5" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 48 - pad: 2 - kernel_size: 5 - weight_filler { - type: "xavier" - std: 0.03 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4a/relu_5x5" - type: "ReLU" - bottom: "inception_4a/5x5" - top: "inception_4a/5x5" -} -layer { - name: "inception_4a/pool" - type: "Pooling" - bottom: "pool3/3x3_s2" - top: "inception_4a/pool" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - name: "inception_4a/pool_proj" - type: "Convolution" - bottom: "inception_4a/pool" - top: "inception_4a/pool_proj" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.1 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4a/relu_pool_proj" - type: "ReLU" - bottom: "inception_4a/pool_proj" - top: "inception_4a/pool_proj" -} -layer { - name: "inception_4a/output" - type: "Concat" - bottom: "inception_4a/1x1" - bottom: "inception_4a/3x3" - bottom: "inception_4a/5x5" - bottom: "inception_4a/pool_proj" - top: "inception_4a/output" -} -layer { - name: "inception_4b/1x1" - type: "Convolution" - bottom: "inception_4a/output" - top: "inception_4b/1x1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 160 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.03 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4b/relu_1x1" - type: "ReLU" - bottom: "inception_4b/1x1" - top: "inception_4b/1x1" -} -layer { - name: "inception_4b/3x3_reduce" - type: "Convolution" - bottom: "inception_4a/output" - top: "inception_4b/3x3_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 112 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.09 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4b/relu_3x3_reduce" - type: "ReLU" - bottom: "inception_4b/3x3_reduce" - top: "inception_4b/3x3_reduce" -} -layer { - name: "inception_4b/3x3" - type: "Convolution" - bottom: "inception_4b/3x3_reduce" - top: "inception_4b/3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 224 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - std: 0.03 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4b/relu_3x3" - type: "ReLU" - bottom: "inception_4b/3x3" - top: "inception_4b/3x3" -} -layer { - name: "inception_4b/5x5_reduce" - type: "Convolution" - bottom: "inception_4a/output" - top: "inception_4b/5x5_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 24 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.2 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4b/relu_5x5_reduce" - type: "ReLU" - bottom: "inception_4b/5x5_reduce" - top: "inception_4b/5x5_reduce" -} -layer { - name: "inception_4b/5x5" - type: "Convolution" - bottom: "inception_4b/5x5_reduce" - top: "inception_4b/5x5" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - pad: 2 - kernel_size: 5 - weight_filler { - type: "xavier" - std: 0.03 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4b/relu_5x5" - type: "ReLU" - bottom: "inception_4b/5x5" - top: "inception_4b/5x5" -} -layer { - name: "inception_4b/pool" - type: "Pooling" - bottom: "inception_4a/output" - top: "inception_4b/pool" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - name: "inception_4b/pool_proj" - type: "Convolution" - bottom: "inception_4b/pool" - top: "inception_4b/pool_proj" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.1 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4b/relu_pool_proj" - type: "ReLU" - bottom: "inception_4b/pool_proj" - top: "inception_4b/pool_proj" -} -layer { - name: "inception_4b/output" - type: "Concat" - bottom: "inception_4b/1x1" - bottom: "inception_4b/3x3" - bottom: "inception_4b/5x5" - bottom: "inception_4b/pool_proj" - top: "inception_4b/output" -} -layer { - name: "inception_4c/1x1" - type: "Convolution" - bottom: "inception_4b/output" - top: "inception_4c/1x1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.03 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4c/relu_1x1" - type: "ReLU" - bottom: "inception_4c/1x1" - top: "inception_4c/1x1" -} -layer { - name: "inception_4c/3x3_reduce" - type: "Convolution" - bottom: "inception_4b/output" - top: "inception_4c/3x3_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.09 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4c/relu_3x3_reduce" - type: "ReLU" - bottom: "inception_4c/3x3_reduce" - top: "inception_4c/3x3_reduce" -} -layer { - name: "inception_4c/3x3" - type: "Convolution" - bottom: "inception_4c/3x3_reduce" - top: "inception_4c/3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - std: 0.03 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4c/relu_3x3" - type: "ReLU" - bottom: "inception_4c/3x3" - top: "inception_4c/3x3" -} -layer { - name: "inception_4c/5x5_reduce" - type: "Convolution" - bottom: "inception_4b/output" - top: "inception_4c/5x5_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 24 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.2 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4c/relu_5x5_reduce" - type: "ReLU" - bottom: "inception_4c/5x5_reduce" - top: "inception_4c/5x5_reduce" -} -layer { - name: "inception_4c/5x5" - type: "Convolution" - bottom: "inception_4c/5x5_reduce" - top: "inception_4c/5x5" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - pad: 2 - kernel_size: 5 - weight_filler { - type: "xavier" - std: 0.03 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4c/relu_5x5" - type: "ReLU" - bottom: "inception_4c/5x5" - top: "inception_4c/5x5" -} -layer { - name: "inception_4c/pool" - type: "Pooling" - bottom: "inception_4b/output" - top: "inception_4c/pool" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - name: "inception_4c/pool_proj" - type: "Convolution" - bottom: "inception_4c/pool" - top: "inception_4c/pool_proj" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.1 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4c/relu_pool_proj" - type: "ReLU" - bottom: "inception_4c/pool_proj" - top: "inception_4c/pool_proj" -} -layer { - name: "inception_4c/output" - type: "Concat" - bottom: "inception_4c/1x1" - bottom: "inception_4c/3x3" - bottom: "inception_4c/5x5" - bottom: "inception_4c/pool_proj" - top: "inception_4c/output" -} -layer { - name: "inception_4d/1x1" - type: "Convolution" - bottom: "inception_4c/output" - top: "inception_4d/1x1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 112 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.03 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4d/relu_1x1" - type: "ReLU" - bottom: "inception_4d/1x1" - top: "inception_4d/1x1" -} -layer { - name: "inception_4d/3x3_reduce" - type: "Convolution" - bottom: "inception_4c/output" - top: "inception_4d/3x3_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 144 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.09 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4d/relu_3x3_reduce" - type: "ReLU" - bottom: "inception_4d/3x3_reduce" - top: "inception_4d/3x3_reduce" -} -layer { - name: "inception_4d/3x3" - type: "Convolution" - bottom: "inception_4d/3x3_reduce" - top: "inception_4d/3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 288 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - std: 0.03 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4d/relu_3x3" - type: "ReLU" - bottom: "inception_4d/3x3" - top: "inception_4d/3x3" -} -layer { - name: "inception_4d/5x5_reduce" - type: "Convolution" - bottom: "inception_4c/output" - top: "inception_4d/5x5_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 32 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.2 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4d/relu_5x5_reduce" - type: "ReLU" - bottom: "inception_4d/5x5_reduce" - top: "inception_4d/5x5_reduce" -} -layer { - name: "inception_4d/5x5" - type: "Convolution" - bottom: "inception_4d/5x5_reduce" - top: "inception_4d/5x5" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - pad: 2 - kernel_size: 5 - weight_filler { - type: "xavier" - std: 0.03 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4d/relu_5x5" - type: "ReLU" - bottom: "inception_4d/5x5" - top: "inception_4d/5x5" -} -layer { - name: "inception_4d/pool" - type: "Pooling" - bottom: "inception_4c/output" - top: "inception_4d/pool" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - name: "inception_4d/pool_proj" - type: "Convolution" - bottom: "inception_4d/pool" - top: "inception_4d/pool_proj" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.1 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4d/relu_pool_proj" - type: "ReLU" - bottom: "inception_4d/pool_proj" - top: "inception_4d/pool_proj" -} -layer { - name: "inception_4d/output" - type: "Concat" - bottom: "inception_4d/1x1" - bottom: "inception_4d/3x3" - bottom: "inception_4d/5x5" - bottom: "inception_4d/pool_proj" - top: "inception_4d/output" -} -layer { - name: "inception_4e/1x1" - type: "Convolution" - bottom: "inception_4d/output" - top: "inception_4e/1x1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 256 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.03 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4e/relu_1x1" - type: "ReLU" - bottom: "inception_4e/1x1" - top: "inception_4e/1x1" -} -layer { - name: "inception_4e/3x3_reduce" - type: "Convolution" - bottom: "inception_4d/output" - top: "inception_4e/3x3_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 160 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.09 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4e/relu_3x3_reduce" - type: "ReLU" - bottom: "inception_4e/3x3_reduce" - top: "inception_4e/3x3_reduce" -} -layer { - name: "inception_4e/3x3" - type: "Convolution" - bottom: "inception_4e/3x3_reduce" - top: "inception_4e/3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 320 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - std: 0.03 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4e/relu_3x3" - type: "ReLU" - bottom: "inception_4e/3x3" - top: "inception_4e/3x3" -} -layer { - name: "inception_4e/5x5_reduce" - type: "Convolution" - bottom: "inception_4d/output" - top: "inception_4e/5x5_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 32 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.2 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4e/relu_5x5_reduce" - type: "ReLU" - bottom: "inception_4e/5x5_reduce" - top: "inception_4e/5x5_reduce" -} -layer { - name: "inception_4e/5x5" - type: "Convolution" - bottom: "inception_4e/5x5_reduce" - top: "inception_4e/5x5" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 2 - kernel_size: 5 - weight_filler { - type: "xavier" - std: 0.03 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4e/relu_5x5" - type: "ReLU" - bottom: "inception_4e/5x5" - top: "inception_4e/5x5" -} -layer { - name: "inception_4e/pool" - type: "Pooling" - bottom: "inception_4d/output" - top: "inception_4e/pool" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - name: "inception_4e/pool_proj" - type: "Convolution" - bottom: "inception_4e/pool" - top: "inception_4e/pool_proj" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.1 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_4e/relu_pool_proj" - type: "ReLU" - bottom: "inception_4e/pool_proj" - top: "inception_4e/pool_proj" -} -layer { - name: "inception_4e/output" - type: "Concat" - bottom: "inception_4e/1x1" - bottom: "inception_4e/3x3" - bottom: "inception_4e/5x5" - bottom: "inception_4e/pool_proj" - top: "inception_4e/output" -} -layer { - name: "pool4/3x3_s2" - type: "Pooling" - bottom: "inception_4e/output" - top: "pool4/3x3_s2" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 2 - } -} -layer { - name: "inception_5a/1x1" - type: "Convolution" - bottom: "pool4/3x3_s2" - top: "inception_5a/1x1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 256 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.03 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_5a/relu_1x1" - type: "ReLU" - bottom: "inception_5a/1x1" - top: "inception_5a/1x1" -} -layer { - name: "inception_5a/3x3_reduce" - type: "Convolution" - bottom: "pool4/3x3_s2" - top: "inception_5a/3x3_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 160 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.09 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_5a/relu_3x3_reduce" - type: "ReLU" - bottom: "inception_5a/3x3_reduce" - top: "inception_5a/3x3_reduce" -} -layer { - name: "inception_5a/3x3" - type: "Convolution" - bottom: "inception_5a/3x3_reduce" - top: "inception_5a/3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 320 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - std: 0.03 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_5a/relu_3x3" - type: "ReLU" - bottom: "inception_5a/3x3" - top: "inception_5a/3x3" -} -layer { - name: "inception_5a/5x5_reduce" - type: "Convolution" - bottom: "pool4/3x3_s2" - top: "inception_5a/5x5_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 32 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.2 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_5a/relu_5x5_reduce" - type: "ReLU" - bottom: "inception_5a/5x5_reduce" - top: "inception_5a/5x5_reduce" -} -layer { - name: "inception_5a/5x5" - type: "Convolution" - bottom: "inception_5a/5x5_reduce" - top: "inception_5a/5x5" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 2 - kernel_size: 5 - weight_filler { - type: "xavier" - std: 0.03 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_5a/relu_5x5" - type: "ReLU" - bottom: "inception_5a/5x5" - top: "inception_5a/5x5" -} -layer { - name: "inception_5a/pool" - type: "Pooling" - bottom: "pool4/3x3_s2" - top: "inception_5a/pool" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - name: "inception_5a/pool_proj" - type: "Convolution" - bottom: "inception_5a/pool" - top: "inception_5a/pool_proj" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.1 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_5a/relu_pool_proj" - type: "ReLU" - bottom: "inception_5a/pool_proj" - top: "inception_5a/pool_proj" -} -layer { - name: "inception_5a/output" - type: "Concat" - bottom: "inception_5a/1x1" - bottom: "inception_5a/3x3" - bottom: "inception_5a/5x5" - bottom: "inception_5a/pool_proj" - top: "inception_5a/output" -} -layer { - name: "inception_5b/1x1" - type: "Convolution" - bottom: "inception_5a/output" - top: "inception_5b/1x1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 384 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.03 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_5b/relu_1x1" - type: "ReLU" - bottom: "inception_5b/1x1" - top: "inception_5b/1x1" -} -layer { - name: "inception_5b/3x3_reduce" - type: "Convolution" - bottom: "inception_5a/output" - top: "inception_5b/3x3_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 192 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.09 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_5b/relu_3x3_reduce" - type: "ReLU" - bottom: "inception_5b/3x3_reduce" - top: "inception_5b/3x3_reduce" -} -layer { - name: "inception_5b/3x3" - type: "Convolution" - bottom: "inception_5b/3x3_reduce" - top: "inception_5b/3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 384 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - std: 0.03 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_5b/relu_3x3" - type: "ReLU" - bottom: "inception_5b/3x3" - top: "inception_5b/3x3" -} -layer { - name: "inception_5b/5x5_reduce" - type: "Convolution" - bottom: "inception_5a/output" - top: "inception_5b/5x5_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 48 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.2 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_5b/relu_5x5_reduce" - type: "ReLU" - bottom: "inception_5b/5x5_reduce" - top: "inception_5b/5x5_reduce" -} -layer { - name: "inception_5b/5x5" - type: "Convolution" - bottom: "inception_5b/5x5_reduce" - top: "inception_5b/5x5" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 2 - kernel_size: 5 - weight_filler { - type: "xavier" - std: 0.03 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_5b/relu_5x5" - type: "ReLU" - bottom: "inception_5b/5x5" - top: "inception_5b/5x5" -} -layer { - name: "inception_5b/pool" - type: "Pooling" - bottom: "inception_5a/output" - top: "inception_5b/pool" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - name: "inception_5b/pool_proj" - type: "Convolution" - bottom: "inception_5b/pool" - top: "inception_5b/pool_proj" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - kernel_size: 1 - weight_filler { - type: "xavier" - std: 0.1 - } - bias_filler { - type: "constant" - value: 0.2 - } - } -} -layer { - name: "inception_5b/relu_pool_proj" - type: "ReLU" - bottom: "inception_5b/pool_proj" - top: "inception_5b/pool_proj" -} -layer { - name: "inception_5b/output" - type: "Concat" - bottom: "inception_5b/1x1" - bottom: "inception_5b/3x3" - bottom: "inception_5b/5x5" - bottom: "inception_5b/pool_proj" - top: "inception_5b/output" -} -layer { - name: "pool5/7x7_s1" - type: "Pooling" - bottom: "inception_5b/output" - top: "pool5/7x7_s1" - pooling_param { - pool: AVE - kernel_size: 7 - stride: 1 - } -} -layer { - name: "pool5/drop_7x7_s1" - type: "Dropout" - bottom: "pool5/7x7_s1" - top: "pool5/7x7_s1" - dropout_param { - dropout_ratio: 0.4 - } -} -layer { - name: "loss3/classifier" - type: "InnerProduct" - bottom: "pool5/7x7_s1" - top: "loss3/classifier" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - inner_product_param { - num_output: 1000 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "prob" - type: "Softmax" - bottom: "loss3/classifier" - top: "prob" -} diff --git a/testdata/dnn/download_models.py b/testdata/dnn/download_models.py index c7013795d..fd3f1c15a 100755 --- a/testdata/dnn/download_models.py +++ b/testdata/dnn/download_models.py @@ -237,54 +237,29 @@ def is_archive(self): models = [ - Model( - name='GoogleNet', - url='http://dl.caffe.berkeleyvision.org/bvlc_googlenet.caffemodel', - sha='405fc5acd08a3bb12de8ee5e23a96bec22f08204', - filename='bvlc_googlenet.caffemodel'), - Model( - name='Alexnet', - url='http://dl.caffe.berkeleyvision.org/bvlc_alexnet.caffemodel', - sha='9116a64c0fbe4459d18f4bb6b56d647b63920377', - filename='bvlc_alexnet.caffemodel'), Model( name='Inception', url='https://github.com/petewarden/tf_ios_makefile_example/raw/master/data/tensorflow_inception_graph.pb', sha='c8a5a000ee8d8dd75886f152a50a9c5b53d726a5', filename='tensorflow_inception_graph.pb'), - Model( - name='Fcn', - url='http://dl.caffe.berkeleyvision.org/fcn8s-heavy-pascal.caffemodel', - sha='c449ea74dd7d83751d1357d6a8c323fcf4038962', - filename='fcn8s-heavy-pascal.caffemodel'), - Model( - name='Ssd_vgg16', - url='https://www.dropbox.com/s/8apyk3uzk2vl522/VGG_ILSVRC2016_SSD_300x300_iter_440000.caffemodel?dl=1', - sha='0fc294d5257f3e0c8a3c5acaa1b1f6a9b0b6ade0', - filename='VGG_ILSVRC2016_SSD_300x300_iter_440000.caffemodel'), - Model( - name='ResNet50', - url=[ - 'https://onedrive.live.com/download?cid=4006CBB8476FF777&resid=4006CBB8476FF777%2117895&authkey=%21AAFW2%2DFVoxeVRck', - 'https://dl.opencv.org/models/ResNet-50-model.caffemodel' - ], - sha='b7c79ccc21ad0479cddc0dd78b1d20c4d722908d', - filename='ResNet-50-model.caffemodel'), - Model( - name='SqueezeNet_v1.1', - url='https://raw.githubusercontent.com/DeepScale/SqueezeNet/b5c3f1a23713c8b3fd7b801d229f6b04c64374a5/SqueezeNet_v1.1/squeezenet_v1.1.caffemodel', - sha='3397f026368a45ae236403ccc81cfcbe8ebe1bd0', - filename='squeezenet_v1.1.caffemodel'), - Model( - name='MobileNet-SSD (caffemodel)', # https://github.com/chuanqi305/MobileNet-SSD - url='https://raw.githubusercontent.com/chuanqi305/MobileNet-SSD/97406996b1eee2d40eb0a00ae567cf41e23369f9/mobilenet_iter_73000.caffemodel', - sha='19e3ec38842f3e68b02c07a1c24424a1e9db57e9', - filename='MobileNetSSD_deploy_19e3ec3.caffemodel'), - Model( - name='MobileNet-SSD (prototxt)', - url='https://raw.githubusercontent.com/chuanqi305/MobileNet-SSD/97406996b1eee2d40eb0a00ae567cf41e23369f9/deploy.prototxt', - sha='50cf80235a8fcccc641bf9f8efc803edbf21c615', - filename='MobileNetSSD_deploy_19e3ec3.prototxt'), + # Disabled due to the lack of the model support. https://github.com/opencv/opencv/issues/25314 + # Model( + # name='Fcn', + # url='https://github.com/onnx/models/raw/491ce05590abb7551d7fae43c067c060eeb575a6/validated/vision/object_detection_segmentation/fcn/model/fcn-resnet50-12.onnx', + # sha='', + # filename='onnx/models/fcn-resnet50-12.onnx'), + # Disabled due to the lack of the model support. https://github.com/opencv/opencv/issues/25314 + # Model( + # name='ssd', + # url='https://github.com/onnx/models/raw/491ce05590abb7551d7fae43c067c060eeb575a6/validated/vision/object_detection_segmentation/ssd/model/ssd-12.onnx', + # sha='20c86b1cbd0a4be6194e40bb8c92cf0401adee8b', + # filename='onnx/models/ssd-12.onnx'), + # Disabled due to the lack of the model support. https://github.com/opencv/opencv/issues/25314 + # Model( + # name='MobileNet-SSD', + # url='https://github.com/onnx/models/raw/491ce05590abb7551d7fae43c067c060eeb575a6/validated/vision/object_detection_segmentation/ssd-mobilenetv1/model/ssd_mobilenet_v1_12.onnx', + # sha='83536889adce1eda154175f8e3b156dd20443631', + # filename='onnx/models/ssd_mobilenet_v1_12.onnx'), Model( name='YoloV2voc', # https://pjreddie.com/darknet/yolo/ url='https://pjreddie.com/media/files/yolo-voc.weights', @@ -296,15 +271,10 @@ def is_archive(self): sha='24b4bd049fc4fa5f5e95f684a8967e65c625dff9', filename='tiny-yolo-voc.weights'), Model( - name='DenseNet-121 (caffemodel)', # https://github.com/shicai/DenseNet-Caffe - url='https://drive.google.com/uc?export=download&id=0B7ubpZO7HnlCcHlfNmJkU2VPelE', - sha='02b520138e8a73c94473b05879978018fefe947b', - filename='DenseNet_121.caffemodel'), - Model( - name='DenseNet-121 (prototxt)', - url='https://raw.githubusercontent.com/shicai/DenseNet-Caffe/master/DenseNet_121.prototxt', - sha='4922099342af5993d9d09f63081c8a392f3c1cc6', - filename='DenseNet_121.prototxt'), + name='DenseNet-121 (ONNX)', + url='https://github.com/onnx/models/raw/491ce05590abb7551d7fae43c067c060eeb575a6/validated/vision/classification/densenet-121/model/densenet-12.onnx', + sha='4f4fe414af50b5fc2675eb1e6fdf5d712eeee735', + filename='onnx/models/densenet-12.onnx'), Model( name='Fast-Neural-Style', url=[ @@ -352,24 +322,21 @@ def is_archive(self): url='https://raw.githubusercontent.com/richzhang/colorization/caffe/models/colorization_deploy_v2.prototxt', sha='f528334e386a69cbaaf237a7611d833bef8e5219', filename='colorization_deploy_v2.prototxt'), - Model( - name='Colorization (caffemodel)', - url=[ - 'http://eecs.berkeley.edu/~rich.zhang/projects/2016_colorization/files/demo_v2/colorization_release_v2.caffemodel', - 'https://dl.opencv.org/models/colorization_release_v2.caffemodel' - ], - sha='21e61293a3fa6747308171c11b6dd18a68a26e7f', - filename='colorization_release_v2.caffemodel'), - Model( - name='Face_detector', - url='https://github.com/opencv/opencv_3rdparty/raw/dnn_samples_face_detector_20170830/res10_300x300_ssd_iter_140000.caffemodel', - sha='15aa726b4d46d9f023526d85537db81cbc8dd566', - filename='opencv_face_detector.caffemodel'), - Model( - name='Face_detector (FP16)', - url='https://github.com/opencv/opencv_3rdparty/raw/19512576c112aa2c7b6328cb0e8d589a4a90a26d/res10_300x300_ssd_iter_140000_fp16.caffemodel', - sha='31fc22bfdd907567a04bb45b7cfad29966caddc1', - filename='opencv_face_detector_fp16.caffemodel'), + # Disabled due to the lack of the model support. https://github.com/opencv/opencv/issues/25314 + # Model( + # name='Colorization (caffemodel)', + # url=[ + # 'http://eecs.berkeley.edu/~rich.zhang/projects/2016_colorization/files/demo_v2/colorization_release_v2.caffemodel', + # 'https://dl.opencv.org/models/colorization_release_v2.caffemodel' + # ], + # sha='21e61293a3fa6747308171c11b6dd18a68a26e7f', + # filename='colorization_release_v2.caffemodel'), + # Disabled due to the lack of the model support. https://github.com/opencv/opencv/issues/25314 + # Model( + # name='Face_detector (FP16)', + # url='https://github.com/opencv/opencv_3rdparty/raw/19512576c112aa2c7b6328cb0e8d589a4a90a26d/res10_300x300_ssd_iter_140000_fp16.caffemodel', + # sha='31fc22bfdd907567a04bb45b7cfad29966caddc1', + # filename='opencv_face_detector_fp16.caffemodel'), Model( name='Face_detector (UINT8)', url='https://github.com/opencv/opencv_3rdparty/raw/8033c2bc31b3256f0d461c919ecc01c2428ca03b/opencv_face_detector_uint8.pb', @@ -386,54 +353,58 @@ def is_archive(self): sha='554a75594e9fd1ccee291b3ba3f1190b868a54c9', filename='ssd_inception_v2_coco_2017_11_17.pb') ]), - Model( - name='Faster-RCNN', # https://github.com/rbgirshick/py-faster-rcnn - url=[ - 'https://dl.dropboxusercontent.com/s/o6ii098bu51d139/faster_rcnn_models.tgz?dl=0', - 'https://dl.opencv.org/models/faster_rcnn_models.tgz' - ], - sha='51bca62727c3fe5d14b66e9331373c1e297df7d1', - filename='faster_rcnn_models.tgz', - sub=[ - Model( - member='faster_rcnn_models/VGG16_faster_rcnn_final.caffemodel', - sha='dd099979468aafba21f3952718a9ceffc7e57699', - filename='VGG16_faster_rcnn_final.caffemodel'), - Model( - member='faster_rcnn_models/ZF_faster_rcnn_final.caffemodel', - sha='7af886686f149622ed7a41c08b96743c9f4130f5', - filename='ZF_faster_rcnn_final.caffemodel'), - ]), - Model( - name='R-FCN', # https://github.com/YuwenXiong/py-R-FCN - url=[ - 'https://onedrive.live.com/download?cid=10B28C0E28BF7B83&resid=10B28C0E28BF7B83%215317&authkey=%21AIeljruhoLuail8', - 'https://dl.opencv.org/models/rfcn_models.tar.gz' - ], - sha='bb3180da68b2b71494f8d3eb8f51b2d47467da3e', - filename='rfcn_models.tar.gz', - sub=[ - Model( - member='rfcn_models/resnet50_rfcn_final.caffemodel', - sha='e00beca7af2790801efb1724d77bddba89e7081c', - filename='resnet50_rfcn_final.caffemodel'), - ]), - Model( - name='OpenPose/pose/coco', # https://github.com/CMU-Perceptual-Computing-Lab/openpose - url=[ - 'http://posefs1.perception.cs.cmu.edu/OpenPose/models/pose/coco/pose_iter_440000.caffemodel', - 'https://dl.opencv.org/models/openpose_pose_coco.caffemodel' - ], - sha='ac7e97da66f3ab8169af2e601384c144e23a95c1', - filename='openpose_pose_coco.caffemodel'), - Model( - name='OpenPose/pose/mpi', # https://github.com/CMU-Perceptual-Computing-Lab/openpose - url=[ - 'http://posefs1.perception.cs.cmu.edu/OpenPose/models/pose/mpi/pose_iter_160000.caffemodel', - 'https://dl.opencv.org/models/openpose_pose_mpi.caffemodel' - ], - sha='a344f4da6b52892e44a0ca8a4c68ee605fc611cf', - filename='openpose_pose_mpi.caffemodel'), + # Disabled due to the lack of the model support. https://github.com/opencv/opencv/issues/25314 + # Model( + # name='Faster-RCNN', # https://github.com/rbgirshick/py-faster-rcnn + # url=[ + # 'https://dl.dropboxusercontent.com/s/o6ii098bu51d139/faster_rcnn_models.tgz?dl=0', + # 'https://dl.opencv.org/models/faster_rcnn_models.tgz' + # ], + # sha='51bca62727c3fe5d14b66e9331373c1e297df7d1', + # filename='faster_rcnn_models.tgz', + # sub=[ + # Model( + # member='faster_rcnn_models/VGG16_faster_rcnn_final.caffemodel', + # sha='dd099979468aafba21f3952718a9ceffc7e57699', + # filename='VGG16_faster_rcnn_final.caffemodel'), + # Model( + # member='faster_rcnn_models/ZF_faster_rcnn_final.caffemodel', + # sha='7af886686f149622ed7a41c08b96743c9f4130f5', + # filename='ZF_faster_rcnn_final.caffemodel'), + # ]), + # Disabled due to the lack of the model support. https://github.com/opencv/opencv/issues/25314 + # Model( + # name='R-FCN', # https://github.com/YuwenXiong/py-R-FCN + # url=[ + # 'https://onedrive.live.com/download?cid=10B28C0E28BF7B83&resid=10B28C0E28BF7B83%215317&authkey=%21AIeljruhoLuail8', + # 'https://dl.opencv.org/models/rfcn_models.tar.gz' + # ], + # sha='bb3180da68b2b71494f8d3eb8f51b2d47467da3e', + # filename='rfcn_models.tar.gz', + # sub=[ + # Model( + # member='rfcn_models/resnet50_rfcn_final.caffemodel', + # sha='e00beca7af2790801efb1724d77bddba89e7081c', + # filename='resnet50_rfcn_final.caffemodel'), + # ]), + # Disabled due to the lack of the model support. https://github.com/opencv/opencv/issues/25314 + # Model( + # name='OpenPose/pose/coco', # https://github.com/CMU-Perceptual-Computing-Lab/openpose + # url=[ + # 'http://posefs1.perception.cs.cmu.edu/OpenPose/models/pose/coco/pose_iter_440000.caffemodel', + # 'https://dl.opencv.org/models/openpose_pose_coco.caffemodel' + # ], + # sha='ac7e97da66f3ab8169af2e601384c144e23a95c1', + # filename='openpose_pose_coco.caffemodel'), + # Disabled due to the lack of the model support. https://github.com/opencv/opencv/issues/25314 + # Model( + # name='OpenPose/pose/mpi', # https://github.com/CMU-Perceptual-Computing-Lab/openpose + # url=[ + # 'http://posefs1.perception.cs.cmu.edu/OpenPose/models/pose/mpi/pose_iter_160000.caffemodel', + # 'https://dl.opencv.org/models/openpose_pose_mpi.caffemodel' + # ], + # sha='a344f4da6b52892e44a0ca8a4c68ee605fc611cf', + # filename='openpose_pose_mpi.caffemodel'), Model( name='YOLOv3', # https://pjreddie.com/darknet/yolo/ url='https://pjreddie.com/media/files/yolov3.weights', @@ -885,14 +856,6 @@ def is_archive(self): url='https://github.com/AlexeyAB/darknet/releases/download/darknet_yolo_v4_pre/yolov4x-mish.weights', sha='a6f2879af2241de2e9730d317a55db6afd0af00b', filename='yolov4x-mish.weights'), - Model( - name='GSOC2016-GOTURN', # https://github.com/opencv/opencv_contrib/issues/941 - url=[ - 'https://docs.google.com/uc?export=download&id=1j4UTqVE4EGaUFiK7a5I_CYX7twO9c5br', - 'https://dl.opencv.org/models/goturn.caffemodel' - ], - sha='49776d262993c387542f84d9cd16566840404f26', - filename='gsoc2016-goturn/goturn.caffemodel'), Model( name='DaSiamRPM Tracker network (ONNX)', url='https://www.dropbox.com/s/rr1lk9355vzolqv/dasiamrpn_model.onnx?dl=1', @@ -947,21 +910,24 @@ def is_archive(self): url='https://raw.githubusercontent.com/WeChatCV/opencv_3rdparty/wechat_qrcode/detect.prototxt', sha='a6936962139282d300ebbf15a54c2aa94b144bb7', filename='wechat_2021-01/detect.prototxt'), - Model( - name='wechat_qr_detect (caffemodel)', - url='https://raw.githubusercontent.com/WeChatCV/opencv_3rdparty/wechat_qrcode/detect.caffemodel', - sha='d587623a055cbd58a648de62a8c703c7abb05f6d', - filename='wechat_2021-01/detect.caffemodel'), - Model( - name='wechat_super_resolution (prototxt)', - url='https://raw.githubusercontent.com/WeChatCV/opencv_3rdparty/wechat_qrcode/sr.prototxt', - sha='39e1f1031c842766f1cc126615fea8e8256facd2', - filename='wechat_2021-01/sr.prototxt'), - Model( - name='wechat_super_resolution (caffemodel)', - url='https://raw.githubusercontent.com/WeChatCV/opencv_3rdparty/wechat_qrcode/sr.caffemodel', - sha='2b181b55d1d7af718eaca6cabdeb741217b64c73', - filename='wechat_2021-01/sr.caffemodel'), + # Disabled due to the lack of the model support. https://github.com/opencv/opencv/issues/25314 + # Model( + # name='wechat_qr_detect (caffemodel)', + # url='https://raw.githubusercontent.com/WeChatCV/opencv_3rdparty/wechat_qrcode/detect.caffemodel', + # sha='d587623a055cbd58a648de62a8c703c7abb05f6d', + # filename='wechat_2021-01/detect.caffemodel'), + # Disabled due to the lack of the model support. https://github.com/opencv/opencv/issues/25314 + # Model( + # name='wechat_super_resolution (prototxt)', + # url='https://raw.githubusercontent.com/WeChatCV/opencv_3rdparty/wechat_qrcode/sr.prototxt', + # sha='39e1f1031c842766f1cc126615fea8e8256facd2', + # filename='wechat_2021-01/sr.prototxt'), + # Disabled due to the lack of the model support. https://github.com/opencv/opencv/issues/25314 + # Model( + # name='wechat_super_resolution (caffemodel)', + # url='https://raw.githubusercontent.com/WeChatCV/opencv_3rdparty/wechat_qrcode/sr.caffemodel', + # sha='2b181b55d1d7af718eaca6cabdeb741217b64c73', + # filename='wechat_2021-01/sr.caffemodel'), Model( name='yolov7', url=[ diff --git a/testdata/dnn/faster_rcnn_vgg16.prototxt b/testdata/dnn/faster_rcnn_vgg16.prototxt deleted file mode 100644 index 3508fe3c0..000000000 --- a/testdata/dnn/faster_rcnn_vgg16.prototxt +++ /dev/null @@ -1,520 +0,0 @@ -# Faster-RCNN network. Based on https://github.com/rbgirshick/py-faster-rcnn/blob/master/models/pascal_voc/VGG16/faster_rcnn_alt_opt/faster_rcnn_test.pt -name: "VGG_ILSVRC_16_layers" - -input: "data" -input_shape { - dim: 1 - dim: 3 - dim: 224 - dim: 224 -} - -input: "im_info" -input_shape { - dim: 1 - dim: 3 -} - -layer { - name: "conv1_1" - type: "Convolution" - bottom: "data" - top: "conv1_1" - convolution_param { - num_output: 64 - pad: 1 kernel_size: 3 - } -} -layer { - name: "relu1_1" - type: "ReLU" - bottom: "conv1_1" - top: "conv1_1" -} -layer { - name: "conv1_2" - type: "Convolution" - bottom: "conv1_1" - top: "conv1_2" - convolution_param { - num_output: 64 - pad: 1 kernel_size: 3 - } -} -layer { - name: "relu1_2" - type: "ReLU" - bottom: "conv1_2" - top: "conv1_2" -} -layer { - name: "pool1" - type: "Pooling" - bottom: "conv1_2" - top: "pool1" - pooling_param { - pool: MAX - kernel_size: 2 stride: 2 - } -} -layer { - name: "conv2_1" - type: "Convolution" - bottom: "pool1" - top: "conv2_1" - convolution_param { - num_output: 128 - pad: 1 kernel_size: 3 - } -} -layer { - name: "relu2_1" - type: "ReLU" - bottom: "conv2_1" - top: "conv2_1" -} -layer { - name: "conv2_2" - type: "Convolution" - bottom: "conv2_1" - top: "conv2_2" - convolution_param { - num_output: 128 - pad: 1 kernel_size: 3 - } -} -layer { - name: "relu2_2" - type: "ReLU" - bottom: "conv2_2" - top: "conv2_2" -} -layer { - name: "pool2" - type: "Pooling" - bottom: "conv2_2" - top: "pool2" - pooling_param { - pool: MAX - kernel_size: 2 stride: 2 - } -} -layer { - name: "conv3_1" - type: "Convolution" - bottom: "pool2" - top: "conv3_1" - convolution_param { - num_output: 256 - pad: 1 kernel_size: 3 - } -} -layer { - name: "relu3_1" - type: "ReLU" - bottom: "conv3_1" - top: "conv3_1" -} -layer { - name: "conv3_2" - type: "Convolution" - bottom: "conv3_1" - top: "conv3_2" - convolution_param { - num_output: 256 - pad: 1 kernel_size: 3 - } -} -layer { - name: "relu3_2" - type: "ReLU" - bottom: "conv3_2" - top: "conv3_2" -} -layer { - name: "conv3_3" - type: "Convolution" - bottom: "conv3_2" - top: "conv3_3" - convolution_param { - num_output: 256 - pad: 1 kernel_size: 3 - } -} -layer { - name: "relu3_3" - type: "ReLU" - bottom: "conv3_3" - top: "conv3_3" -} -layer { - name: "pool3" - type: "Pooling" - bottom: "conv3_3" - top: "pool3" - pooling_param { - pool: MAX - kernel_size: 2 stride: 2 - } -} -layer { - name: "conv4_1" - type: "Convolution" - bottom: "pool3" - top: "conv4_1" - convolution_param { - num_output: 512 - pad: 1 kernel_size: 3 - } -} -layer { - name: "relu4_1" - type: "ReLU" - bottom: "conv4_1" - top: "conv4_1" -} -layer { - name: "conv4_2" - type: "Convolution" - bottom: "conv4_1" - top: "conv4_2" - convolution_param { - num_output: 512 - pad: 1 kernel_size: 3 - } -} -layer { - name: "relu4_2" - type: "ReLU" - bottom: "conv4_2" - top: "conv4_2" -} -layer { - name: "conv4_3" - type: "Convolution" - bottom: "conv4_2" - top: "conv4_3" - convolution_param { - num_output: 512 - pad: 1 kernel_size: 3 - } -} -layer { - name: "relu4_3" - type: "ReLU" - bottom: "conv4_3" - top: "conv4_3" -} -layer { - name: "pool4" - type: "Pooling" - bottom: "conv4_3" - top: "pool4" - pooling_param { - pool: MAX - kernel_size: 2 stride: 2 - } -} -layer { - name: "conv5_1" - type: "Convolution" - bottom: "pool4" - top: "conv5_1" - convolution_param { - num_output: 512 - pad: 1 kernel_size: 3 - } -} -layer { - name: "relu5_1" - type: "ReLU" - bottom: "conv5_1" - top: "conv5_1" -} -layer { - name: "conv5_2" - type: "Convolution" - bottom: "conv5_1" - top: "conv5_2" - convolution_param { - num_output: 512 - pad: 1 kernel_size: 3 - } -} -layer { - name: "relu5_2" - type: "ReLU" - bottom: "conv5_2" - top: "conv5_2" -} -layer { - name: "conv5_3" - type: "Convolution" - bottom: "conv5_2" - top: "conv5_3" - convolution_param { - num_output: 512 - pad: 1 kernel_size: 3 - } -} -layer { - name: "relu5_3" - type: "ReLU" - bottom: "conv5_3" - top: "conv5_3" -} - -#========= RPN ============ - -layer { - name: "rpn_conv/3x3" - type: "Convolution" - bottom: "conv5_3" - top: "rpn/output" - convolution_param { - num_output: 512 - kernel_size: 3 pad: 1 stride: 1 - } -} -layer { - name: "rpn_relu/3x3" - type: "ReLU" - bottom: "rpn/output" - top: "rpn/output" -} - -layer { - name: "rpn_cls_score" - type: "Convolution" - bottom: "rpn/output" - top: "rpn_cls_score" - convolution_param { - num_output: 18 # 2(bg/fg) * 9(anchors) - kernel_size: 1 pad: 0 stride: 1 - } -} -layer { - name: "rpn_bbox_pred" - type: "Convolution" - bottom: "rpn/output" - top: "rpn_bbox_pred" - convolution_param { - num_output: 36 # 4 * 9(anchors) - kernel_size: 1 pad: 0 stride: 1 - } -} -layer { - bottom: "rpn_cls_score" - top: "rpn_cls_score_reshape" - name: "rpn_cls_score_reshape" - type: "Reshape" - reshape_param { shape { dim: 0 dim: 2 dim: -1 dim: 0 } } -} - -#========= RoI Proposal ============ - -layer { - name: "rpn_cls_prob" - type: "Softmax" - bottom: "rpn_cls_score_reshape" - top: "rpn_cls_prob" -} -layer { - name: 'rpn_cls_prob_reshape' - type: 'Reshape' - bottom: 'rpn_cls_prob' - top: 'rpn_cls_prob_reshape' - reshape_param { shape { dim: 0 dim: 18 dim: -1 dim: 0 } } -} -# layer { -# name: 'proposal' -# type: 'Python' -# bottom: 'rpn_cls_prob_reshape' -# bottom: 'rpn_bbox_pred' -# bottom: 'im_info' -# top: 'rois' -# python_param { -# module: 'rpn.proposal_layer' -# layer: 'ProposalLayer' -# param_str: "'feat_stride': 16" -# } -# } -layer { - name: 'proposal' - type: 'Proposal' - bottom: 'rpn_cls_prob_reshape' - bottom: 'rpn_bbox_pred' - bottom: 'im_info' - top: 'rois' - proposal_param { - ratio: 0.5 - ratio: 1.0 - ratio: 2.0 - scale: 8 - scale: 16 - scale: 32 - } -} - -#========= RCNN ============ - -layer { - name: "roi_pool5" - type: "ROIPooling" - bottom: "conv5_3" - bottom: "rois" - top: "pool5" - roi_pooling_param { - pooled_w: 7 - pooled_h: 7 - spatial_scale: 0.0625 # 1/16 - } -} -layer { - name: "fc6" - type: "InnerProduct" - bottom: "pool5" - top: "fc6" - inner_product_param { - num_output: 4096 - } -} -layer { - name: "relu6" - type: "ReLU" - bottom: "fc6" - top: "fc6" -} -layer { - name: "fc7" - type: "InnerProduct" - bottom: "fc6" - top: "fc7" - inner_product_param { - num_output: 4096 - } -} -layer { - name: "relu7" - type: "ReLU" - bottom: "fc7" - top: "fc7" -} -layer { - name: "cls_score" - type: "InnerProduct" - bottom: "fc7" - top: "cls_score" - inner_product_param { - num_output: 21 - } -} -layer { - name: "bbox_pred" - type: "InnerProduct" - bottom: "fc7" - top: "bbox_pred" - inner_product_param { - num_output: 84 - } -} -layer { - name: "cls_prob" - type: "Softmax" - bottom: "cls_score" - top: "cls_prob" -} - -# ======== Postprocessing ========== -# cls_prob has a shape [numPriors x 21]. Flatten it to [1 x numPriors*21]. -layer { - name: "cls_prob_reshape" - type: "Reshape" - bottom: "cls_prob" - top: "cls_prob_reshape" - reshape_param { - shape { - dim: 1 - dim: -1 - } - } -} -# Reshape bounding boxes from [numPriors x 84] to [1 x numPriors*21 x 4 x 1]. -layer { - name: "bbox_pred_reshape" - type: "Reshape" - bottom: "bbox_pred" - top: "bbox_pred_reshape" - reshape_param { - shape { - dim: 1 - dim: -1 - dim: 4 - dim: 1 - } - } -} -# Reshape proposals to [1 x numPriors x 5 x 1]. -layer { - name: "rois_reshape" - type: "Reshape" - bottom: "rois" - top: "rois_reshape" - reshape_param { - shape { - dim: 1 - dim: -1 - dim: 5 - dim: 1 - } - } -} -# Proposal layer generates [numPriors x 5] blob where 0th column are batch indices -# and only the rest are bounding boxes. -layer { - name: "proposal_bboxes" - type: "Crop" - bottom: "rois_reshape" - bottom: "bbox_pred_reshape" - top: "proposal_bboxes" - crop_param { - axis: 2 - offset: 1 # An offset at [batch x left x top x right x bottom data] - offset: 0 - } -} -# Reshape it to [1 x 1 x numPriors*4 x 1] -layer { - name: "proposal_reshape" - type: "Reshape" - bottom: "proposal_bboxes" - top: "proposal_reshape" - reshape_param { - shape { - dim: 1 - dim: 1 - dim: -1 - dim: 1 # Reshape to 4d to enable clDNN from Intel's Inference Engine - } - } -} -layer { - name: "detection_out" - type: "DetectionOutput" - bottom: "bbox_pred_reshape" - bottom: "cls_prob_reshape" - bottom: "proposal_reshape" - top: "detection_out" - detection_output_param { - num_classes: 21 - share_location: false - background_label_id: 0 - nms_param { - nms_threshold: 0.3 - } - code_type: CENTER_SIZE - keep_top_k: 100 - variance_encoded_in_target: true - normalized_bbox: false - } -} diff --git a/testdata/dnn/faster_rcnn_zf.prototxt b/testdata/dnn/faster_rcnn_zf.prototxt deleted file mode 100644 index a2ffdde6b..000000000 --- a/testdata/dnn/faster_rcnn_zf.prototxt +++ /dev/null @@ -1,438 +0,0 @@ -# Faster-RCNN network. Based on https://github.com/rbgirshick/py-faster-rcnn/blob/master/models/pascal_voc/ZF/faster_rcnn_alt_opt/faster_rcnn_test.pt -name: "ZF" - -input: "data" -input_shape { - dim: 1 - dim: 3 - dim: 224 - dim: 224 -} - -input: "im_info" -input_shape { - dim: 1 - dim: 3 -} - -#========= conv1-conv5 ============ - -layer { - name: "conv1" - type: "Convolution" - bottom: "data" - top: "conv1" - convolution_param { - num_output: 96 - kernel_size: 7 - pad: 3 - stride: 2 - } -} -layer { - name: "relu1" - type: "ReLU" - bottom: "conv1" - top: "conv1" -} -layer { - name: "norm1" - type: "LRN" - bottom: "conv1" - top: "norm1" - lrn_param { - local_size: 3 - alpha: 0.00005 - beta: 0.75 - norm_region: WITHIN_CHANNEL - engine: CAFFE - } -} -layer { - name: "pool1" - type: "Pooling" - bottom: "norm1" - top: "pool1" - pooling_param { - kernel_size: 3 - stride: 2 - pad: 1 - pool: MAX - } -} -layer { - name: "conv2" - type: "Convolution" - bottom: "pool1" - top: "conv2" - convolution_param { - num_output: 256 - kernel_size: 5 - pad: 2 - stride: 2 - } -} -layer { - name: "relu2" - type: "ReLU" - bottom: "conv2" - top: "conv2" -} -layer { - name: "norm2" - type: "LRN" - bottom: "conv2" - top: "norm2" - lrn_param { - local_size: 3 - alpha: 0.00005 - beta: 0.75 - norm_region: WITHIN_CHANNEL - engine: CAFFE - } -} -layer { - name: "pool2" - type: "Pooling" - bottom: "norm2" - top: "pool2" - pooling_param { - kernel_size: 3 - stride: 2 - pad: 1 - pool: MAX - } -} -layer { - name: "conv3" - type: "Convolution" - bottom: "pool2" - top: "conv3" - convolution_param { - num_output: 384 - kernel_size: 3 - pad: 1 - stride: 1 - } -} -layer { - name: "relu3" - type: "ReLU" - bottom: "conv3" - top: "conv3" -} -layer { - name: "conv4" - type: "Convolution" - bottom: "conv3" - top: "conv4" - convolution_param { - num_output: 384 - kernel_size: 3 - pad: 1 - stride: 1 - } -} -layer { - name: "relu4" - type: "ReLU" - bottom: "conv4" - top: "conv4" -} -layer { - name: "conv5" - type: "Convolution" - bottom: "conv4" - top: "conv5" - convolution_param { - num_output: 256 - kernel_size: 3 - pad: 1 - stride: 1 - } -} -layer { - name: "relu5" - type: "ReLU" - bottom: "conv5" - top: "conv5" -} - -#========= RPN ============ - - -layer { - name: "rpn_conv1" - type: "Convolution" - bottom: "conv5" - top: "rpn_conv1" - convolution_param { - num_output: 256 - kernel_size: 3 pad: 1 stride: 1 - } -} -layer { - name: "rpn_relu1" - type: "ReLU" - bottom: "rpn_conv1" - top: "rpn_conv1" -} -layer { - name: "rpn_cls_score" - type: "Convolution" - bottom: "rpn_conv1" - top: "rpn_cls_score" - convolution_param { - num_output: 18 # 2(bg/fg) * 9(anchors) - kernel_size: 1 pad: 0 stride: 1 - } -} -layer { - name: "rpn_bbox_pred" - type: "Convolution" - bottom: "rpn_conv1" - top: "rpn_bbox_pred" - convolution_param { - num_output: 36 # 4 * 9(anchors) - kernel_size: 1 pad: 0 stride: 1 - } -} -layer { - bottom: "rpn_cls_score" - top: "rpn_cls_score_reshape" - name: "rpn_cls_score_reshape" - type: "Reshape" - reshape_param { shape { dim: 0 dim: 2 dim: -1 dim: 0 } } -} - -#========= RoI Proposal ============ - -layer { - name: "rpn_cls_prob" - type: "Softmax" - bottom: "rpn_cls_score_reshape" - top: "rpn_cls_prob" -} -layer { - name: 'rpn_cls_prob_reshape' - type: 'Reshape' - bottom: 'rpn_cls_prob' - top: 'rpn_cls_prob_reshape' - reshape_param { shape { dim: 0 dim: 18 dim: -1 dim: 0 } } -} -# layer { -# name: 'proposal' -# type: 'Python' -# bottom: 'rpn_cls_prob_reshape' -# bottom: 'rpn_bbox_pred' -# bottom: 'im_info' -# top: 'rois' -# python_param { -# module: 'rpn.proposal_layer' -# layer: 'ProposalLayer' -# param_str: "'feat_stride': 16" -# } -# } -layer { - name: 'proposal' - type: 'Proposal' - bottom: 'rpn_cls_prob_reshape' - bottom: 'rpn_bbox_pred' - bottom: 'im_info' - top: 'rois' - proposal_param { - ratio: 0.5 - ratio: 1.0 - ratio: 2.0 - scale: 8 - scale: 16 - scale: 32 - } -} - -#========= RCNN ============ - -layer { - name: "roi_pool_conv5" - type: "ROIPooling" - bottom: "conv5" - bottom: "rois" - top: "roi_pool_conv5" - roi_pooling_param { - pooled_w: 6 - pooled_h: 6 - spatial_scale: 0.0625 # 1/16 - } -} -layer { - name: "fc6" - type: "InnerProduct" - bottom: "roi_pool_conv5" - top: "fc6" - inner_product_param { - num_output: 4096 - } -} -layer { - name: "relu6" - type: "ReLU" - bottom: "fc6" - top: "fc6" -} -layer { - name: "drop6" - type: "Dropout" - bottom: "fc6" - top: "fc6" - dropout_param { - dropout_ratio: 0.5 - scale_train: false - } -} -layer { - name: "fc7" - type: "InnerProduct" - bottom: "fc6" - top: "fc7" - inner_product_param { - num_output: 4096 - } -} -layer { - name: "relu7" - type: "ReLU" - bottom: "fc7" - top: "fc7" -} -layer { - name: "drop7" - type: "Dropout" - bottom: "fc7" - top: "fc7" - dropout_param { - dropout_ratio: 0.5 - scale_train: false - } -} -layer { - name: "cls_score" - type: "InnerProduct" - bottom: "fc7" - top: "cls_score" - inner_product_param { - num_output: 21 - } -} -layer { - name: "bbox_pred" - type: "InnerProduct" - bottom: "fc7" - top: "bbox_pred" - inner_product_param { - num_output: 84 - } -} -layer { - name: "cls_prob" - type: "Softmax" - bottom: "cls_score" - top: "cls_prob" - loss_param { - ignore_label: -1 - normalize: true - } -} - -# ======== Postprocessing ========== -# cls_prob has a shape [numPriors x 21]. Flatten it to [1 x numPriors*21]. -layer { - name: "cls_prob_reshape" - type: "Reshape" - bottom: "cls_prob" - top: "cls_prob_reshape" - reshape_param { - shape { - dim: 1 - dim: -1 - } - } -} -# Reshape bounding boxes from [numPriors x 84] to [1 x numPriors*21 x 4 x 1]. -layer { - name: "bbox_pred_reshape" - type: "Reshape" - bottom: "bbox_pred" - top: "bbox_pred_reshape" - reshape_param { - shape { - dim: 1 - dim: -1 - dim: 4 - dim: 1 - } - } -} -# Reshape proposals to [1 x numPriors x 5 x 1]. -layer { - name: "rois_reshape" - type: "Reshape" - bottom: "rois" - top: "rois_reshape" - reshape_param { - shape { - dim: 1 - dim: -1 - dim: 5 - dim: 1 - } - } -} -# Proposal layer generates [numPriors x 5] blob where 0th column are batch indices -# and only the rest are bounding boxes. -layer { - name: "proposal_bboxes" - type: "Crop" - bottom: "rois_reshape" - bottom: "bbox_pred_reshape" - top: "proposal_bboxes" - crop_param { - axis: 2 - offset: 1 # An offset at [batch x left x top x right x bottom data] - offset: 0 - } -} -# Reshape it to [1 x 1 x numPriors*4] -layer { - name: "proposal_reshape" - type: "Reshape" - bottom: "proposal_bboxes" - top: "proposal_reshape" - reshape_param { - shape { - dim: 1 - dim: 1 - dim: -1 - dim: 1 # Reshape to 4d to enable clDNN from Intel's Inference Engine - } - } -} -layer { - name: "detection_out" - type: "DetectionOutput" - bottom: "bbox_pred_reshape" - bottom: "cls_prob_reshape" - bottom: "proposal_reshape" - top: "detection_out" - detection_output_param { - num_classes: 21 - share_location: false - background_label_id: 0 - nms_param { - nms_threshold: 0.3 - } - code_type: CENTER_SIZE - keep_top_k: 100 - variance_encoded_in_target: true - normalized_bbox: false - } -} diff --git a/testdata/dnn/fcn8s-heavy-pascal.prototxt b/testdata/dnn/fcn8s-heavy-pascal.prototxt deleted file mode 100644 index 426b40f81..000000000 --- a/testdata/dnn/fcn8s-heavy-pascal.prototxt +++ /dev/null @@ -1,612 +0,0 @@ -# -# This prototxt is based on voc-fcn8s/val.prototxt file from -# https://github.com/shelhamer/fcn.berkeleyvision.org, which is distributed under -# Caffe (BSD) license: -# http://caffe.berkeleyvision.org/model_zoo.html#bvlc-model-license -# -name: "voc-fcn8s" -input: "data" -input_dim: 1 -input_dim: 3 -input_dim: 500 -input_dim: 500 -layer { - name: "conv1_1" - type: "Convolution" - bottom: "data" - top: "conv1_1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - pad: 100 - kernel_size: 3 - stride: 1 - } -} -layer { - name: "relu1_1" - type: "ReLU" - bottom: "conv1_1" - top: "conv1_1" -} -layer { - name: "conv1_2" - type: "Convolution" - bottom: "conv1_1" - top: "conv1_2" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - pad: 1 - kernel_size: 3 - stride: 1 - } -} -layer { - name: "relu1_2" - type: "ReLU" - bottom: "conv1_2" - top: "conv1_2" -} -layer { - name: "pool1" - type: "Pooling" - bottom: "conv1_2" - top: "pool1" - pooling_param { - pool: MAX - kernel_size: 2 - stride: 2 - } -} -layer { - name: "conv2_1" - type: "Convolution" - bottom: "pool1" - top: "conv2_1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - stride: 1 - } -} -layer { - name: "relu2_1" - type: "ReLU" - bottom: "conv2_1" - top: "conv2_1" -} -layer { - name: "conv2_2" - type: "Convolution" - bottom: "conv2_1" - top: "conv2_2" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - stride: 1 - } -} -layer { - name: "relu2_2" - type: "ReLU" - bottom: "conv2_2" - top: "conv2_2" -} -layer { - name: "pool2" - type: "Pooling" - bottom: "conv2_2" - top: "pool2" - pooling_param { - pool: MAX - kernel_size: 2 - stride: 2 - } -} -layer { - name: "conv3_1" - type: "Convolution" - bottom: "pool2" - top: "conv3_1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - stride: 1 - } -} -layer { - name: "relu3_1" - type: "ReLU" - bottom: "conv3_1" - top: "conv3_1" -} -layer { - name: "conv3_2" - type: "Convolution" - bottom: "conv3_1" - top: "conv3_2" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - stride: 1 - } -} -layer { - name: "relu3_2" - type: "ReLU" - bottom: "conv3_2" - top: "conv3_2" -} -layer { - name: "conv3_3" - type: "Convolution" - bottom: "conv3_2" - top: "conv3_3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - stride: 1 - } -} -layer { - name: "relu3_3" - type: "ReLU" - bottom: "conv3_3" - top: "conv3_3" -} -layer { - name: "pool3" - type: "Pooling" - bottom: "conv3_3" - top: "pool3" - pooling_param { - pool: MAX - kernel_size: 2 - stride: 2 - } -} -layer { - name: "conv4_1" - type: "Convolution" - bottom: "pool3" - top: "conv4_1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 512 - pad: 1 - kernel_size: 3 - stride: 1 - } -} -layer { - name: "relu4_1" - type: "ReLU" - bottom: "conv4_1" - top: "conv4_1" -} -layer { - name: "conv4_2" - type: "Convolution" - bottom: "conv4_1" - top: "conv4_2" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 512 - pad: 1 - kernel_size: 3 - stride: 1 - } -} -layer { - name: "relu4_2" - type: "ReLU" - bottom: "conv4_2" - top: "conv4_2" -} -layer { - name: "conv4_3" - type: "Convolution" - bottom: "conv4_2" - top: "conv4_3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 512 - pad: 1 - kernel_size: 3 - stride: 1 - } -} -layer { - name: "relu4_3" - type: "ReLU" - bottom: "conv4_3" - top: "conv4_3" -} -layer { - name: "pool4" - type: "Pooling" - bottom: "conv4_3" - top: "pool4" - pooling_param { - pool: MAX - kernel_size: 2 - stride: 2 - } -} -layer { - name: "conv5_1" - type: "Convolution" - bottom: "pool4" - top: "conv5_1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 512 - pad: 1 - kernel_size: 3 - stride: 1 - } -} -layer { - name: "relu5_1" - type: "ReLU" - bottom: "conv5_1" - top: "conv5_1" -} -layer { - name: "conv5_2" - type: "Convolution" - bottom: "conv5_1" - top: "conv5_2" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 512 - pad: 1 - kernel_size: 3 - stride: 1 - } -} -layer { - name: "relu5_2" - type: "ReLU" - bottom: "conv5_2" - top: "conv5_2" -} -layer { - name: "conv5_3" - type: "Convolution" - bottom: "conv5_2" - top: "conv5_3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 512 - pad: 1 - kernel_size: 3 - stride: 1 - } -} -layer { - name: "relu5_3" - type: "ReLU" - bottom: "conv5_3" - top: "conv5_3" -} -layer { - name: "pool5" - type: "Pooling" - bottom: "conv5_3" - top: "pool5" - pooling_param { - pool: MAX - kernel_size: 2 - stride: 2 - } -} -layer { - name: "fc6" - type: "Convolution" - bottom: "pool5" - top: "fc6" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 4096 - pad: 0 - kernel_size: 7 - stride: 1 - } -} -layer { - name: "relu6" - type: "ReLU" - bottom: "fc6" - top: "fc6" -} -layer { - name: "fc7" - type: "Convolution" - bottom: "fc6" - top: "fc7" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 4096 - pad: 0 - kernel_size: 1 - stride: 1 - } -} -layer { - name: "relu7" - type: "ReLU" - bottom: "fc7" - top: "fc7" -} -layer { - name: "score_fr" - type: "Convolution" - bottom: "fc7" - top: "score_fr" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 21 - pad: 0 - kernel_size: 1 - } -} -layer { - name: "upscore2" - type: "Deconvolution" - bottom: "score_fr" - top: "upscore2" - param { - lr_mult: 0 - } - convolution_param { - num_output: 21 - bias_term: false - kernel_size: 4 - stride: 2 - } -} -layer { - name: "score_pool4" - type: "Convolution" - bottom: "pool4" - top: "score_pool4" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 21 - pad: 0 - kernel_size: 1 - } -} -layer { - name: "score_pool4c" - type: "Crop" - bottom: "score_pool4" - bottom: "upscore2" - top: "score_pool4c" - crop_param { - axis: 2 - offset: 5 - } -} -layer { - name: "fuse_pool4" - type: "Eltwise" - bottom: "upscore2" - bottom: "score_pool4c" - top: "fuse_pool4" - eltwise_param { - operation: SUM - } -} -layer { - name: "upscore_pool4" - type: "Deconvolution" - bottom: "fuse_pool4" - top: "upscore_pool4" - param { - lr_mult: 0 - } - convolution_param { - num_output: 21 - bias_term: false - kernel_size: 4 - stride: 2 - } -} -layer { - name: "score_pool3" - type: "Convolution" - bottom: "pool3" - top: "score_pool3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 21 - pad: 0 - kernel_size: 1 - } -} -layer { - name: "score_pool3c" - type: "Crop" - bottom: "score_pool3" - bottom: "upscore_pool4" - top: "score_pool3c" - crop_param { - axis: 2 - offset: 9 - } -} -layer { - name: "fuse_pool3" - type: "Eltwise" - bottom: "upscore_pool4" - bottom: "score_pool3c" - top: "fuse_pool3" - eltwise_param { - operation: SUM - } -} -layer { - name: "upscore8" - type: "Deconvolution" - bottom: "fuse_pool3" - top: "upscore8" - param { - lr_mult: 0 - } - convolution_param { - num_output: 21 - bias_term: false - kernel_size: 16 - stride: 8 - } -} -layer { - name: "score" - type: "Crop" - bottom: "upscore8" - bottom: "data" - top: "score" - crop_param { - axis: 2 - offset: 31 - } -} diff --git a/testdata/dnn/googlenet_conv1#7x7_s2.npy b/testdata/dnn/googlenet_conv1#7x7_s2_1.npy similarity index 100% rename from testdata/dnn/googlenet_conv1#7x7_s2.npy rename to testdata/dnn/googlenet_conv1#7x7_s2_1.npy diff --git a/testdata/dnn/googlenet_conv1#relu_7x7.npy b/testdata/dnn/googlenet_conv1#7x7_s2_2.npy similarity index 100% rename from testdata/dnn/googlenet_conv1#relu_7x7.npy rename to testdata/dnn/googlenet_conv1#7x7_s2_2.npy diff --git a/testdata/dnn/googlenet_inception_4c#1x1.npy b/testdata/dnn/googlenet_inception_4c#1x1_1.npy similarity index 100% rename from testdata/dnn/googlenet_inception_4c#1x1.npy rename to testdata/dnn/googlenet_inception_4c#1x1_1.npy diff --git a/testdata/dnn/googlenet_inception_4c#relu_1x1.npy b/testdata/dnn/googlenet_inception_4c#1x1_2.npy similarity index 100% rename from testdata/dnn/googlenet_inception_4c#relu_1x1.npy rename to testdata/dnn/googlenet_inception_4c#1x1_2.npy diff --git a/testdata/dnn/gsoc2016-goturn/README.md b/testdata/dnn/gsoc2016-goturn/README.md deleted file mode 100644 index 2fa3bc6a7..000000000 --- a/testdata/dnn/gsoc2016-goturn/README.md +++ /dev/null @@ -1,2 +0,0 @@ -Original: https://github.com/opencv/opencv_extra/tree/c4219d5eb3105ed8e634278fad312a1a8d2c182d/testdata/tracking -Result of GSoC 2016 project diff --git a/testdata/dnn/gsoc2016-goturn/goturn.prototxt b/testdata/dnn/gsoc2016-goturn/goturn.prototxt deleted file mode 100644 index 6dbb1f427..000000000 --- a/testdata/dnn/gsoc2016-goturn/goturn.prototxt +++ /dev/null @@ -1,587 +0,0 @@ -name: "GOTURN" - -input: "data1" -input_dim: 1 -input_dim: 3 -input_dim: 227 -input_dim: 227 - -input: "data2" -input_dim: 1 -input_dim: 3 -input_dim: 227 -input_dim: 227 - -layer { - name: "conv11" - type: "Convolution" - bottom: "data1" - top: "conv11" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 96 - kernel_size: 11 - stride: 4 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "relu11" - type: "ReLU" - bottom: "conv11" - top: "conv11" -} -layer { - name: "pool11" - type: "Pooling" - bottom: "conv11" - top: "pool11" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 2 - } -} -layer { - name: "norm11" - type: "LRN" - bottom: "pool11" - top: "norm11" - lrn_param { - local_size: 5 - alpha: 0.0001 - beta: 0.75 - } -} -layer { - name: "conv12" - type: "Convolution" - bottom: "norm11" - top: "conv12" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 2 - kernel_size: 5 - group: 2 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - value: 1 - } - } -} -layer { - name: "relu12" - type: "ReLU" - bottom: "conv12" - top: "conv12" -} -layer { - name: "pool12" - type: "Pooling" - bottom: "conv12" - top: "pool12" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 2 - } -} -layer { - name: "norm12" - type: "LRN" - bottom: "pool12" - top: "norm12" - lrn_param { - local_size: 5 - alpha: 0.0001 - beta: 0.75 - } -} -layer { - name: "conv13" - type: "Convolution" - bottom: "norm12" - top: "conv13" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 384 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "relu13" - type: "ReLU" - bottom: "conv13" - top: "conv13" -} -layer { - name: "conv14" - type: "Convolution" - bottom: "conv13" - top: "conv14" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 384 - pad: 1 - kernel_size: 3 - group: 2 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - value: 1 - } - } -} -layer { - name: "relu14" - type: "ReLU" - bottom: "conv14" - top: "conv14" -} -layer { - name: "conv15" - type: "Convolution" - bottom: "conv14" - top: "conv15" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - group: 2 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - value: 1 - } - } -} -layer { - name: "relu15" - type: "ReLU" - bottom: "conv15" - top: "conv15" -} -layer { - name: "pool15" - type: "Pooling" - bottom: "conv15" - top: "pool15" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 2 - } -} - - -layer { - name: "conv21" - type: "Convolution" - bottom: "data2" - top: "conv21" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 96 - kernel_size: 11 - stride: 4 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "relu21" - type: "ReLU" - bottom: "conv21" - top: "conv21" -} -layer { - name: "pool21" - type: "Pooling" - bottom: "conv21" - top: "pool21" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 2 - } -} -layer { - name: "norm21" - type: "LRN" - bottom: "pool21" - top: "norm21" - lrn_param { - local_size: 5 - alpha: 0.0001 - beta: 0.75 - } -} -layer { - name: "conv22" - type: "Convolution" - bottom: "norm21" - top: "conv22" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 2 - kernel_size: 5 - group: 2 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - value: 1 - } - } -} -layer { - name: "relu22" - type: "ReLU" - bottom: "conv22" - top: "conv22" -} -layer { - name: "pool22" - type: "Pooling" - bottom: "conv22" - top: "pool22" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 2 - } -} -layer { - name: "norm22" - type: "LRN" - bottom: "pool22" - top: "norm22" - lrn_param { - local_size: 5 - alpha: 0.0001 - beta: 0.75 - } -} -layer { - name: "conv23" - type: "Convolution" - bottom: "norm22" - top: "conv23" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 384 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "relu23" - type: "ReLU" - bottom: "conv23" - top: "conv23" -} -layer { - name: "conv24" - type: "Convolution" - bottom: "conv23" - top: "conv24" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 384 - pad: 1 - kernel_size: 3 - group: 2 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - value: 1 - } - } -} -layer { - name: "relu24" - type: "ReLU" - bottom: "conv24" - top: "conv24" -} -layer { - name: "conv25" - type: "Convolution" - bottom: "conv24" - top: "conv25" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - group: 2 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - value: 1 - } - } -} -layer { - name: "relu25" - type: "ReLU" - bottom: "conv25" - top: "conv25" -} -layer { - name: "pool25" - type: "Pooling" - bottom: "conv25" - top: "pool25" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 2 - } -} - -layer { - name: "concat1" - type: "Concat" - bottom: "pool15" - bottom: "pool25" - top: "poolConcat" -} - -layer { - name: "fc6" - type: "InnerProduct" - bottom: "poolConcat" - top: "fc6" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - inner_product_param { - num_output: 4096 - weight_filler { - type: "gaussian" - std: 0.005 - } - bias_filler { - type: "constant" - value: 1 - } - } -} -layer { - name: "relu6" - type: "ReLU" - bottom: "fc6" - top: "fc6" -} -layer { - name: "drop6" - type: "Dropout" - bottom: "fc6" - top: "fc6" - dropout_param { - dropout_ratio: 0.5 - } -} -layer { - name: "fc7" - type: "InnerProduct" - bottom: "fc6" - top: "fc7" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - inner_product_param { - num_output: 4096 - weight_filler { - type: "gaussian" - std: 0.005 - } - bias_filler { - type: "constant" - value: 1 - } - } -} -layer { - name: "relu7" - type: "ReLU" - bottom: "fc7" - top: "fc7" -} -layer { - name: "drop7" - type: "Dropout" - bottom: "fc7" - top: "fc7" - dropout_param { - dropout_ratio: 0.5 - } -} -layer { - name: "fc8" - type: "InnerProduct" - bottom: "fc7" - top: "fc8" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - inner_product_param { - num_output: 4 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "scale" - bottom: "fc8" - top: "out" - type: "Power" - power_param { - power: 1 - scale: 10 - shift: 0 - } -} diff --git a/testdata/dnn/gtsrb.prototxt b/testdata/dnn/gtsrb.prototxt deleted file mode 100644 index e10c39fa1..000000000 --- a/testdata/dnn/gtsrb.prototxt +++ /dev/null @@ -1,166 +0,0 @@ -name: "gtsrb" -input: "input" -input_dim: 1 -input_dim: 3 -input_dim: 48 -input_dim: 48 - -layers { - bottom: "input" - top: "layer1" - name: "layer1" - type: CONVOLUTION - blobs_lr: 1 - blobs_lr: 2 - convolution_param { - num_output: 100 - kernel_size: 7 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - } - } -} -layers { - name: "tanh1" - bottom: "layer1" - top: "layer1" - type: TANH -} -layers { - bottom: "layer1" - top: "layer2" - name: "layer2" - type: POOLING - pooling_param { - pool: MAX - kernel_size: 2 - stride: 2 - } -} - -layers { - bottom: "layer2" - top: "layer3" - name: "layer3" - type: CONVOLUTION - blobs_lr: 1 - blobs_lr: 2 - convolution_param { - num_output: 150 - kernel_size: 4 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - } - } -} -layers { - name: "tanh3" - bottom: "layer3" - top: "layer3" - type: TANH -} -layers { - bottom: "layer3" - top: "layer4" - name: "layer4" - type: POOLING - pooling_param { - pool: MAX - kernel_size: 2 - stride: 2 - } -} - -layers { - bottom: "layer4" - top: "layer5" - name: "layer5" - type: CONVOLUTION - blobs_lr: 1 - blobs_lr: 2 - convolution_param { - num_output: 250 - kernel_size: 4 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - } - } -} -layers { - name: "tanh5" - bottom: "layer5" - top: "layer5" - type: TANH -} -layers { - bottom: "layer5" - top: "layer6" - name: "layer6" - type: POOLING - pooling_param { - pool: MAX - kernel_size: 2 - stride: 2 - } -} - -layers { - bottom: "layer6" - top: "layer7" - name: "layer7" - type: INNER_PRODUCT - blobs_lr: 1 - blobs_lr: 2 - inner_product_param { - num_output: 300 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - } - } -} -layers { - name: "tanh7" - bottom: "layer7" - top: "layer7" - type: TANH -} - -layers { - bottom: "layer7" - top: "layer8" - name: "layer8" - type: INNER_PRODUCT - blobs_lr: 1 - blobs_lr: 2 - inner_product_param { - num_output: 43 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - } - } -} - -layers { - name: "loss" - top: "loss" - bottom: "layer8" - type: SOFTMAX -} diff --git a/testdata/dnn/layers/accum.input_0.npy b/testdata/dnn/layers/accum.input_0.npy deleted file mode 100644 index 896f1f594..000000000 Binary files a/testdata/dnn/layers/accum.input_0.npy and /dev/null differ diff --git a/testdata/dnn/layers/accum.input_1.npy b/testdata/dnn/layers/accum.input_1.npy deleted file mode 100644 index a6f140c0a..000000000 Binary files a/testdata/dnn/layers/accum.input_1.npy and /dev/null differ diff --git a/testdata/dnn/layers/accum.npy b/testdata/dnn/layers/accum.npy deleted file mode 100644 index dc1da334a..000000000 Binary files a/testdata/dnn/layers/accum.npy and /dev/null differ diff --git a/testdata/dnn/layers/accum.prototxt b/testdata/dnn/layers/accum.prototxt deleted file mode 100644 index d1b30feb0..000000000 --- a/testdata/dnn/layers/accum.prototxt +++ /dev/null @@ -1,25 +0,0 @@ -name: "Accum" -input: "input_0" -input: "input_1" -input_shape { - dim: 1 - dim: 2 - dim: 2 - dim: 3 -} -input_shape { - dim: 1 - dim: 3 - dim: 8 - dim: 12 -} -layer { - name: "Accum1" - type: "Accum" - bottom: "input_0" - bottom: "input_1" - top: "out" - accum_param { - have_reference: false - } -} diff --git a/testdata/dnn/layers/accum_ref.input_0.npy b/testdata/dnn/layers/accum_ref.input_0.npy deleted file mode 100644 index 896f1f594..000000000 Binary files a/testdata/dnn/layers/accum_ref.input_0.npy and /dev/null differ diff --git a/testdata/dnn/layers/accum_ref.input_1.npy b/testdata/dnn/layers/accum_ref.input_1.npy deleted file mode 100644 index a6f140c0a..000000000 Binary files a/testdata/dnn/layers/accum_ref.input_1.npy and /dev/null differ diff --git a/testdata/dnn/layers/accum_ref.npy b/testdata/dnn/layers/accum_ref.npy deleted file mode 100644 index 512cb51d6..000000000 Binary files a/testdata/dnn/layers/accum_ref.npy and /dev/null differ diff --git a/testdata/dnn/layers/accum_ref.prototxt b/testdata/dnn/layers/accum_ref.prototxt deleted file mode 100644 index 347c7b727..000000000 --- a/testdata/dnn/layers/accum_ref.prototxt +++ /dev/null @@ -1,25 +0,0 @@ -name: "Accum" -input: "input_0" -input: "input_1" -input_shape { - dim: 1 - dim: 2 - dim: 2 - dim: 3 -} -input_shape { - dim: 1 - dim: 3 - dim: 8 - dim: 12 -} -layer { - name: "Accum1" - type: "Accum" - bottom: "input_0" - bottom: "input_1" - top: "out" - accum_param { - have_reference: true - } -} diff --git a/testdata/dnn/layers/channel_norm.input.npy b/testdata/dnn/layers/channel_norm.input.npy deleted file mode 100644 index f0f056a21..000000000 Binary files a/testdata/dnn/layers/channel_norm.input.npy and /dev/null differ diff --git a/testdata/dnn/layers/channel_norm.npy b/testdata/dnn/layers/channel_norm.npy deleted file mode 100644 index 7cee3a4da..000000000 Binary files a/testdata/dnn/layers/channel_norm.npy and /dev/null differ diff --git a/testdata/dnn/layers/channel_norm.prototxt b/testdata/dnn/layers/channel_norm.prototxt deleted file mode 100644 index 725ce9afb..000000000 --- a/testdata/dnn/layers/channel_norm.prototxt +++ /dev/null @@ -1,74 +0,0 @@ -name: "ChannelNorm" -input: "input" -input_shape { - dim: 1 - dim: 3 - dim: 4 - dim: 3 -} -layer { - name: "Sqr1" - type: "Power" - bottom: "input" - top: "blob45" - power_param { - power: 2 - } -} -layer{ - type: "Reshape" - name: "dummy_reshape" - bottom: "blob45" - reshape_param{ - shape{ - dim: 1 - dim: 1 - dim: 3 - dim: -1 - } - axis: 0 - num_axes: -1 - } - top: "dummy_reshape" -} -layer { - type: "Pooling" - pooling_param{ - pool: AVE - pad_h: 0 - pad_w: 0 - kernel_w: 1 - kernel_h: 3 - stride_h: 1 - stride_w: 1 - } - name: "AvePool" - bottom: "dummy_reshape" - top: "ave_pool" -} -layer { - name: "Mul1" - type: "Power" - bottom: "ave_pool" - top: "mul" - power_param { - scale: 3 - power: 0.5 - } -} -layer{ - type: "Reshape" - name: "reshape_back" - bottom: "mul" - reshape_param{ - shape{ - dim: 1 - dim: 1 - dim: 4 - dim: -1 - } - axis: 0 - num_axes: -1 - } - top: "out" -} diff --git a/testdata/dnn/layers/conv_2_inps.caffemodel b/testdata/dnn/layers/conv_2_inps.caffemodel deleted file mode 100644 index f0078f153..000000000 Binary files a/testdata/dnn/layers/conv_2_inps.caffemodel and /dev/null differ diff --git a/testdata/dnn/layers/conv_2_inps.input_0.npy b/testdata/dnn/layers/conv_2_inps.input_0.npy deleted file mode 100644 index 233fdbbf5..000000000 Binary files a/testdata/dnn/layers/conv_2_inps.input_0.npy and /dev/null differ diff --git a/testdata/dnn/layers/conv_2_inps.input_1.npy b/testdata/dnn/layers/conv_2_inps.input_1.npy deleted file mode 100644 index fc9be0290..000000000 Binary files a/testdata/dnn/layers/conv_2_inps.input_1.npy and /dev/null differ diff --git a/testdata/dnn/layers/conv_2_inps.npy b/testdata/dnn/layers/conv_2_inps.npy deleted file mode 100644 index 30a106c20..000000000 Binary files a/testdata/dnn/layers/conv_2_inps.npy and /dev/null differ diff --git a/testdata/dnn/layers/conv_2_inps.prototxt b/testdata/dnn/layers/conv_2_inps.prototxt deleted file mode 100644 index 42902b6f4..000000000 --- a/testdata/dnn/layers/conv_2_inps.prototxt +++ /dev/null @@ -1,45 +0,0 @@ -name: "Convolution" -input: "input_0" -input: "input_1" -input_shape { - dim: 1 - dim: 3 - dim: 4 - dim: 5 -} -input_shape { - dim: 1 - dim: 3 - dim: 4 - dim: 5 -} -layer { - name: "Convolution1" - type: "Convolution" - bottom: "input_0" - bottom: "input_1" - top: "out_0" - top: "out_1" - convolution_param { - num_output: 2 - pad: 1 - kernel_size: 2 - stride: 2 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - } - } -} -layer { - type: "Eltwise" - name: "eltwise_sum" - bottom: "out_0" - bottom: "out_1" - top: "out" - eltwise_param { - operation: SUM - } -} diff --git a/testdata/dnn/layers/correlation.input_0.npy b/testdata/dnn/layers/correlation.input_0.npy deleted file mode 100644 index d773823e5..000000000 Binary files a/testdata/dnn/layers/correlation.input_0.npy and /dev/null differ diff --git a/testdata/dnn/layers/correlation.input_1.npy b/testdata/dnn/layers/correlation.input_1.npy deleted file mode 100644 index 2e9d0b5de..000000000 Binary files a/testdata/dnn/layers/correlation.input_1.npy and /dev/null differ diff --git a/testdata/dnn/layers/correlation.npy b/testdata/dnn/layers/correlation.npy deleted file mode 100644 index a0f756dc3..000000000 Binary files a/testdata/dnn/layers/correlation.npy and /dev/null differ diff --git a/testdata/dnn/layers/correlation.prototxt b/testdata/dnn/layers/correlation.prototxt deleted file mode 100644 index 98fef883a..000000000 --- a/testdata/dnn/layers/correlation.prototxt +++ /dev/null @@ -1,30 +0,0 @@ -name: "Correlation" -input: "input_0" -input: "input_1" -input_shape { - dim: 1 - dim: 3 - dim: 2 - dim: 2 -} -input_shape { - dim: 1 - dim: 3 - dim: 2 - dim: 2 -} -layer { - name: "corr" - type: "Correlation" - bottom: "input_0" - bottom: "input_1" - top: "out" - correlation_param { - pad: 1 - kernel_size: 1 - max_displacement: 1 - stride_1: 1 - stride_2: 1 - } -} - diff --git a/testdata/dnn/layers/data_augmentation.caffemodel b/testdata/dnn/layers/data_augmentation.caffemodel deleted file mode 100644 index 4c6ad2c75..000000000 Binary files a/testdata/dnn/layers/data_augmentation.caffemodel and /dev/null differ diff --git a/testdata/dnn/layers/data_augmentation.input.npy b/testdata/dnn/layers/data_augmentation.input.npy deleted file mode 100644 index f0f056a21..000000000 Binary files a/testdata/dnn/layers/data_augmentation.input.npy and /dev/null differ diff --git a/testdata/dnn/layers/data_augmentation.npy b/testdata/dnn/layers/data_augmentation.npy deleted file mode 100644 index d10b24338..000000000 Binary files a/testdata/dnn/layers/data_augmentation.npy and /dev/null differ diff --git a/testdata/dnn/layers/data_augmentation.prototxt b/testdata/dnn/layers/data_augmentation.prototxt deleted file mode 100644 index be6b9de3a..000000000 --- a/testdata/dnn/layers/data_augmentation.prototxt +++ /dev/null @@ -1,19 +0,0 @@ -name: "DataAugmentation" -input: "input" -input_shape { - dim: 1 - dim: 3 - dim: 4 - dim: 3 -} -layer { - name: "DataAugmentation1" - type: "DataAugmentation" - bottom: "input" - top: "out" - augmentation_param { - augment_during_test: true - recompute_mean: 1 - mean_per_pixel: false - } -} diff --git a/testdata/dnn/layers/data_augmentation_2x1.caffemodel b/testdata/dnn/layers/data_augmentation_2x1.caffemodel deleted file mode 100644 index 4c6ad2c75..000000000 Binary files a/testdata/dnn/layers/data_augmentation_2x1.caffemodel and /dev/null differ diff --git a/testdata/dnn/layers/data_augmentation_2x1.input.npy b/testdata/dnn/layers/data_augmentation_2x1.input.npy deleted file mode 100644 index 034118312..000000000 Binary files a/testdata/dnn/layers/data_augmentation_2x1.input.npy and /dev/null differ diff --git a/testdata/dnn/layers/data_augmentation_2x1.npy b/testdata/dnn/layers/data_augmentation_2x1.npy deleted file mode 100644 index 8695e2bff..000000000 Binary files a/testdata/dnn/layers/data_augmentation_2x1.npy and /dev/null differ diff --git a/testdata/dnn/layers/data_augmentation_2x1.prototxt b/testdata/dnn/layers/data_augmentation_2x1.prototxt deleted file mode 100644 index 3f465308b..000000000 --- a/testdata/dnn/layers/data_augmentation_2x1.prototxt +++ /dev/null @@ -1,19 +0,0 @@ -name: "DataAugmentation" -input: "input" -input_shape { - dim: 1 - dim: 3 - dim: 2 - dim: 1 -} -layer { - name: "DataAugmentation1" - type: "DataAugmentation" - bottom: "input" - top: "out" - augmentation_param { - augment_during_test: true - recompute_mean: 1 - mean_per_pixel: false - } -} diff --git a/testdata/dnn/layers/data_augmentation_8x6.caffemodel b/testdata/dnn/layers/data_augmentation_8x6.caffemodel deleted file mode 100644 index 4c6ad2c75..000000000 Binary files a/testdata/dnn/layers/data_augmentation_8x6.caffemodel and /dev/null differ diff --git a/testdata/dnn/layers/data_augmentation_8x6.input.npy b/testdata/dnn/layers/data_augmentation_8x6.input.npy deleted file mode 100644 index 110f85263..000000000 Binary files a/testdata/dnn/layers/data_augmentation_8x6.input.npy and /dev/null differ diff --git a/testdata/dnn/layers/data_augmentation_8x6.npy b/testdata/dnn/layers/data_augmentation_8x6.npy deleted file mode 100644 index 02a6aa7eb..000000000 Binary files a/testdata/dnn/layers/data_augmentation_8x6.npy and /dev/null differ diff --git a/testdata/dnn/layers/data_augmentation_8x6.prototxt b/testdata/dnn/layers/data_augmentation_8x6.prototxt deleted file mode 100644 index 93785e984..000000000 --- a/testdata/dnn/layers/data_augmentation_8x6.prototxt +++ /dev/null @@ -1,19 +0,0 @@ -name: "DataAugmentation" -input: "input" -input_shape { - dim: 1 - dim: 3 - dim: 8 - dim: 6 -} -layer { - name: "DataAugmentation1" - type: "DataAugmentation" - bottom: "input" - top: "out" - augmentation_param { - augment_during_test: true - recompute_mean: 1 - mean_per_pixel: false - } -} diff --git a/testdata/dnn/layers/flow_warp.input_0.npy b/testdata/dnn/layers/flow_warp.input_0.npy deleted file mode 100644 index a6f140c0a..000000000 Binary files a/testdata/dnn/layers/flow_warp.input_0.npy and /dev/null differ diff --git a/testdata/dnn/layers/flow_warp.input_1.npy b/testdata/dnn/layers/flow_warp.input_1.npy deleted file mode 100644 index c1617bbb7..000000000 Binary files a/testdata/dnn/layers/flow_warp.input_1.npy and /dev/null differ diff --git a/testdata/dnn/layers/flow_warp.npy b/testdata/dnn/layers/flow_warp.npy deleted file mode 100644 index fd7c43b3f..000000000 Binary files a/testdata/dnn/layers/flow_warp.npy and /dev/null differ diff --git a/testdata/dnn/layers/flow_warp.prototxt b/testdata/dnn/layers/flow_warp.prototxt deleted file mode 100644 index 243b618c5..000000000 --- a/testdata/dnn/layers/flow_warp.prototxt +++ /dev/null @@ -1,22 +0,0 @@ -name: "FlowWarp" -input: "input_0" -input: "input_1" -input_shape { - dim: 1 - dim: 3 - dim: 8 - dim: 12 -} -input_shape { - dim: 1 - dim: 2 - dim: 8 - dim: 12 -} -layer { - name: "FlowWarp1" - type: "FlowWarp" - bottom: "input_0" - bottom: "input_1" - top: "out" -} diff --git a/testdata/dnn/layers/layer_batch_norm.caffemodel b/testdata/dnn/layers/layer_batch_norm.caffemodel deleted file mode 100644 index a5ffb3f5e..000000000 Binary files a/testdata/dnn/layers/layer_batch_norm.caffemodel and /dev/null differ diff --git a/testdata/dnn/layers/layer_batch_norm.npy b/testdata/dnn/layers/layer_batch_norm.npy deleted file mode 100644 index 6372e421e..000000000 Binary files a/testdata/dnn/layers/layer_batch_norm.npy and /dev/null differ diff --git a/testdata/dnn/layers/layer_batch_norm.prototxt b/testdata/dnn/layers/layer_batch_norm.prototxt deleted file mode 100644 index ca254f24c..000000000 --- a/testdata/dnn/layers/layer_batch_norm.prototxt +++ /dev/null @@ -1,14 +0,0 @@ -name: "test_BatchNorm" -input: "input" - -input_dim: 2 -input_dim: 6 -input_dim: 75 -input_dim: 113 - -layer { - type: "BatchNorm" - name: "output" - bottom: "input" - top: "output" -} \ No newline at end of file diff --git a/testdata/dnn/layers/layer_batch_norm_local_stats.caffemodel b/testdata/dnn/layers/layer_batch_norm_local_stats.caffemodel deleted file mode 100644 index d872e0741..000000000 Binary files a/testdata/dnn/layers/layer_batch_norm_local_stats.caffemodel and /dev/null differ diff --git a/testdata/dnn/layers/layer_batch_norm_local_stats.input.npy b/testdata/dnn/layers/layer_batch_norm_local_stats.input.npy deleted file mode 100644 index 1201fab91..000000000 Binary files a/testdata/dnn/layers/layer_batch_norm_local_stats.input.npy and /dev/null differ diff --git a/testdata/dnn/layers/layer_batch_norm_local_stats.npy b/testdata/dnn/layers/layer_batch_norm_local_stats.npy deleted file mode 100644 index ac2af1095..000000000 Binary files a/testdata/dnn/layers/layer_batch_norm_local_stats.npy and /dev/null differ diff --git a/testdata/dnn/layers/layer_batch_norm_local_stats.prototxt b/testdata/dnn/layers/layer_batch_norm_local_stats.prototxt deleted file mode 100644 index f9ca7fa6a..000000000 --- a/testdata/dnn/layers/layer_batch_norm_local_stats.prototxt +++ /dev/null @@ -1,18 +0,0 @@ -name: "test_BatchNorm_local_stats" -input: "input" - -input_dim: 1 -input_dim: 2 -input_dim: 3 -input_dim: 4 - -layer { - type: "BatchNorm" - name: "output" - bottom: "input" - top: "output" - batch_norm_param { - use_global_stats: false - moving_average_fraction: 999.982 - } -} diff --git a/testdata/dnn/layers/layer_concat.npy b/testdata/dnn/layers/layer_concat.npy deleted file mode 100644 index 370bfe8a6..000000000 Binary files a/testdata/dnn/layers/layer_concat.npy and /dev/null differ diff --git a/testdata/dnn/layers/layer_concat.prototxt b/testdata/dnn/layers/layer_concat.prototxt deleted file mode 100644 index a2730a20a..000000000 --- a/testdata/dnn/layers/layer_concat.prototxt +++ /dev/null @@ -1,21 +0,0 @@ -name: "test_Concat" -input: "input" - -input_dim: 2 -input_dim: 6 -input_dim: 75 -input_dim: 113 - -layer { - type: "Split" - name: "split" - bottom: "input" - top: "split" -} - -layer { - type: "Concat" - name: "output" - bottom: "split" - top: "output" -} \ No newline at end of file diff --git a/testdata/dnn/layers/layer_concat_optim.caffemodel b/testdata/dnn/layers/layer_concat_optim.caffemodel deleted file mode 100644 index 5f25f8aef..000000000 Binary files a/testdata/dnn/layers/layer_concat_optim.caffemodel and /dev/null differ diff --git a/testdata/dnn/layers/layer_concat_optim.input.npy b/testdata/dnn/layers/layer_concat_optim.input.npy deleted file mode 100644 index 2b88a9ebb..000000000 Binary files a/testdata/dnn/layers/layer_concat_optim.input.npy and /dev/null differ diff --git a/testdata/dnn/layers/layer_concat_optim.npy b/testdata/dnn/layers/layer_concat_optim.npy deleted file mode 100644 index 4dc90c035..000000000 Binary files a/testdata/dnn/layers/layer_concat_optim.npy and /dev/null differ diff --git a/testdata/dnn/layers/layer_concat_optim.prototxt b/testdata/dnn/layers/layer_concat_optim.prototxt deleted file mode 100644 index 4a51466b7..000000000 --- a/testdata/dnn/layers/layer_concat_optim.prototxt +++ /dev/null @@ -1,60 +0,0 @@ -name: "test_Concat_optimization" - -input: "input" -input_dim: 1 -input_dim: 2 -input_dim: 3 -input_dim: 4 - -layer { - type: "Convolution" - convolution_param - { - num_output: 6 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler{ type: 'uniform' min: -1 max: 1 } - bias_filler { type: 'uniform' min: -1 max: 1 } - } - name: "conv" - bottom: "input" - top: "conv" -} -layer { - type: "ReLU" - name: "relu" - bottom: "conv" - top: "relu" -} -layer { - type: "Concat" - name: "concat" - bottom: "relu" - top: "concat" -} -layer { - type: "Convolution" - convolution_param - { - num_output: 6 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler{ type: 'uniform' min: -1 max: 1 } - bias_filler { type: 'uniform' min: -1 max: 1 } - } - name: "consumer" - bottom: "relu" - top: "consumer" -} -layer { - name: "output" - type: "Eltwise" - bottom: "concat" - bottom: "consumer" - top: "output" - eltwise_param { - operation: SUM - } -} diff --git a/testdata/dnn/layers/layer_concat_shared_input.caffemodel b/testdata/dnn/layers/layer_concat_shared_input.caffemodel deleted file mode 100644 index e3b01963e..000000000 Binary files a/testdata/dnn/layers/layer_concat_shared_input.caffemodel and /dev/null differ diff --git a/testdata/dnn/layers/layer_concat_shared_input.input.npy b/testdata/dnn/layers/layer_concat_shared_input.input.npy deleted file mode 100644 index 6a8a5a06f..000000000 Binary files a/testdata/dnn/layers/layer_concat_shared_input.input.npy and /dev/null differ diff --git a/testdata/dnn/layers/layer_concat_shared_input.npy b/testdata/dnn/layers/layer_concat_shared_input.npy deleted file mode 100644 index 3bbd7cd49..000000000 Binary files a/testdata/dnn/layers/layer_concat_shared_input.npy and /dev/null differ diff --git a/testdata/dnn/layers/layer_concat_shared_input.prototxt b/testdata/dnn/layers/layer_concat_shared_input.prototxt deleted file mode 100644 index d42c8cc42..000000000 --- a/testdata/dnn/layers/layer_concat_shared_input.prototxt +++ /dev/null @@ -1,81 +0,0 @@ -# input -# conv1 ------+---+ -# conv2 | | -# concat1 <---+ | -# conv3 | -# conv4 | -# concat2 <-------+ -name: "test_Concat_shared_input" -input: "input" - -input_dim: 1 -input_dim: 2 -input_dim: 3 -input_dim: 4 - -layer { - name: "conv1" - type: "Convolution" - bottom: "input" - top: "conv1" - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - weight_filler { type: "gaussian" std: 0.01 } - bias_filler { type: "gaussian" std: 0.01 } - } -} -layer { - name: "conv2" - type: "Convolution" - bottom: "conv1" - top: "conv2" - convolution_param { - num_output: 22 - pad: 0 - kernel_size: 1 - weight_filler { type: "gaussian" std: 0.01 } - bias_filler { type: "gaussian" std: 0.01 } - } -} -layer { - name: "concat1" - type: "Concat" - bottom: "conv2" - bottom: "conv1" - top: "concat1" -} -layer { - name: "conv3" - type: "Convolution" - bottom: "concat1" - top: "conv3" - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - weight_filler { type: "gaussian" std: 0.1 } - bias_filler { type: "gaussian" std: 0.1 } - } -} -layer { - name: "conv4" - type: "Convolution" - bottom: "conv3" - top: "conv4" - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - weight_filler { type: "gaussian" std: 0.01 } - bias_filler { type: "gaussian" std: 0.01 } - } -} -layer { - name: "output" - type: "Concat" - bottom: "conv4" - bottom: "conv1" - top: "output" -} diff --git a/testdata/dnn/layers/layer_convolution.caffemodel b/testdata/dnn/layers/layer_convolution.caffemodel deleted file mode 100644 index aadae5768..000000000 Binary files a/testdata/dnn/layers/layer_convolution.caffemodel and /dev/null differ diff --git a/testdata/dnn/layers/layer_convolution.prototxt b/testdata/dnn/layers/layer_convolution.prototxt deleted file mode 100644 index 979d34352..000000000 --- a/testdata/dnn/layers/layer_convolution.prototxt +++ /dev/null @@ -1,39 +0,0 @@ -name: "test_Convolution" -input: "input" - -input_dim: 2 -input_dim: 6 -input_dim: 75 -input_dim: 113 - -layer { - type: "Convolution" - - convolution_param - { - group: 3 - num_output: 12 - - pad_h: 0 - pad_w: 1 - kernel_h: 4 - kernel_w: 5 - stride_h: 2 - stride_w: 3 - - weight_filler{ - type: 'uniform' - min: -1 - max: 1 - } - bias_filler { - type: 'uniform' - min: -1 - max: 1 - } - } - - name: "output" - bottom: "input" - top: "output" -} \ No newline at end of file diff --git a/testdata/dnn/layers/layer_deconvolution.caffemodel b/testdata/dnn/layers/layer_deconvolution.caffemodel deleted file mode 100644 index 1fd778e92..000000000 Binary files a/testdata/dnn/layers/layer_deconvolution.caffemodel and /dev/null differ diff --git a/testdata/dnn/layers/layer_deconvolution.input.npy b/testdata/dnn/layers/layer_deconvolution.input.npy deleted file mode 100644 index 6b80f3cfb..000000000 Binary files a/testdata/dnn/layers/layer_deconvolution.input.npy and /dev/null differ diff --git a/testdata/dnn/layers/layer_deconvolution.npy b/testdata/dnn/layers/layer_deconvolution.npy deleted file mode 100644 index cc4508660..000000000 Binary files a/testdata/dnn/layers/layer_deconvolution.npy and /dev/null differ diff --git a/testdata/dnn/layers/layer_deconvolution.prototxt b/testdata/dnn/layers/layer_deconvolution.prototxt deleted file mode 100644 index a7d793774..000000000 --- a/testdata/dnn/layers/layer_deconvolution.prototxt +++ /dev/null @@ -1,39 +0,0 @@ -name: "test_Convolution" -input: "input" - -input_dim: 2 -input_dim: 12 -input_dim: 36 -input_dim: 37 - -layer { - type: "Deconvolution" - - convolution_param - { - group: 3 - num_output: 15 - - pad_h: 0 - pad_w: 1 - kernel_size: 4 - kernel_size: 5 - stride_h: 2 - stride_w: 3 - - weight_filler{ - type: 'uniform' - min: -1 - max: 1 - } - bias_filler { - type: 'uniform' - min: -1 - max: 1 - } - } - - name: "output" - bottom: "input" - top: "output" -} diff --git a/testdata/dnn/layers/layer_dropout.npy b/testdata/dnn/layers/layer_dropout.npy deleted file mode 100644 index 370bfe8a6..000000000 Binary files a/testdata/dnn/layers/layer_dropout.npy and /dev/null differ diff --git a/testdata/dnn/layers/layer_dropout.prototxt b/testdata/dnn/layers/layer_dropout.prototxt deleted file mode 100644 index effed3b34..000000000 --- a/testdata/dnn/layers/layer_dropout.prototxt +++ /dev/null @@ -1,18 +0,0 @@ -name: "test_Dropout" -input: "input" - -input_dim: 2 -input_dim: 6 -input_dim: 75 -input_dim: 113 - -layer { - type: "Dropout" - dropout_param - { - dropout_ratio: 0.12345 - } - name: "output" - bottom: "input" - top: "output" -} \ No newline at end of file diff --git a/testdata/dnn/layers/layer_eltwise.npy b/testdata/dnn/layers/layer_eltwise.npy deleted file mode 100644 index 3da786597..000000000 Binary files a/testdata/dnn/layers/layer_eltwise.npy and /dev/null differ diff --git a/testdata/dnn/layers/layer_eltwise.prototxt b/testdata/dnn/layers/layer_eltwise.prototxt deleted file mode 100644 index ca2af9091..000000000 --- a/testdata/dnn/layers/layer_eltwise.prototxt +++ /dev/null @@ -1,69 +0,0 @@ -name: "test_Eltwise" -input: "input" -input_dim: 2 -input_dim: 6 -input_dim: 75 -input_dim: 113 - -layer { - type: "Eltwise" - name: "eltwise_sum" - bottom: "input" - bottom: "input" - top: "eltwise_sum" - eltwise_param { - operation: SUM - coeff: 0.1 - coeff: 0.2 - } -} - -layer { - type: "Reshape" - name: "reshape_input_3d" - bottom: "input" - reshape_param{ shape { dim: 6 dim: 2 dim: 8475 } } - top: "reshape_input_3d" -} -layer { - type: "Reshape" - name: "reshape_eltwise_sum_3d" - bottom: "eltwise_sum" - reshape_param{ shape { dim: 6 dim: 2 dim: 8475 } } - top: "reshape_eltwise_sum_3d" -} -layer { - type: "Eltwise" - name: "eltwise_prod" - bottom: "reshape_input_3d" - bottom: "reshape_eltwise_sum_3d" - top: "eltwise_prod" - eltwise_param { - operation: PROD - } -} - -layer { - type: "Reshape" - name: "reshape_eltwise_sum_2d" - bottom: "eltwise_sum" - reshape_param{ shape { dim: 2 dim: 50850 } } - top: "reshape_eltwise_sum_2d" -} -layer { - type: "Reshape" - name: "reshape_eltwise_prod_2d" - bottom: "eltwise_prod" - reshape_param{ shape { dim: 2 dim: 50850 } } - top: "reshape_eltwise_prod_2d" -} -layer { - type: "Eltwise" - name: "output" - bottom: "reshape_eltwise_sum_2d" - bottom: "reshape_eltwise_prod_2d" - top: "output" - eltwise_param { - operation: MAX - } -} diff --git a/testdata/dnn/layers/layer_elu_in.npy b/testdata/dnn/layers/layer_elu_in.npy deleted file mode 100644 index 5e763902b..000000000 Binary files a/testdata/dnn/layers/layer_elu_in.npy and /dev/null differ diff --git a/testdata/dnn/layers/layer_elu_out.npy b/testdata/dnn/layers/layer_elu_out.npy deleted file mode 100644 index f52ceb1d0..000000000 Binary files a/testdata/dnn/layers/layer_elu_out.npy and /dev/null differ diff --git a/testdata/dnn/layers/layer_inner_product.caffemodel b/testdata/dnn/layers/layer_inner_product.caffemodel deleted file mode 100644 index 683d64fd7..000000000 Binary files a/testdata/dnn/layers/layer_inner_product.caffemodel and /dev/null differ diff --git a/testdata/dnn/layers/layer_inner_product.npy b/testdata/dnn/layers/layer_inner_product.npy deleted file mode 100644 index 2c6247e80..000000000 Binary files a/testdata/dnn/layers/layer_inner_product.npy and /dev/null differ diff --git a/testdata/dnn/layers/layer_inner_product.prototxt b/testdata/dnn/layers/layer_inner_product.prototxt deleted file mode 100644 index 62368d777..000000000 --- a/testdata/dnn/layers/layer_inner_product.prototxt +++ /dev/null @@ -1,63 +0,0 @@ -name: "test_InnerProduct" -input: "input" - -input_dim: 2 -input_dim: 6 -input_dim: 75 -input_dim: 113 - -# 2x6x75x113 -> 2x6x10 -layer { - type: "InnerProduct" - inner_product_param - { - axis: 2 - num_output: 10 - weight_filler { - type: "xavier" - std: 0.1 - } - bias_filler { - type: 'uniform' - min: -1 - max: 1 - } - } - name: "fc1" - bottom: "input" - top: "fc1" -} - -# 2x6x10 -> 2x20 -layer { - type: "InnerProduct" - - inner_product_param - { - axis: 1 - num_output: 20 - - weight_filler { - type: "xavier" - std: 0.1 - } - bias_filler { - type: 'uniform' - min: -1 - max: 1 - } - } - - name: "fc2" - bottom: "fc1" - top: "fc2" -} - -layer { - type: "Scale" - scale_param { bias_term: true } - - name: "output" - bottom: "fc2" - top: "output" -} diff --git a/testdata/dnn/layers/layer_interp.input.npy b/testdata/dnn/layers/layer_interp.input.npy deleted file mode 100644 index 798af6bd6..000000000 Binary files a/testdata/dnn/layers/layer_interp.input.npy and /dev/null differ diff --git a/testdata/dnn/layers/layer_interp.npy b/testdata/dnn/layers/layer_interp.npy deleted file mode 100644 index 90333e35b..000000000 Binary files a/testdata/dnn/layers/layer_interp.npy and /dev/null differ diff --git a/testdata/dnn/layers/layer_interp.prototxt b/testdata/dnn/layers/layer_interp.prototxt deleted file mode 100644 index ae6993728..000000000 --- a/testdata/dnn/layers/layer_interp.prototxt +++ /dev/null @@ -1,27 +0,0 @@ -name: "test_layer_interp" -input: "input" -input_shape { - dim: 2 - dim: 3 - dim: 4 - dim: 5 -} -layer { - name: "first" - type: "Interp" - bottom: "input" - top: "first" - interp_param { - height: 9 - width: 8 - } -} -layer { - name: "output" - type: "Interp" - bottom: "first" - top: "output" - interp_param { - zoom_factor: 2 - } -} diff --git a/testdata/dnn/layers/layer_lrn_channels.npy b/testdata/dnn/layers/layer_lrn_channels.npy deleted file mode 100644 index b54860551..000000000 Binary files a/testdata/dnn/layers/layer_lrn_channels.npy and /dev/null differ diff --git a/testdata/dnn/layers/layer_lrn_channels.prototxt b/testdata/dnn/layers/layer_lrn_channels.prototxt deleted file mode 100644 index a8ec041c1..000000000 --- a/testdata/dnn/layers/layer_lrn_channels.prototxt +++ /dev/null @@ -1,21 +0,0 @@ -name: "test_LRN_channels" -input: "input" - -input_dim: 2 -input_dim: 6 -input_dim: 75 -input_dim: 113 - -layer { - type: "LRN" - lrn_param { - norm_region: ACROSS_CHANNELS; - local_size: 5 - alpha: 1.1 - beta: 0.75 - } - - name: "output" - bottom: "input" - top: "output" -} diff --git a/testdata/dnn/layers/layer_lrn_spatial.npy b/testdata/dnn/layers/layer_lrn_spatial.npy deleted file mode 100644 index 7fcb60f66..000000000 Binary files a/testdata/dnn/layers/layer_lrn_spatial.npy and /dev/null differ diff --git a/testdata/dnn/layers/layer_lrn_spatial.prototxt b/testdata/dnn/layers/layer_lrn_spatial.prototxt deleted file mode 100644 index df88afbd5..000000000 --- a/testdata/dnn/layers/layer_lrn_spatial.prototxt +++ /dev/null @@ -1,22 +0,0 @@ -name: "test_LRN_spatial" -input: "input" - -input_dim: 2 -input_dim: 6 -input_dim: 75 -input_dim: 113 - -layer { - type: "LRN" - - lrn_param { - norm_region: WITHIN_CHANNEL; - local_size: 5 - alpha: 0.9 - beta: 0.75 - } - - name: "output" - bottom: "input" - top: "output" -} diff --git a/testdata/dnn/layers/layer_mvn.npy b/testdata/dnn/layers/layer_mvn.npy deleted file mode 100644 index 4ad1a7b3c..000000000 Binary files a/testdata/dnn/layers/layer_mvn.npy and /dev/null differ diff --git a/testdata/dnn/layers/layer_mvn.prototxt b/testdata/dnn/layers/layer_mvn.prototxt deleted file mode 100644 index ade0213e3..000000000 --- a/testdata/dnn/layers/layer_mvn.prototxt +++ /dev/null @@ -1,21 +0,0 @@ -name: "test_MVN_channels" -input: "input" - -input_dim: 2 -input_dim: 6 -input_dim: 75 -input_dim: 113 - -layer { - type: "MVN" - - mvn_param { - eps: 1e-5 - across_channels: false - normalize_variance: true - } - - name: "output" - bottom: "input" - top: "output" -} diff --git a/testdata/dnn/layers/layer_pooling_ave.npy b/testdata/dnn/layers/layer_pooling_ave.npy deleted file mode 100644 index a87cb911d..000000000 Binary files a/testdata/dnn/layers/layer_pooling_ave.npy and /dev/null differ diff --git a/testdata/dnn/layers/layer_pooling_ave.prototxt b/testdata/dnn/layers/layer_pooling_ave.prototxt deleted file mode 100644 index 95cff9aad..000000000 --- a/testdata/dnn/layers/layer_pooling_ave.prototxt +++ /dev/null @@ -1,26 +0,0 @@ -name: "test_Pooling_max" -input: "input" - -input_dim: 2 -input_dim: 6 -input_dim: 75 -input_dim: 113 - -layer { - type: "Pooling" - - pooling_param - { - pool: AVE - pad_h: 2 - pad_w: 1 - kernel_h: 3 - kernel_w: 5 - stride_h: 2 - stride_w: 1 - } - - name: "output" - bottom: "input" - top: "output" -} \ No newline at end of file diff --git a/testdata/dnn/layers/layer_pooling_max.npy b/testdata/dnn/layers/layer_pooling_max.npy deleted file mode 100644 index bc726db1b..000000000 Binary files a/testdata/dnn/layers/layer_pooling_max.npy and /dev/null differ diff --git a/testdata/dnn/layers/layer_pooling_max.prototxt b/testdata/dnn/layers/layer_pooling_max.prototxt deleted file mode 100644 index 5c4f4155c..000000000 --- a/testdata/dnn/layers/layer_pooling_max.prototxt +++ /dev/null @@ -1,26 +0,0 @@ -name: "test_Pooling_max" -input: "input" - -input_dim: 2 -input_dim: 6 -input_dim: 75 -input_dim: 113 - -layer { - type: "Pooling" - - pooling_param - { - pool: MAX - pad_h: 2 - pad_w: 1 - kernel_h: 3 - kernel_w: 5 - stride_h: 2 - stride_w: 1 - } - - name: "output" - bottom: "input" - top: "output" -} \ No newline at end of file diff --git a/testdata/dnn/layers/layer_prelu.caffemodel b/testdata/dnn/layers/layer_prelu.caffemodel deleted file mode 100644 index b5c750100..000000000 Binary files a/testdata/dnn/layers/layer_prelu.caffemodel and /dev/null differ diff --git a/testdata/dnn/layers/layer_prelu.npy b/testdata/dnn/layers/layer_prelu.npy deleted file mode 100644 index d7916d3e0..000000000 Binary files a/testdata/dnn/layers/layer_prelu.npy and /dev/null differ diff --git a/testdata/dnn/layers/layer_prelu.prototxt b/testdata/dnn/layers/layer_prelu.prototxt deleted file mode 100644 index e5bd448a4..000000000 --- a/testdata/dnn/layers/layer_prelu.prototxt +++ /dev/null @@ -1,37 +0,0 @@ -name: "test_PReLU" -layer { - name: "input" - type: "Input" - top: "input" - input_param { - shape { dim: 2 dim: 6 dim: 75 dim: 113 } - } -} -layer { - name: "prelu_1" - type: "PReLU" - bottom: "input" - top: "input" - prelu_param { - filler { - type: "gaussian" - mean: 0.0 - std: 0.01 - } - channel_shared: false - } -} -layer { - name: "output" - type: "PReLU" - bottom: "input" - top: "output" - prelu_param { - filler { - type: "gaussian" - mean: 0.0 - std: 0.01 - } - channel_shared: true - } -} diff --git a/testdata/dnn/layers/layer_prelu_fc.caffemodel b/testdata/dnn/layers/layer_prelu_fc.caffemodel deleted file mode 100644 index 11e3db566..000000000 Binary files a/testdata/dnn/layers/layer_prelu_fc.caffemodel and /dev/null differ diff --git a/testdata/dnn/layers/layer_prelu_fc.input.npy b/testdata/dnn/layers/layer_prelu_fc.input.npy deleted file mode 100644 index 5bf6fcb99..000000000 Binary files a/testdata/dnn/layers/layer_prelu_fc.input.npy and /dev/null differ diff --git a/testdata/dnn/layers/layer_prelu_fc.npy b/testdata/dnn/layers/layer_prelu_fc.npy deleted file mode 100644 index 350f4d0d7..000000000 Binary files a/testdata/dnn/layers/layer_prelu_fc.npy and /dev/null differ diff --git a/testdata/dnn/layers/layer_prelu_fc.prototxt b/testdata/dnn/layers/layer_prelu_fc.prototxt deleted file mode 100644 index e268263b1..000000000 --- a/testdata/dnn/layers/layer_prelu_fc.prototxt +++ /dev/null @@ -1,54 +0,0 @@ -name: "test_PReLU_FC" -layer { - name: "input" - type: "Input" - top: "input" - input_param { - shape { dim: 2 dim: 3 dim: 4 dim: 5 } - } -} - -layer { - type: "InnerProduct" - inner_product_param { - num_output: 10 - weight_filler { - type: "xavier" - std: 0.1 - } - bias_filler { - type: 'uniform' - min: -1 - max: 1 - } - } - name: "fc1" - bottom: "input" - top: "fc1" -} -layer { - name: "prelu_1" - type: "PReLU" - bottom: "fc1" - top: "fc1" - prelu_param { - filler { - type: "gaussian" - mean: 0.0 - std: 0.01 - } - } -} -layer { - name: "output" - type: "PReLU" - bottom: "fc1" - top: "output" - prelu_param { - filler { - type: "gaussian" - mean: 0.0 - std: 0.01 - } - } -} diff --git a/testdata/dnn/layers/layer_relu.npy b/testdata/dnn/layers/layer_relu.npy deleted file mode 100644 index 673ca6e61..000000000 Binary files a/testdata/dnn/layers/layer_relu.npy and /dev/null differ diff --git a/testdata/dnn/layers/layer_relu.prototxt b/testdata/dnn/layers/layer_relu.prototxt deleted file mode 100644 index ceed3627d..000000000 --- a/testdata/dnn/layers/layer_relu.prototxt +++ /dev/null @@ -1,14 +0,0 @@ -name: "test_ReLU" -input: "input" - -input_dim: 2 -input_dim: 6 -input_dim: 75 -input_dim: 113 - -layer { - type: "ReLU" - name: "output" - bottom: "input" - top: "output" -} \ No newline at end of file diff --git a/testdata/dnn/layers/layer_softmax.npy b/testdata/dnn/layers/layer_softmax.npy deleted file mode 100644 index 7db85f01c..000000000 Binary files a/testdata/dnn/layers/layer_softmax.npy and /dev/null differ diff --git a/testdata/dnn/layers/layer_softmax.prototxt b/testdata/dnn/layers/layer_softmax.prototxt deleted file mode 100644 index 3a717a4c6..000000000 --- a/testdata/dnn/layers/layer_softmax.prototxt +++ /dev/null @@ -1,15 +0,0 @@ -name: "test_Softmax" -input: "input" - -input_dim: 2 -input_dim: 6 -input_dim: 75 -input_dim: 113 - -layer { - type: "Softmax" - - name: "output" - bottom: "input" - top: "output" -} \ No newline at end of file diff --git a/testdata/dnn/layers/nearest.input.npy b/testdata/dnn/layers/nearest.input.npy deleted file mode 100644 index ac11aaab1..000000000 Binary files a/testdata/dnn/layers/nearest.input.npy and /dev/null differ diff --git a/testdata/dnn/layers/nearest.npy b/testdata/dnn/layers/nearest.npy deleted file mode 100644 index 5b5b77cf6..000000000 Binary files a/testdata/dnn/layers/nearest.npy and /dev/null differ diff --git a/testdata/dnn/layers/nearest.prototxt b/testdata/dnn/layers/nearest.prototxt deleted file mode 100644 index 3b42644ee..000000000 --- a/testdata/dnn/layers/nearest.prototxt +++ /dev/null @@ -1,21 +0,0 @@ -name: "Resample" -input: "input" - -input_shape { - dim: 1 - dim: 1 - dim: 2 - dim: 3 -} - -layer { - name: "Resample1" - type: "Resample" - bottom: "input" - top: "out" - resample_param { - type: NEAREST - antialias: false - factor: 2.0 - } -} diff --git a/testdata/dnn/layers/nearest_2inps.input_0.npy b/testdata/dnn/layers/nearest_2inps.input_0.npy deleted file mode 100644 index ac11aaab1..000000000 Binary files a/testdata/dnn/layers/nearest_2inps.input_0.npy and /dev/null differ diff --git a/testdata/dnn/layers/nearest_2inps.input_1.npy b/testdata/dnn/layers/nearest_2inps.input_1.npy deleted file mode 100644 index 08e2a69a1..000000000 Binary files a/testdata/dnn/layers/nearest_2inps.input_1.npy and /dev/null differ diff --git a/testdata/dnn/layers/nearest_2inps.npy b/testdata/dnn/layers/nearest_2inps.npy deleted file mode 100644 index 5b5b77cf6..000000000 Binary files a/testdata/dnn/layers/nearest_2inps.npy and /dev/null differ diff --git a/testdata/dnn/layers/nearest_2inps.prototxt b/testdata/dnn/layers/nearest_2inps.prototxt deleted file mode 100644 index 3513733e4..000000000 --- a/testdata/dnn/layers/nearest_2inps.prototxt +++ /dev/null @@ -1,27 +0,0 @@ -name: "Resample" -input: "input_0" -input: "input_1" -input_shape { - dim: 1 - dim: 1 - dim: 2 - dim: 3 -} -input_shape { - dim: 1 - dim: 1 - dim: 4 - dim: 6 -} -layer { - name: "Resample1" - type: "Resample" - bottom: "input_0" - bottom: "input_1" - top: "out" - resample_param { - type: NEAREST - antialias: false - factor: 1.0 - } -} diff --git a/testdata/dnn/layers/net_faster_rcnn_proposal.deltas.npy b/testdata/dnn/layers/net_faster_rcnn_proposal.deltas.npy deleted file mode 100644 index 3ae1dd6ef..000000000 Binary files a/testdata/dnn/layers/net_faster_rcnn_proposal.deltas.npy and /dev/null differ diff --git a/testdata/dnn/layers/net_faster_rcnn_proposal.out_rois.npy b/testdata/dnn/layers/net_faster_rcnn_proposal.out_rois.npy deleted file mode 100644 index c42be2f3c..000000000 Binary files a/testdata/dnn/layers/net_faster_rcnn_proposal.out_rois.npy and /dev/null differ diff --git a/testdata/dnn/layers/net_faster_rcnn_proposal.out_scores.npy b/testdata/dnn/layers/net_faster_rcnn_proposal.out_scores.npy deleted file mode 100644 index 6eb3b1f83..000000000 Binary files a/testdata/dnn/layers/net_faster_rcnn_proposal.out_scores.npy and /dev/null differ diff --git a/testdata/dnn/layers/net_faster_rcnn_proposal.prototxt b/testdata/dnn/layers/net_faster_rcnn_proposal.prototxt deleted file mode 100644 index 63aebe9bb..000000000 --- a/testdata/dnn/layers/net_faster_rcnn_proposal.prototxt +++ /dev/null @@ -1,74 +0,0 @@ -name: "TestFasterRCNNProposal" - -# input: "rpn_cls_prob_reshape" -# input_shape { -# dim: 1 -# dim: 18 -# dim: 39 -# dim: 51 -# } -# -# input: "rpn_bbox_pred" -# input_shape { -# dim: 1 -# dim: 36 -# dim: 39 -# dim: 51 -# } -# -# -# input: "im_info" -# input_shape { -# dim: 1 -# dim: 3 -# } - -layer { - type: 'Input' - name: 'rpn_cls_prob_reshape' - top: 'rpn_cls_prob_reshape' -} -layer { - type: 'Input' - name: 'rpn_bbox_pred' - top: 'rpn_bbox_pred' -} -layer { - type: 'Input' - name: 'im_info' - top: 'im_info' -} - -# layer { -# name: 'output' -# type: 'Python' -# bottom: 'rpn_cls_prob_reshape' -# bottom: 'rpn_bbox_pred' -# bottom: 'im_info' -# top: 'rois' -# top: 'scores' -# python_param { -# module: 'rpn.proposal_layer' -# layer: 'ProposalLayer' -# param_str: "'feat_stride': 9" -# } -# } - -layer { - name: 'output' - type: 'Proposal' - bottom: 'rpn_cls_prob_reshape' - bottom: 'rpn_bbox_pred' - bottom: 'im_info' - top: 'rois' - top: 'scores' - proposal_param { - feat_stride: 9 - ratio: 0.5 - ratio: 1.0 - ratio: 2.0 - scale: 8 - scale: 16 - scale: 32 - } -} diff --git a/testdata/dnn/layers/net_faster_rcnn_proposal.scores.npy b/testdata/dnn/layers/net_faster_rcnn_proposal.scores.npy deleted file mode 100644 index 53da4dfbf..000000000 Binary files a/testdata/dnn/layers/net_faster_rcnn_proposal.scores.npy and /dev/null differ diff --git a/testdata/dnn/layers/net_input.prototxt b/testdata/dnn/layers/net_input.prototxt deleted file mode 100644 index 2828e8b58..000000000 --- a/testdata/dnn/layers/net_input.prototxt +++ /dev/null @@ -1,64 +0,0 @@ -name: "TestInput" - -input: "old_style_input_blue_green" -input_dim: 1 -input_dim: 2 -input_dim: 10 -input_dim: 11 - -input: "old_style_input_red" -input_dim: 1 -input_dim: 1 -input_dim: 10 -input_dim: 11 - -layer { - type: "Input" - name: "input_red" - top: "different_name_for_red" # Top is different to 'name' field - input_param { - shape { - dim: 1 - dim: 1 - dim: 10 - dim: 11 - } - } -} -layer { - type: "Input" - name: "input_layer_blue_green" - top: "input_layer_blue_green" - input_param { - shape { - dim: 1 - dim: 2 - dim: 10 - dim: 11 - } - } -} -layer { - type: "Concat" - name: "first_image" - bottom: "old_style_input_blue_green" - bottom: "different_name_for_red" - top: "first_image_merged" -} -layer { - type: "Concat" - name: "second_image" - bottom: "input_layer_blue_green" - bottom: "old_style_input_red" - top: "second_image" -} -layer { - type: "Eltwise" - name: "output" - bottom: "first_image_merged" - bottom: "second_image" - top: "output" - eltwise_param { - operation: SUM - } -} diff --git a/testdata/dnn/layers/net_roi_pooling.input.npy b/testdata/dnn/layers/net_roi_pooling.input.npy deleted file mode 100644 index 6f0c6a24e..000000000 Binary files a/testdata/dnn/layers/net_roi_pooling.input.npy and /dev/null differ diff --git a/testdata/dnn/layers/net_roi_pooling.npy b/testdata/dnn/layers/net_roi_pooling.npy deleted file mode 100644 index 8f6efd883..000000000 Binary files a/testdata/dnn/layers/net_roi_pooling.npy and /dev/null differ diff --git a/testdata/dnn/layers/net_roi_pooling.prototxt b/testdata/dnn/layers/net_roi_pooling.prototxt deleted file mode 100644 index 3d640ea8c..000000000 --- a/testdata/dnn/layers/net_roi_pooling.prototxt +++ /dev/null @@ -1,46 +0,0 @@ -# Script to generate data. Be sure that PYTHONPATH contains path to -# https://github.com/rbgirshick/caffe-fast-rcnn/tree/fast-rcnn branch. So -# caffe.__file__ is a path to caffe-fast-rcnn/python/caffe/__init__.pyc -# -# import caffe -# import numpy as np -# -# caffe_net = caffe.Net('net_roi_pooling.prototxt', caffe.TEST) -# -# caffe_net.blobs['input'].data[:,:,:,:] = np.random.standard_normal([4, 3, 21, 17]).astype(np.float32) -# caffe_net.blobs['rois'].data[:,0] = np.random.randint(0, 4, [100]).astype(np.float32) -# caffe_net.blobs['rois'].data[:,1:] = np.random.randint(-10, 30, [100, 4]).astype(np.float32) -# print caffe_net.blobs['rois'].data -# caffe_net.forward() -# -# np.save('net_roi_pooling.input.npy', caffe_net.blobs['input'].data) -# np.save('net_roi_pooling.rois.npy', caffe_net.blobs['rois'].data) -# np.save('net_roi_pooling.npy', caffe_net.blobs['output'].data) -name: "test_ROIPooling" - -input: "input" -input_shape { - dim: 4 - dim: 3 - dim: 21 - dim: 17 -} - -input: "rois" -input_shape { - dim: 100 - dim: 5 -} - -layer { - name: "output" - type: "ROIPooling" - bottom: "input" - bottom: "rois" - top: "output" - roi_pooling_param { - pooled_w: 6 - pooled_h: 6 - spatial_scale: 0.0625 # 1/16 - } -} diff --git a/testdata/dnn/layers/net_roi_pooling.rois.npy b/testdata/dnn/layers/net_roi_pooling.rois.npy deleted file mode 100644 index 10a75bb0e..000000000 Binary files a/testdata/dnn/layers/net_roi_pooling.rois.npy and /dev/null differ diff --git a/testdata/dnn/layers/prior_box.prototxt b/testdata/dnn/layers/prior_box.prototxt deleted file mode 100644 index 38cc182c7..000000000 --- a/testdata/dnn/layers/prior_box.prototxt +++ /dev/null @@ -1,37 +0,0 @@ -name: "prior_box" -input: "data" -input_shape { - dim: 1 - dim: 3 - dim: 10 - dim: 10 -} - -input: "shape" -input_shape { - dim: 1 - dim: 2 - dim: 3 - dim: 4 -} - -layer { - name: "priorbox" - type: "PriorBox" - bottom: "shape" - bottom: "data" - top: "priorbox" - prior_box_param { - min_size: 2.0 - min_size: 3.0 - max_size: 6.0 - max_size: 7.0 - aspect_ratio: 2 - flip: true - clip: false - variance: 0.1 - variance: 0.1 - variance: 0.2 - variance: 0.2 - } -} diff --git a/testdata/dnn/layers/priorbox_output.npy b/testdata/dnn/layers/priorbox_output.npy deleted file mode 100644 index cf685d275..000000000 Binary files a/testdata/dnn/layers/priorbox_output.npy and /dev/null differ diff --git a/testdata/dnn/layers/reshape_and_slice_routines.prototxt b/testdata/dnn/layers/reshape_and_slice_routines.prototxt deleted file mode 100644 index 9d02133b4..000000000 --- a/testdata/dnn/layers/reshape_and_slice_routines.prototxt +++ /dev/null @@ -1,77 +0,0 @@ -name: "test_reshape_splice_split" -input: "input" - -layer{ - type: "Split" - name: "dummy_split" - bottom: "input" - top: "dummy_split_0" - top: "dummy_split_1" -} -layer{ - type: "Slice" - name: "dummy_slice_0" - bottom: "dummy_split_0" - slice_param{ - slice_point: 1 - slice_point: 2 - } - top: "dummy_slice_0_0" - top: "dummy_slice_0_1" - top: "dummy_slice_0_2" -} -layer{ - type: "Slice" - name: "dummy_slice_1" - bottom: "dummy_split_1" - slice_param{ - slice_point: 1 - slice_point: 2 - } - top: "dummy_slice_1_0" - top: "dummy_slice_1_1" - top: "dummy_slice_1_2" -} -layer{ - type: "Sigmoid" - name: "alter_sliced_split" - bottom: "dummy_slice_1_2" - top: "dummy_slice_1_2" -} -layer{ - type: "Concat" - name: "dummy_concat" - bottom: "dummy_slice_0_0" - bottom: "dummy_slice_1_1" - bottom: "dummy_slice_0_2" - top: "dummy_concat" -} -layer{ - type: "Reshape" - name: "dummy_reshape" - bottom: "dummy_concat" - reshape_param{ - shape{ - dim: 0 - dim: 1 - dim: 1 - dim: -1 - dim: 1 - } - axis: 1 - num_axes: 1 - } - top: "dummy_reshape" -} -layer{ - type: "Flatten" - name: "dummy_reshape_undo" - bottom: "dummy_reshape" - top: "dummy_reshape_undo" -} -layer{ - type: "Split" - name: "output" - bottom: "dummy_reshape_undo" - top: "output" -} \ No newline at end of file diff --git a/testdata/dnn/layers/shared_weights.caffemodel b/testdata/dnn/layers/shared_weights.caffemodel deleted file mode 100644 index 2bd3d417a..000000000 Binary files a/testdata/dnn/layers/shared_weights.caffemodel and /dev/null differ diff --git a/testdata/dnn/layers/shared_weights.prototxt b/testdata/dnn/layers/shared_weights.prototxt deleted file mode 100644 index d11a891d0..000000000 --- a/testdata/dnn/layers/shared_weights.prototxt +++ /dev/null @@ -1,113 +0,0 @@ -name: "TestSharedWeights" - -input: "input_1" -input_shape { dim: 1 dim: 1 dim: 2 dim: 2} - -input: "input_2" -input_shape { dim: 1 dim: 1 dim: 2 dim: 2} - -layer { - name: "conv" - type: "Convolution" - bottom: "input_1" - top: "conv_1" - - convolution_param - { - group: 1 - num_output: 1 - - pad_h: 0 - pad_w: 0 - kernel_h: 1 - kernel_w: 1 - stride_h: 1 - stride_w: 1 - - weight_filler{ - type: 'constant' - value: 1 - } - bias_filler { - type: 'constant' - value: 0 - } - } -} - -layer { - name: "conv" - type: "Convolution" - bottom: "input_2" - top: "conv_2" - - convolution_param - { - group: 1 - num_output: 1 - - pad_h: 0 - pad_w: 0 - kernel_h: 1 - kernel_w: 1 - stride_h: 1 - stride_w: 1 - - weight_filler{ - type: 'constant' - value: 1 - } - bias_filler { - type: 'constant' - value: 0 - } - } -} - - -layer { - type: "InnerProduct" - name: "sum" - bottom: "conv_1" - top: "sum_1" - inner_product_param { - num_output: 1 - - weight_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - } -} - -layer { - type: "InnerProduct" - name: "sum" - bottom: "conv_2" - top: "sum_2" - inner_product_param { - num_output: 1 - - weight_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - } -} - -layer { - type: "Concat" - name: "concat" - bottom: "sum_1" - bottom: "sum_2" - top: "sum" -} - diff --git a/testdata/dnn/opencv_face_detector.prototxt b/testdata/dnn/opencv_face_detector.prototxt deleted file mode 100644 index a12851566..000000000 --- a/testdata/dnn/opencv_face_detector.prototxt +++ /dev/null @@ -1,1790 +0,0 @@ -input: "data" -input_shape { - dim: 1 - dim: 3 - dim: 300 - dim: 300 -} - -layer { - name: "data_bn" - type: "BatchNorm" - bottom: "data" - top: "data_bn" - param { - lr_mult: 0.0 - } - param { - lr_mult: 0.0 - } - param { - lr_mult: 0.0 - } -} -layer { - name: "data_scale" - type: "Scale" - bottom: "data_bn" - top: "data_bn" - param { - lr_mult: 1.0 - decay_mult: 1.0 - } - param { - lr_mult: 2.0 - decay_mult: 1.0 - } - scale_param { - bias_term: true - } -} -layer { - name: "conv1_h" - type: "Convolution" - bottom: "data_bn" - top: "conv1_h" - param { - lr_mult: 1.0 - decay_mult: 1.0 - } - param { - lr_mult: 2.0 - decay_mult: 1.0 - } - convolution_param { - num_output: 32 - pad: 3 - kernel_size: 7 - stride: 2 - weight_filler { - type: "msra" - variance_norm: FAN_OUT - } - bias_filler { - type: "constant" - value: 0.0 - } - } -} -layer { - name: "conv1_bn_h" - type: "BatchNorm" - bottom: "conv1_h" - top: "conv1_h" - param { - lr_mult: 0.0 - } - param { - lr_mult: 0.0 - } - param { - lr_mult: 0.0 - } -} -layer { - name: "conv1_scale_h" - type: "Scale" - bottom: "conv1_h" - top: "conv1_h" - param { - lr_mult: 1.0 - decay_mult: 1.0 - } - param { - lr_mult: 2.0 - decay_mult: 1.0 - } - scale_param { - bias_term: true - } -} -layer { - name: "conv1_relu" - type: "ReLU" - bottom: "conv1_h" - top: "conv1_h" -} -layer { - name: "conv1_pool" - type: "Pooling" - bottom: "conv1_h" - top: "conv1_pool" - pooling_param { - kernel_size: 3 - stride: 2 - } -} -layer { - name: "layer_64_1_conv1_h" - type: "Convolution" - bottom: "conv1_pool" - top: "layer_64_1_conv1_h" - param { - lr_mult: 1.0 - decay_mult: 1.0 - } - convolution_param { - num_output: 32 - bias_term: false - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } - } -} -layer { - name: "layer_64_1_bn2_h" - type: "BatchNorm" - bottom: "layer_64_1_conv1_h" - top: "layer_64_1_conv1_h" - param { - lr_mult: 0.0 - } - param { - lr_mult: 0.0 - } - param { - lr_mult: 0.0 - } -} -layer { - name: "layer_64_1_scale2_h" - type: "Scale" - bottom: "layer_64_1_conv1_h" - top: "layer_64_1_conv1_h" - param { - lr_mult: 1.0 - decay_mult: 1.0 - } - param { - lr_mult: 2.0 - decay_mult: 1.0 - } - scale_param { - bias_term: true - } -} -layer { - name: "layer_64_1_relu2" - type: "ReLU" - bottom: "layer_64_1_conv1_h" - top: "layer_64_1_conv1_h" -} -layer { - name: "layer_64_1_conv2_h" - type: "Convolution" - bottom: "layer_64_1_conv1_h" - top: "layer_64_1_conv2_h" - param { - lr_mult: 1.0 - decay_mult: 1.0 - } - convolution_param { - num_output: 32 - bias_term: false - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } - } -} -layer { - name: "layer_64_1_sum" - type: "Eltwise" - bottom: "layer_64_1_conv2_h" - bottom: "conv1_pool" - top: "layer_64_1_sum" -} -layer { - name: "layer_128_1_bn1_h" - type: "BatchNorm" - bottom: "layer_64_1_sum" - top: "layer_128_1_bn1_h" - param { - lr_mult: 0.0 - } - param { - lr_mult: 0.0 - } - param { - lr_mult: 0.0 - } -} -layer { - name: "layer_128_1_scale1_h" - type: "Scale" - bottom: "layer_128_1_bn1_h" - top: "layer_128_1_bn1_h" - param { - lr_mult: 1.0 - decay_mult: 1.0 - } - param { - lr_mult: 2.0 - decay_mult: 1.0 - } - scale_param { - bias_term: true - } -} -layer { - name: "layer_128_1_relu1" - type: "ReLU" - bottom: "layer_128_1_bn1_h" - top: "layer_128_1_bn1_h" -} -layer { - name: "layer_128_1_conv1_h" - type: "Convolution" - bottom: "layer_128_1_bn1_h" - top: "layer_128_1_conv1_h" - param { - lr_mult: 1.0 - decay_mult: 1.0 - } - convolution_param { - num_output: 128 - bias_term: false - pad: 1 - kernel_size: 3 - stride: 2 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } - } -} -layer { - name: "layer_128_1_bn2" - type: "BatchNorm" - bottom: "layer_128_1_conv1_h" - top: "layer_128_1_conv1_h" - param { - lr_mult: 0.0 - } - param { - lr_mult: 0.0 - } - param { - lr_mult: 0.0 - } -} -layer { - name: "layer_128_1_scale2" - type: "Scale" - bottom: "layer_128_1_conv1_h" - top: "layer_128_1_conv1_h" - param { - lr_mult: 1.0 - decay_mult: 1.0 - } - param { - lr_mult: 2.0 - decay_mult: 1.0 - } - scale_param { - bias_term: true - } -} -layer { - name: "layer_128_1_relu2" - type: "ReLU" - bottom: "layer_128_1_conv1_h" - top: "layer_128_1_conv1_h" -} -layer { - name: "layer_128_1_conv2" - type: "Convolution" - bottom: "layer_128_1_conv1_h" - top: "layer_128_1_conv2" - param { - lr_mult: 1.0 - decay_mult: 1.0 - } - convolution_param { - num_output: 128 - bias_term: false - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } - } -} -layer { - name: "layer_128_1_conv_expand_h" - type: "Convolution" - bottom: "layer_128_1_bn1_h" - top: "layer_128_1_conv_expand_h" - param { - lr_mult: 1.0 - decay_mult: 1.0 - } - convolution_param { - num_output: 128 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 2 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } - } -} -layer { - name: "layer_128_1_sum" - type: "Eltwise" - bottom: "layer_128_1_conv2" - bottom: "layer_128_1_conv_expand_h" - top: "layer_128_1_sum" -} -layer { - name: "layer_256_1_bn1" - type: "BatchNorm" - bottom: "layer_128_1_sum" - top: "layer_256_1_bn1" - param { - lr_mult: 0.0 - } - param { - lr_mult: 0.0 - } - param { - lr_mult: 0.0 - } -} -layer { - name: "layer_256_1_scale1" - type: "Scale" - bottom: "layer_256_1_bn1" - top: "layer_256_1_bn1" - param { - lr_mult: 1.0 - decay_mult: 1.0 - } - param { - lr_mult: 2.0 - decay_mult: 1.0 - } - scale_param { - bias_term: true - } -} -layer { - name: "layer_256_1_relu1" - type: "ReLU" - bottom: "layer_256_1_bn1" - top: "layer_256_1_bn1" -} -layer { - name: "layer_256_1_conv1" - type: "Convolution" - bottom: "layer_256_1_bn1" - top: "layer_256_1_conv1" - param { - lr_mult: 1.0 - decay_mult: 1.0 - } - convolution_param { - num_output: 256 - bias_term: false - pad: 1 - kernel_size: 3 - stride: 2 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } - } -} -layer { - name: "layer_256_1_bn2" - type: "BatchNorm" - bottom: "layer_256_1_conv1" - top: "layer_256_1_conv1" - param { - lr_mult: 0.0 - } - param { - lr_mult: 0.0 - } - param { - lr_mult: 0.0 - } -} -layer { - name: "layer_256_1_scale2" - type: "Scale" - bottom: "layer_256_1_conv1" - top: "layer_256_1_conv1" - param { - lr_mult: 1.0 - decay_mult: 1.0 - } - param { - lr_mult: 2.0 - decay_mult: 1.0 - } - scale_param { - bias_term: true - } -} -layer { - name: "layer_256_1_relu2" - type: "ReLU" - bottom: "layer_256_1_conv1" - top: "layer_256_1_conv1" -} -layer { - name: "layer_256_1_conv2" - type: "Convolution" - bottom: "layer_256_1_conv1" - top: "layer_256_1_conv2" - param { - lr_mult: 1.0 - decay_mult: 1.0 - } - convolution_param { - num_output: 256 - bias_term: false - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } - } -} -layer { - name: "layer_256_1_conv_expand" - type: "Convolution" - bottom: "layer_256_1_bn1" - top: "layer_256_1_conv_expand" - param { - lr_mult: 1.0 - decay_mult: 1.0 - } - convolution_param { - num_output: 256 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 2 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } - } -} -layer { - name: "layer_256_1_sum" - type: "Eltwise" - bottom: "layer_256_1_conv2" - bottom: "layer_256_1_conv_expand" - top: "layer_256_1_sum" -} -layer { - name: "layer_512_1_bn1" - type: "BatchNorm" - bottom: "layer_256_1_sum" - top: "layer_512_1_bn1" - param { - lr_mult: 0.0 - } - param { - lr_mult: 0.0 - } - param { - lr_mult: 0.0 - } -} -layer { - name: "layer_512_1_scale1" - type: "Scale" - bottom: "layer_512_1_bn1" - top: "layer_512_1_bn1" - param { - lr_mult: 1.0 - decay_mult: 1.0 - } - param { - lr_mult: 2.0 - decay_mult: 1.0 - } - scale_param { - bias_term: true - } -} -layer { - name: "layer_512_1_relu1" - type: "ReLU" - bottom: "layer_512_1_bn1" - top: "layer_512_1_bn1" -} -layer { - name: "layer_512_1_conv1_h" - type: "Convolution" - bottom: "layer_512_1_bn1" - top: "layer_512_1_conv1_h" - param { - lr_mult: 1.0 - decay_mult: 1.0 - } - convolution_param { - num_output: 128 - bias_term: false - pad: 1 - kernel_size: 3 - stride: 1 # 2 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } - } -} -layer { - name: "layer_512_1_bn2_h" - type: "BatchNorm" - bottom: "layer_512_1_conv1_h" - top: "layer_512_1_conv1_h" - param { - lr_mult: 0.0 - } - param { - lr_mult: 0.0 - } - param { - lr_mult: 0.0 - } -} -layer { - name: "layer_512_1_scale2_h" - type: "Scale" - bottom: "layer_512_1_conv1_h" - top: "layer_512_1_conv1_h" - param { - lr_mult: 1.0 - decay_mult: 1.0 - } - param { - lr_mult: 2.0 - decay_mult: 1.0 - } - scale_param { - bias_term: true - } -} -layer { - name: "layer_512_1_relu2" - type: "ReLU" - bottom: "layer_512_1_conv1_h" - top: "layer_512_1_conv1_h" -} -layer { - name: "layer_512_1_conv2_h" - type: "Convolution" - bottom: "layer_512_1_conv1_h" - top: "layer_512_1_conv2_h" - param { - lr_mult: 1.0 - decay_mult: 1.0 - } - convolution_param { - num_output: 256 - bias_term: false - pad: 2 # 1 - kernel_size: 3 - stride: 1 - dilation: 2 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } - } -} -layer { - name: "layer_512_1_conv_expand_h" - type: "Convolution" - bottom: "layer_512_1_bn1" - top: "layer_512_1_conv_expand_h" - param { - lr_mult: 1.0 - decay_mult: 1.0 - } - convolution_param { - num_output: 256 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 # 2 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } - } -} -layer { - name: "layer_512_1_sum" - type: "Eltwise" - bottom: "layer_512_1_conv2_h" - bottom: "layer_512_1_conv_expand_h" - top: "layer_512_1_sum" -} -layer { - name: "last_bn_h" - type: "BatchNorm" - bottom: "layer_512_1_sum" - top: "layer_512_1_sum" - param { - lr_mult: 0.0 - } - param { - lr_mult: 0.0 - } - param { - lr_mult: 0.0 - } -} -layer { - name: "last_scale_h" - type: "Scale" - bottom: "layer_512_1_sum" - top: "layer_512_1_sum" - param { - lr_mult: 1.0 - decay_mult: 1.0 - } - param { - lr_mult: 2.0 - decay_mult: 1.0 - } - scale_param { - bias_term: true - } -} -layer { - name: "last_relu" - type: "ReLU" - bottom: "layer_512_1_sum" - top: "fc7" -} - -layer { - name: "conv6_1_h" - type: "Convolution" - bottom: "fc7" - top: "conv6_1_h" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv6_1_relu" - type: "ReLU" - bottom: "conv6_1_h" - top: "conv6_1_h" -} -layer { - name: "conv6_2_h" - type: "Convolution" - bottom: "conv6_1_h" - top: "conv6_2_h" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - stride: 2 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv6_2_relu" - type: "ReLU" - bottom: "conv6_2_h" - top: "conv6_2_h" -} -layer { - name: "conv7_1_h" - type: "Convolution" - bottom: "conv6_2_h" - top: "conv7_1_h" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv7_1_relu" - type: "ReLU" - bottom: "conv7_1_h" - top: "conv7_1_h" -} -layer { - name: "conv7_2_h" - type: "Convolution" - bottom: "conv7_1_h" - top: "conv7_2_h" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - stride: 2 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv7_2_relu" - type: "ReLU" - bottom: "conv7_2_h" - top: "conv7_2_h" -} -layer { - name: "conv8_1_h" - type: "Convolution" - bottom: "conv7_2_h" - top: "conv8_1_h" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv8_1_relu" - type: "ReLU" - bottom: "conv8_1_h" - top: "conv8_1_h" -} -layer { - name: "conv8_2_h" - type: "Convolution" - bottom: "conv8_1_h" - top: "conv8_2_h" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv8_2_relu" - type: "ReLU" - bottom: "conv8_2_h" - top: "conv8_2_h" -} -layer { - name: "conv9_1_h" - type: "Convolution" - bottom: "conv8_2_h" - top: "conv9_1_h" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv9_1_relu" - type: "ReLU" - bottom: "conv9_1_h" - top: "conv9_1_h" -} -layer { - name: "conv9_2_h" - type: "Convolution" - bottom: "conv9_1_h" - top: "conv9_2_h" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv9_2_relu" - type: "ReLU" - bottom: "conv9_2_h" - top: "conv9_2_h" -} -layer { - name: "conv4_3_norm" - type: "Normalize" - bottom: "layer_256_1_bn1" - top: "conv4_3_norm" - norm_param { - across_spatial: false - scale_filler { - type: "constant" - value: 20 - } - channel_shared: false - } -} -layer { - name: "conv4_3_norm_mbox_loc" - type: "Convolution" - bottom: "conv4_3_norm" - top: "conv4_3_norm_mbox_loc" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 16 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv4_3_norm_mbox_loc_perm" - type: "Permute" - bottom: "conv4_3_norm_mbox_loc" - top: "conv4_3_norm_mbox_loc_perm" - permute_param { - order: 0 - order: 2 - order: 3 - order: 1 - } -} -layer { - name: "conv4_3_norm_mbox_loc_flat" - type: "Flatten" - bottom: "conv4_3_norm_mbox_loc_perm" - top: "conv4_3_norm_mbox_loc_flat" - flatten_param { - axis: 1 - } -} -layer { - name: "conv4_3_norm_mbox_conf" - type: "Convolution" - bottom: "conv4_3_norm" - top: "conv4_3_norm_mbox_conf" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 8 # 84 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv4_3_norm_mbox_conf_perm" - type: "Permute" - bottom: "conv4_3_norm_mbox_conf" - top: "conv4_3_norm_mbox_conf_perm" - permute_param { - order: 0 - order: 2 - order: 3 - order: 1 - } -} -layer { - name: "conv4_3_norm_mbox_conf_flat" - type: "Flatten" - bottom: "conv4_3_norm_mbox_conf_perm" - top: "conv4_3_norm_mbox_conf_flat" - flatten_param { - axis: 1 - } -} -layer { - name: "conv4_3_norm_mbox_priorbox" - type: "PriorBox" - bottom: "conv4_3_norm" - bottom: "data" - top: "conv4_3_norm_mbox_priorbox" - prior_box_param { - min_size: 30.0 - max_size: 60.0 - aspect_ratio: 2 - flip: true - clip: false - variance: 0.1 - variance: 0.1 - variance: 0.2 - variance: 0.2 - step: 8 - offset: 0.5 - } -} -layer { - name: "fc7_mbox_loc" - type: "Convolution" - bottom: "fc7" - top: "fc7_mbox_loc" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 24 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "fc7_mbox_loc_perm" - type: "Permute" - bottom: "fc7_mbox_loc" - top: "fc7_mbox_loc_perm" - permute_param { - order: 0 - order: 2 - order: 3 - order: 1 - } -} -layer { - name: "fc7_mbox_loc_flat" - type: "Flatten" - bottom: "fc7_mbox_loc_perm" - top: "fc7_mbox_loc_flat" - flatten_param { - axis: 1 - } -} -layer { - name: "fc7_mbox_conf" - type: "Convolution" - bottom: "fc7" - top: "fc7_mbox_conf" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 12 # 126 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "fc7_mbox_conf_perm" - type: "Permute" - bottom: "fc7_mbox_conf" - top: "fc7_mbox_conf_perm" - permute_param { - order: 0 - order: 2 - order: 3 - order: 1 - } -} -layer { - name: "fc7_mbox_conf_flat" - type: "Flatten" - bottom: "fc7_mbox_conf_perm" - top: "fc7_mbox_conf_flat" - flatten_param { - axis: 1 - } -} -layer { - name: "fc7_mbox_priorbox" - type: "PriorBox" - bottom: "fc7" - bottom: "data" - top: "fc7_mbox_priorbox" - prior_box_param { - min_size: 60.0 - max_size: 111.0 - aspect_ratio: 2 - aspect_ratio: 3 - flip: true - clip: false - variance: 0.1 - variance: 0.1 - variance: 0.2 - variance: 0.2 - step: 16 - offset: 0.5 - } -} -layer { - name: "conv6_2_mbox_loc" - type: "Convolution" - bottom: "conv6_2_h" - top: "conv6_2_mbox_loc" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 24 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv6_2_mbox_loc_perm" - type: "Permute" - bottom: "conv6_2_mbox_loc" - top: "conv6_2_mbox_loc_perm" - permute_param { - order: 0 - order: 2 - order: 3 - order: 1 - } -} -layer { - name: "conv6_2_mbox_loc_flat" - type: "Flatten" - bottom: "conv6_2_mbox_loc_perm" - top: "conv6_2_mbox_loc_flat" - flatten_param { - axis: 1 - } -} -layer { - name: "conv6_2_mbox_conf" - type: "Convolution" - bottom: "conv6_2_h" - top: "conv6_2_mbox_conf" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 12 # 126 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv6_2_mbox_conf_perm" - type: "Permute" - bottom: "conv6_2_mbox_conf" - top: "conv6_2_mbox_conf_perm" - permute_param { - order: 0 - order: 2 - order: 3 - order: 1 - } -} -layer { - name: "conv6_2_mbox_conf_flat" - type: "Flatten" - bottom: "conv6_2_mbox_conf_perm" - top: "conv6_2_mbox_conf_flat" - flatten_param { - axis: 1 - } -} -layer { - name: "conv6_2_mbox_priorbox" - type: "PriorBox" - bottom: "conv6_2_h" - bottom: "data" - top: "conv6_2_mbox_priorbox" - prior_box_param { - min_size: 111.0 - max_size: 162.0 - aspect_ratio: 2 - aspect_ratio: 3 - flip: true - clip: false - variance: 0.1 - variance: 0.1 - variance: 0.2 - variance: 0.2 - step: 32 - offset: 0.5 - } -} -layer { - name: "conv7_2_mbox_loc" - type: "Convolution" - bottom: "conv7_2_h" - top: "conv7_2_mbox_loc" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 24 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv7_2_mbox_loc_perm" - type: "Permute" - bottom: "conv7_2_mbox_loc" - top: "conv7_2_mbox_loc_perm" - permute_param { - order: 0 - order: 2 - order: 3 - order: 1 - } -} -layer { - name: "conv7_2_mbox_loc_flat" - type: "Flatten" - bottom: "conv7_2_mbox_loc_perm" - top: "conv7_2_mbox_loc_flat" - flatten_param { - axis: 1 - } -} -layer { - name: "conv7_2_mbox_conf" - type: "Convolution" - bottom: "conv7_2_h" - top: "conv7_2_mbox_conf" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 12 # 126 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv7_2_mbox_conf_perm" - type: "Permute" - bottom: "conv7_2_mbox_conf" - top: "conv7_2_mbox_conf_perm" - permute_param { - order: 0 - order: 2 - order: 3 - order: 1 - } -} -layer { - name: "conv7_2_mbox_conf_flat" - type: "Flatten" - bottom: "conv7_2_mbox_conf_perm" - top: "conv7_2_mbox_conf_flat" - flatten_param { - axis: 1 - } -} -layer { - name: "conv7_2_mbox_priorbox" - type: "PriorBox" - bottom: "conv7_2_h" - bottom: "data" - top: "conv7_2_mbox_priorbox" - prior_box_param { - min_size: 162.0 - max_size: 213.0 - aspect_ratio: 2 - aspect_ratio: 3 - flip: true - clip: false - variance: 0.1 - variance: 0.1 - variance: 0.2 - variance: 0.2 - step: 64 - offset: 0.5 - } -} -layer { - name: "conv8_2_mbox_loc" - type: "Convolution" - bottom: "conv8_2_h" - top: "conv8_2_mbox_loc" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 16 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv8_2_mbox_loc_perm" - type: "Permute" - bottom: "conv8_2_mbox_loc" - top: "conv8_2_mbox_loc_perm" - permute_param { - order: 0 - order: 2 - order: 3 - order: 1 - } -} -layer { - name: "conv8_2_mbox_loc_flat" - type: "Flatten" - bottom: "conv8_2_mbox_loc_perm" - top: "conv8_2_mbox_loc_flat" - flatten_param { - axis: 1 - } -} -layer { - name: "conv8_2_mbox_conf" - type: "Convolution" - bottom: "conv8_2_h" - top: "conv8_2_mbox_conf" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 8 # 84 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv8_2_mbox_conf_perm" - type: "Permute" - bottom: "conv8_2_mbox_conf" - top: "conv8_2_mbox_conf_perm" - permute_param { - order: 0 - order: 2 - order: 3 - order: 1 - } -} -layer { - name: "conv8_2_mbox_conf_flat" - type: "Flatten" - bottom: "conv8_2_mbox_conf_perm" - top: "conv8_2_mbox_conf_flat" - flatten_param { - axis: 1 - } -} -layer { - name: "conv8_2_mbox_priorbox" - type: "PriorBox" - bottom: "conv8_2_h" - bottom: "data" - top: "conv8_2_mbox_priorbox" - prior_box_param { - min_size: 213.0 - max_size: 264.0 - aspect_ratio: 2 - flip: true - clip: false - variance: 0.1 - variance: 0.1 - variance: 0.2 - variance: 0.2 - step: 100 - offset: 0.5 - } -} -layer { - name: "conv9_2_mbox_loc" - type: "Convolution" - bottom: "conv9_2_h" - top: "conv9_2_mbox_loc" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 16 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv9_2_mbox_loc_perm" - type: "Permute" - bottom: "conv9_2_mbox_loc" - top: "conv9_2_mbox_loc_perm" - permute_param { - order: 0 - order: 2 - order: 3 - order: 1 - } -} -layer { - name: "conv9_2_mbox_loc_flat" - type: "Flatten" - bottom: "conv9_2_mbox_loc_perm" - top: "conv9_2_mbox_loc_flat" - flatten_param { - axis: 1 - } -} -layer { - name: "conv9_2_mbox_conf" - type: "Convolution" - bottom: "conv9_2_h" - top: "conv9_2_mbox_conf" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 8 # 84 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv9_2_mbox_conf_perm" - type: "Permute" - bottom: "conv9_2_mbox_conf" - top: "conv9_2_mbox_conf_perm" - permute_param { - order: 0 - order: 2 - order: 3 - order: 1 - } -} -layer { - name: "conv9_2_mbox_conf_flat" - type: "Flatten" - bottom: "conv9_2_mbox_conf_perm" - top: "conv9_2_mbox_conf_flat" - flatten_param { - axis: 1 - } -} -layer { - name: "conv9_2_mbox_priorbox" - type: "PriorBox" - bottom: "conv9_2_h" - bottom: "data" - top: "conv9_2_mbox_priorbox" - prior_box_param { - min_size: 264.0 - max_size: 315.0 - aspect_ratio: 2 - flip: true - clip: false - variance: 0.1 - variance: 0.1 - variance: 0.2 - variance: 0.2 - step: 300 - offset: 0.5 - } -} -layer { - name: "mbox_loc" - type: "Concat" - bottom: "conv4_3_norm_mbox_loc_flat" - bottom: "fc7_mbox_loc_flat" - bottom: "conv6_2_mbox_loc_flat" - bottom: "conv7_2_mbox_loc_flat" - bottom: "conv8_2_mbox_loc_flat" - bottom: "conv9_2_mbox_loc_flat" - top: "mbox_loc" - concat_param { - axis: 1 - } -} -layer { - name: "mbox_conf" - type: "Concat" - bottom: "conv4_3_norm_mbox_conf_flat" - bottom: "fc7_mbox_conf_flat" - bottom: "conv6_2_mbox_conf_flat" - bottom: "conv7_2_mbox_conf_flat" - bottom: "conv8_2_mbox_conf_flat" - bottom: "conv9_2_mbox_conf_flat" - top: "mbox_conf" - concat_param { - axis: 1 - } -} -layer { - name: "mbox_priorbox" - type: "Concat" - bottom: "conv4_3_norm_mbox_priorbox" - bottom: "fc7_mbox_priorbox" - bottom: "conv6_2_mbox_priorbox" - bottom: "conv7_2_mbox_priorbox" - bottom: "conv8_2_mbox_priorbox" - bottom: "conv9_2_mbox_priorbox" - top: "mbox_priorbox" - concat_param { - axis: 2 - } -} - -layer { - name: "mbox_conf_reshape" - type: "Reshape" - bottom: "mbox_conf" - top: "mbox_conf_reshape" - reshape_param { - shape { - dim: 0 - dim: -1 - dim: 2 - } - } -} -layer { - name: "mbox_conf_softmax" - type: "Softmax" - bottom: "mbox_conf_reshape" - top: "mbox_conf_softmax" - softmax_param { - axis: 2 - } -} -layer { - name: "mbox_conf_flatten" - type: "Flatten" - bottom: "mbox_conf_softmax" - top: "mbox_conf_flatten" - flatten_param { - axis: 1 - } -} - -layer { - name: "detection_out" - type: "DetectionOutput" - bottom: "mbox_loc" - bottom: "mbox_conf_flatten" - bottom: "mbox_priorbox" - top: "detection_out" - include { - phase: TEST - } - detection_output_param { - num_classes: 2 - share_location: true - background_label_id: 0 - nms_param { - nms_threshold: 0.45 - top_k: 400 - } - code_type: CENTER_SIZE - keep_top_k: 200 - confidence_threshold: 0.01 - clip: 1 - } -} diff --git a/testdata/dnn/openpose_pose_coco.prototxt b/testdata/dnn/openpose_pose_coco.prototxt deleted file mode 100644 index a8e0bfe10..000000000 --- a/testdata/dnn/openpose_pose_coco.prototxt +++ /dev/null @@ -1,2977 +0,0 @@ -# source: https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/models/pose/coco/pose_deploy_linevec.prototxt -input: "image" -input_dim: 1 -input_dim: 3 -input_dim: 368 -input_dim: 368 -layer { - name: "conv1_1" - type: "Convolution" - bottom: "image" - top: "conv1_1" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 64 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu1_1" - type: "ReLU" - bottom: "conv1_1" - top: "conv1_1" -} -layer { - name: "conv1_2" - type: "Convolution" - bottom: "conv1_1" - top: "conv1_2" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 64 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu1_2" - type: "ReLU" - bottom: "conv1_2" - top: "conv1_2" -} -layer { - name: "pool1_stage1" - type: "Pooling" - bottom: "conv1_2" - top: "pool1_stage1" - pooling_param { - pool: MAX - kernel_size: 2 - stride: 2 - } -} -layer { - name: "conv2_1" - type: "Convolution" - bottom: "pool1_stage1" - top: "conv2_1" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu2_1" - type: "ReLU" - bottom: "conv2_1" - top: "conv2_1" -} -layer { - name: "conv2_2" - type: "Convolution" - bottom: "conv2_1" - top: "conv2_2" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu2_2" - type: "ReLU" - bottom: "conv2_2" - top: "conv2_2" -} -layer { - name: "pool2_stage1" - type: "Pooling" - bottom: "conv2_2" - top: "pool2_stage1" - pooling_param { - pool: MAX - kernel_size: 2 - stride: 2 - } -} -layer { - name: "conv3_1" - type: "Convolution" - bottom: "pool2_stage1" - top: "conv3_1" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu3_1" - type: "ReLU" - bottom: "conv3_1" - top: "conv3_1" -} -layer { - name: "conv3_2" - type: "Convolution" - bottom: "conv3_1" - top: "conv3_2" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu3_2" - type: "ReLU" - bottom: "conv3_2" - top: "conv3_2" -} -layer { - name: "conv3_3" - type: "Convolution" - bottom: "conv3_2" - top: "conv3_3" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu3_3" - type: "ReLU" - bottom: "conv3_3" - top: "conv3_3" -} -layer { - name: "conv3_4" - type: "Convolution" - bottom: "conv3_3" - top: "conv3_4" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu3_4" - type: "ReLU" - bottom: "conv3_4" - top: "conv3_4" -} -layer { - name: "pool3_stage1" - type: "Pooling" - bottom: "conv3_4" - top: "pool3_stage1" - pooling_param { - pool: MAX - kernel_size: 2 - stride: 2 - } -} -layer { - name: "conv4_1" - type: "Convolution" - bottom: "pool3_stage1" - top: "conv4_1" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 512 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu4_1" - type: "ReLU" - bottom: "conv4_1" - top: "conv4_1" -} -layer { - name: "conv4_2" - type: "Convolution" - bottom: "conv4_1" - top: "conv4_2" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 512 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu4_2" - type: "ReLU" - bottom: "conv4_2" - top: "conv4_2" -} -layer { - name: "conv4_3_CPM" - type: "Convolution" - bottom: "conv4_2" - top: "conv4_3_CPM" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu4_3_CPM" - type: "ReLU" - bottom: "conv4_3_CPM" - top: "conv4_3_CPM" -} -layer { - name: "conv4_4_CPM" - type: "Convolution" - bottom: "conv4_3_CPM" - top: "conv4_4_CPM" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu4_4_CPM" - type: "ReLU" - bottom: "conv4_4_CPM" - top: "conv4_4_CPM" -} -layer { - name: "conv5_1_CPM_L1" - type: "Convolution" - bottom: "conv4_4_CPM" - top: "conv5_1_CPM_L1" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu5_1_CPM_L1" - type: "ReLU" - bottom: "conv5_1_CPM_L1" - top: "conv5_1_CPM_L1" -} -layer { - name: "conv5_1_CPM_L2" - type: "Convolution" - bottom: "conv4_4_CPM" - top: "conv5_1_CPM_L2" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu5_1_CPM_L2" - type: "ReLU" - bottom: "conv5_1_CPM_L2" - top: "conv5_1_CPM_L2" -} -layer { - name: "conv5_2_CPM_L1" - type: "Convolution" - bottom: "conv5_1_CPM_L1" - top: "conv5_2_CPM_L1" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu5_2_CPM_L1" - type: "ReLU" - bottom: "conv5_2_CPM_L1" - top: "conv5_2_CPM_L1" -} -layer { - name: "conv5_2_CPM_L2" - type: "Convolution" - bottom: "conv5_1_CPM_L2" - top: "conv5_2_CPM_L2" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu5_2_CPM_L2" - type: "ReLU" - bottom: "conv5_2_CPM_L2" - top: "conv5_2_CPM_L2" -} -layer { - name: "conv5_3_CPM_L1" - type: "Convolution" - bottom: "conv5_2_CPM_L1" - top: "conv5_3_CPM_L1" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu5_3_CPM_L1" - type: "ReLU" - bottom: "conv5_3_CPM_L1" - top: "conv5_3_CPM_L1" -} -layer { - name: "conv5_3_CPM_L2" - type: "Convolution" - bottom: "conv5_2_CPM_L2" - top: "conv5_3_CPM_L2" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu5_3_CPM_L2" - type: "ReLU" - bottom: "conv5_3_CPM_L2" - top: "conv5_3_CPM_L2" -} -layer { - name: "conv5_4_CPM_L1" - type: "Convolution" - bottom: "conv5_3_CPM_L1" - top: "conv5_4_CPM_L1" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 512 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu5_4_CPM_L1" - type: "ReLU" - bottom: "conv5_4_CPM_L1" - top: "conv5_4_CPM_L1" -} -layer { - name: "conv5_4_CPM_L2" - type: "Convolution" - bottom: "conv5_3_CPM_L2" - top: "conv5_4_CPM_L2" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 512 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu5_4_CPM_L2" - type: "ReLU" - bottom: "conv5_4_CPM_L2" - top: "conv5_4_CPM_L2" -} -layer { - name: "conv5_5_CPM_L1" - type: "Convolution" - bottom: "conv5_4_CPM_L1" - top: "conv5_5_CPM_L1" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 38 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "conv5_5_CPM_L2" - type: "Convolution" - bottom: "conv5_4_CPM_L2" - top: "conv5_5_CPM_L2" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 19 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "concat_stage2" - type: "Concat" - bottom: "conv5_5_CPM_L1" - bottom: "conv5_5_CPM_L2" - bottom: "conv4_4_CPM" - top: "concat_stage2" - concat_param { - axis: 1 - } -} -layer { - name: "Mconv1_stage2_L1" - type: "Convolution" - bottom: "concat_stage2" - top: "Mconv1_stage2_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu1_stage2_L1" - type: "ReLU" - bottom: "Mconv1_stage2_L1" - top: "Mconv1_stage2_L1" -} -layer { - name: "Mconv1_stage2_L2" - type: "Convolution" - bottom: "concat_stage2" - top: "Mconv1_stage2_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu1_stage2_L2" - type: "ReLU" - bottom: "Mconv1_stage2_L2" - top: "Mconv1_stage2_L2" -} -layer { - name: "Mconv2_stage2_L1" - type: "Convolution" - bottom: "Mconv1_stage2_L1" - top: "Mconv2_stage2_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu2_stage2_L1" - type: "ReLU" - bottom: "Mconv2_stage2_L1" - top: "Mconv2_stage2_L1" -} -layer { - name: "Mconv2_stage2_L2" - type: "Convolution" - bottom: "Mconv1_stage2_L2" - top: "Mconv2_stage2_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu2_stage2_L2" - type: "ReLU" - bottom: "Mconv2_stage2_L2" - top: "Mconv2_stage2_L2" -} -layer { - name: "Mconv3_stage2_L1" - type: "Convolution" - bottom: "Mconv2_stage2_L1" - top: "Mconv3_stage2_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu3_stage2_L1" - type: "ReLU" - bottom: "Mconv3_stage2_L1" - top: "Mconv3_stage2_L1" -} -layer { - name: "Mconv3_stage2_L2" - type: "Convolution" - bottom: "Mconv2_stage2_L2" - top: "Mconv3_stage2_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu3_stage2_L2" - type: "ReLU" - bottom: "Mconv3_stage2_L2" - top: "Mconv3_stage2_L2" -} -layer { - name: "Mconv4_stage2_L1" - type: "Convolution" - bottom: "Mconv3_stage2_L1" - top: "Mconv4_stage2_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu4_stage2_L1" - type: "ReLU" - bottom: "Mconv4_stage2_L1" - top: "Mconv4_stage2_L1" -} -layer { - name: "Mconv4_stage2_L2" - type: "Convolution" - bottom: "Mconv3_stage2_L2" - top: "Mconv4_stage2_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu4_stage2_L2" - type: "ReLU" - bottom: "Mconv4_stage2_L2" - top: "Mconv4_stage2_L2" -} -layer { - name: "Mconv5_stage2_L1" - type: "Convolution" - bottom: "Mconv4_stage2_L1" - top: "Mconv5_stage2_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu5_stage2_L1" - type: "ReLU" - bottom: "Mconv5_stage2_L1" - top: "Mconv5_stage2_L1" -} -layer { - name: "Mconv5_stage2_L2" - type: "Convolution" - bottom: "Mconv4_stage2_L2" - top: "Mconv5_stage2_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu5_stage2_L2" - type: "ReLU" - bottom: "Mconv5_stage2_L2" - top: "Mconv5_stage2_L2" -} -layer { - name: "Mconv6_stage2_L1" - type: "Convolution" - bottom: "Mconv5_stage2_L1" - top: "Mconv6_stage2_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu6_stage2_L1" - type: "ReLU" - bottom: "Mconv6_stage2_L1" - top: "Mconv6_stage2_L1" -} -layer { - name: "Mconv6_stage2_L2" - type: "Convolution" - bottom: "Mconv5_stage2_L2" - top: "Mconv6_stage2_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu6_stage2_L2" - type: "ReLU" - bottom: "Mconv6_stage2_L2" - top: "Mconv6_stage2_L2" -} -layer { - name: "Mconv7_stage2_L1" - type: "Convolution" - bottom: "Mconv6_stage2_L1" - top: "Mconv7_stage2_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 38 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mconv7_stage2_L2" - type: "Convolution" - bottom: "Mconv6_stage2_L2" - top: "Mconv7_stage2_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 19 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "concat_stage3" - type: "Concat" - bottom: "Mconv7_stage2_L1" - bottom: "Mconv7_stage2_L2" - bottom: "conv4_4_CPM" - top: "concat_stage3" - concat_param { - axis: 1 - } -} -layer { - name: "Mconv1_stage3_L1" - type: "Convolution" - bottom: "concat_stage3" - top: "Mconv1_stage3_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu1_stage3_L1" - type: "ReLU" - bottom: "Mconv1_stage3_L1" - top: "Mconv1_stage3_L1" -} -layer { - name: "Mconv1_stage3_L2" - type: "Convolution" - bottom: "concat_stage3" - top: "Mconv1_stage3_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu1_stage3_L2" - type: "ReLU" - bottom: "Mconv1_stage3_L2" - top: "Mconv1_stage3_L2" -} -layer { - name: "Mconv2_stage3_L1" - type: "Convolution" - bottom: "Mconv1_stage3_L1" - top: "Mconv2_stage3_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu2_stage3_L1" - type: "ReLU" - bottom: "Mconv2_stage3_L1" - top: "Mconv2_stage3_L1" -} -layer { - name: "Mconv2_stage3_L2" - type: "Convolution" - bottom: "Mconv1_stage3_L2" - top: "Mconv2_stage3_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu2_stage3_L2" - type: "ReLU" - bottom: "Mconv2_stage3_L2" - top: "Mconv2_stage3_L2" -} -layer { - name: "Mconv3_stage3_L1" - type: "Convolution" - bottom: "Mconv2_stage3_L1" - top: "Mconv3_stage3_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu3_stage3_L1" - type: "ReLU" - bottom: "Mconv3_stage3_L1" - top: "Mconv3_stage3_L1" -} -layer { - name: "Mconv3_stage3_L2" - type: "Convolution" - bottom: "Mconv2_stage3_L2" - top: "Mconv3_stage3_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu3_stage3_L2" - type: "ReLU" - bottom: "Mconv3_stage3_L2" - top: "Mconv3_stage3_L2" -} -layer { - name: "Mconv4_stage3_L1" - type: "Convolution" - bottom: "Mconv3_stage3_L1" - top: "Mconv4_stage3_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu4_stage3_L1" - type: "ReLU" - bottom: "Mconv4_stage3_L1" - top: "Mconv4_stage3_L1" -} -layer { - name: "Mconv4_stage3_L2" - type: "Convolution" - bottom: "Mconv3_stage3_L2" - top: "Mconv4_stage3_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu4_stage3_L2" - type: "ReLU" - bottom: "Mconv4_stage3_L2" - top: "Mconv4_stage3_L2" -} -layer { - name: "Mconv5_stage3_L1" - type: "Convolution" - bottom: "Mconv4_stage3_L1" - top: "Mconv5_stage3_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu5_stage3_L1" - type: "ReLU" - bottom: "Mconv5_stage3_L1" - top: "Mconv5_stage3_L1" -} -layer { - name: "Mconv5_stage3_L2" - type: "Convolution" - bottom: "Mconv4_stage3_L2" - top: "Mconv5_stage3_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu5_stage3_L2" - type: "ReLU" - bottom: "Mconv5_stage3_L2" - top: "Mconv5_stage3_L2" -} -layer { - name: "Mconv6_stage3_L1" - type: "Convolution" - bottom: "Mconv5_stage3_L1" - top: "Mconv6_stage3_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu6_stage3_L1" - type: "ReLU" - bottom: "Mconv6_stage3_L1" - top: "Mconv6_stage3_L1" -} -layer { - name: "Mconv6_stage3_L2" - type: "Convolution" - bottom: "Mconv5_stage3_L2" - top: "Mconv6_stage3_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu6_stage3_L2" - type: "ReLU" - bottom: "Mconv6_stage3_L2" - top: "Mconv6_stage3_L2" -} -layer { - name: "Mconv7_stage3_L1" - type: "Convolution" - bottom: "Mconv6_stage3_L1" - top: "Mconv7_stage3_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 38 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mconv7_stage3_L2" - type: "Convolution" - bottom: "Mconv6_stage3_L2" - top: "Mconv7_stage3_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 19 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "concat_stage4" - type: "Concat" - bottom: "Mconv7_stage3_L1" - bottom: "Mconv7_stage3_L2" - bottom: "conv4_4_CPM" - top: "concat_stage4" - concat_param { - axis: 1 - } -} -layer { - name: "Mconv1_stage4_L1" - type: "Convolution" - bottom: "concat_stage4" - top: "Mconv1_stage4_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu1_stage4_L1" - type: "ReLU" - bottom: "Mconv1_stage4_L1" - top: "Mconv1_stage4_L1" -} -layer { - name: "Mconv1_stage4_L2" - type: "Convolution" - bottom: "concat_stage4" - top: "Mconv1_stage4_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu1_stage4_L2" - type: "ReLU" - bottom: "Mconv1_stage4_L2" - top: "Mconv1_stage4_L2" -} -layer { - name: "Mconv2_stage4_L1" - type: "Convolution" - bottom: "Mconv1_stage4_L1" - top: "Mconv2_stage4_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu2_stage4_L1" - type: "ReLU" - bottom: "Mconv2_stage4_L1" - top: "Mconv2_stage4_L1" -} -layer { - name: "Mconv2_stage4_L2" - type: "Convolution" - bottom: "Mconv1_stage4_L2" - top: "Mconv2_stage4_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu2_stage4_L2" - type: "ReLU" - bottom: "Mconv2_stage4_L2" - top: "Mconv2_stage4_L2" -} -layer { - name: "Mconv3_stage4_L1" - type: "Convolution" - bottom: "Mconv2_stage4_L1" - top: "Mconv3_stage4_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu3_stage4_L1" - type: "ReLU" - bottom: "Mconv3_stage4_L1" - top: "Mconv3_stage4_L1" -} -layer { - name: "Mconv3_stage4_L2" - type: "Convolution" - bottom: "Mconv2_stage4_L2" - top: "Mconv3_stage4_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu3_stage4_L2" - type: "ReLU" - bottom: "Mconv3_stage4_L2" - top: "Mconv3_stage4_L2" -} -layer { - name: "Mconv4_stage4_L1" - type: "Convolution" - bottom: "Mconv3_stage4_L1" - top: "Mconv4_stage4_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu4_stage4_L1" - type: "ReLU" - bottom: "Mconv4_stage4_L1" - top: "Mconv4_stage4_L1" -} -layer { - name: "Mconv4_stage4_L2" - type: "Convolution" - bottom: "Mconv3_stage4_L2" - top: "Mconv4_stage4_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu4_stage4_L2" - type: "ReLU" - bottom: "Mconv4_stage4_L2" - top: "Mconv4_stage4_L2" -} -layer { - name: "Mconv5_stage4_L1" - type: "Convolution" - bottom: "Mconv4_stage4_L1" - top: "Mconv5_stage4_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu5_stage4_L1" - type: "ReLU" - bottom: "Mconv5_stage4_L1" - top: "Mconv5_stage4_L1" -} -layer { - name: "Mconv5_stage4_L2" - type: "Convolution" - bottom: "Mconv4_stage4_L2" - top: "Mconv5_stage4_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu5_stage4_L2" - type: "ReLU" - bottom: "Mconv5_stage4_L2" - top: "Mconv5_stage4_L2" -} -layer { - name: "Mconv6_stage4_L1" - type: "Convolution" - bottom: "Mconv5_stage4_L1" - top: "Mconv6_stage4_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu6_stage4_L1" - type: "ReLU" - bottom: "Mconv6_stage4_L1" - top: "Mconv6_stage4_L1" -} -layer { - name: "Mconv6_stage4_L2" - type: "Convolution" - bottom: "Mconv5_stage4_L2" - top: "Mconv6_stage4_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu6_stage4_L2" - type: "ReLU" - bottom: "Mconv6_stage4_L2" - top: "Mconv6_stage4_L2" -} -layer { - name: "Mconv7_stage4_L1" - type: "Convolution" - bottom: "Mconv6_stage4_L1" - top: "Mconv7_stage4_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 38 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mconv7_stage4_L2" - type: "Convolution" - bottom: "Mconv6_stage4_L2" - top: "Mconv7_stage4_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 19 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "concat_stage5" - type: "Concat" - bottom: "Mconv7_stage4_L1" - bottom: "Mconv7_stage4_L2" - bottom: "conv4_4_CPM" - top: "concat_stage5" - concat_param { - axis: 1 - } -} -layer { - name: "Mconv1_stage5_L1" - type: "Convolution" - bottom: "concat_stage5" - top: "Mconv1_stage5_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu1_stage5_L1" - type: "ReLU" - bottom: "Mconv1_stage5_L1" - top: "Mconv1_stage5_L1" -} -layer { - name: "Mconv1_stage5_L2" - type: "Convolution" - bottom: "concat_stage5" - top: "Mconv1_stage5_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu1_stage5_L2" - type: "ReLU" - bottom: "Mconv1_stage5_L2" - top: "Mconv1_stage5_L2" -} -layer { - name: "Mconv2_stage5_L1" - type: "Convolution" - bottom: "Mconv1_stage5_L1" - top: "Mconv2_stage5_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu2_stage5_L1" - type: "ReLU" - bottom: "Mconv2_stage5_L1" - top: "Mconv2_stage5_L1" -} -layer { - name: "Mconv2_stage5_L2" - type: "Convolution" - bottom: "Mconv1_stage5_L2" - top: "Mconv2_stage5_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu2_stage5_L2" - type: "ReLU" - bottom: "Mconv2_stage5_L2" - top: "Mconv2_stage5_L2" -} -layer { - name: "Mconv3_stage5_L1" - type: "Convolution" - bottom: "Mconv2_stage5_L1" - top: "Mconv3_stage5_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu3_stage5_L1" - type: "ReLU" - bottom: "Mconv3_stage5_L1" - top: "Mconv3_stage5_L1" -} -layer { - name: "Mconv3_stage5_L2" - type: "Convolution" - bottom: "Mconv2_stage5_L2" - top: "Mconv3_stage5_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu3_stage5_L2" - type: "ReLU" - bottom: "Mconv3_stage5_L2" - top: "Mconv3_stage5_L2" -} -layer { - name: "Mconv4_stage5_L1" - type: "Convolution" - bottom: "Mconv3_stage5_L1" - top: "Mconv4_stage5_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu4_stage5_L1" - type: "ReLU" - bottom: "Mconv4_stage5_L1" - top: "Mconv4_stage5_L1" -} -layer { - name: "Mconv4_stage5_L2" - type: "Convolution" - bottom: "Mconv3_stage5_L2" - top: "Mconv4_stage5_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu4_stage5_L2" - type: "ReLU" - bottom: "Mconv4_stage5_L2" - top: "Mconv4_stage5_L2" -} -layer { - name: "Mconv5_stage5_L1" - type: "Convolution" - bottom: "Mconv4_stage5_L1" - top: "Mconv5_stage5_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu5_stage5_L1" - type: "ReLU" - bottom: "Mconv5_stage5_L1" - top: "Mconv5_stage5_L1" -} -layer { - name: "Mconv5_stage5_L2" - type: "Convolution" - bottom: "Mconv4_stage5_L2" - top: "Mconv5_stage5_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu5_stage5_L2" - type: "ReLU" - bottom: "Mconv5_stage5_L2" - top: "Mconv5_stage5_L2" -} -layer { - name: "Mconv6_stage5_L1" - type: "Convolution" - bottom: "Mconv5_stage5_L1" - top: "Mconv6_stage5_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu6_stage5_L1" - type: "ReLU" - bottom: "Mconv6_stage5_L1" - top: "Mconv6_stage5_L1" -} -layer { - name: "Mconv6_stage5_L2" - type: "Convolution" - bottom: "Mconv5_stage5_L2" - top: "Mconv6_stage5_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu6_stage5_L2" - type: "ReLU" - bottom: "Mconv6_stage5_L2" - top: "Mconv6_stage5_L2" -} -layer { - name: "Mconv7_stage5_L1" - type: "Convolution" - bottom: "Mconv6_stage5_L1" - top: "Mconv7_stage5_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 38 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mconv7_stage5_L2" - type: "Convolution" - bottom: "Mconv6_stage5_L2" - top: "Mconv7_stage5_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 19 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "concat_stage6" - type: "Concat" - bottom: "Mconv7_stage5_L1" - bottom: "Mconv7_stage5_L2" - bottom: "conv4_4_CPM" - top: "concat_stage6" - concat_param { - axis: 1 - } -} -# layer { -# name: "Mconv1_stage6_L1" -# type: "Convolution" -# bottom: "concat_stage6" -# top: "Mconv1_stage6_L1" -# param { -# lr_mult: 4.0 -# decay_mult: 1 -# } -# param { -# lr_mult: 8.0 -# decay_mult: 0 -# } -# convolution_param { -# num_output: 128 -# pad: 3 -# kernel_size: 7 -# weight_filler { -# type: "gaussian" -# std: 0.01 -# } -# bias_filler { -# type: "constant" -# } -# } -# } -# layer { -# name: "Mrelu1_stage6_L1" -# type: "ReLU" -# bottom: "Mconv1_stage6_L1" -# top: "Mconv1_stage6_L1" -# } -layer { - name: "Mconv1_stage6_L2" - type: "Convolution" - bottom: "concat_stage6" - top: "Mconv1_stage6_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu1_stage6_L2" - type: "ReLU" - bottom: "Mconv1_stage6_L2" - top: "Mconv1_stage6_L2" -} -# layer { -# name: "Mconv2_stage6_L1" -# type: "Convolution" -# bottom: "Mconv1_stage6_L1" -# top: "Mconv2_stage6_L1" -# param { -# lr_mult: 4.0 -# decay_mult: 1 -# } -# param { -# lr_mult: 8.0 -# decay_mult: 0 -# } -# convolution_param { -# num_output: 128 -# pad: 3 -# kernel_size: 7 -# weight_filler { -# type: "gaussian" -# std: 0.01 -# } -# bias_filler { -# type: "constant" -# } -# } -# } -# layer { -# name: "Mrelu2_stage6_L1" -# type: "ReLU" -# bottom: "Mconv2_stage6_L1" -# top: "Mconv2_stage6_L1" -# } -layer { - name: "Mconv2_stage6_L2" - type: "Convolution" - bottom: "Mconv1_stage6_L2" - top: "Mconv2_stage6_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu2_stage6_L2" - type: "ReLU" - bottom: "Mconv2_stage6_L2" - top: "Mconv2_stage6_L2" -} -# layer { -# name: "Mconv3_stage6_L1" -# type: "Convolution" -# bottom: "Mconv2_stage6_L1" -# top: "Mconv3_stage6_L1" -# param { -# lr_mult: 4.0 -# decay_mult: 1 -# } -# param { -# lr_mult: 8.0 -# decay_mult: 0 -# } -# convolution_param { -# num_output: 128 -# pad: 3 -# kernel_size: 7 -# weight_filler { -# type: "gaussian" -# std: 0.01 -# } -# bias_filler { -# type: "constant" -# } -# } -# } -# layer { -# name: "Mrelu3_stage6_L1" -# type: "ReLU" -# bottom: "Mconv3_stage6_L1" -# top: "Mconv3_stage6_L1" -# } -layer { - name: "Mconv3_stage6_L2" - type: "Convolution" - bottom: "Mconv2_stage6_L2" - top: "Mconv3_stage6_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu3_stage6_L2" - type: "ReLU" - bottom: "Mconv3_stage6_L2" - top: "Mconv3_stage6_L2" -} -# layer { -# name: "Mconv4_stage6_L1" -# type: "Convolution" -# bottom: "Mconv3_stage6_L1" -# top: "Mconv4_stage6_L1" -# param { -# lr_mult: 4.0 -# decay_mult: 1 -# } -# param { -# lr_mult: 8.0 -# decay_mult: 0 -# } -# convolution_param { -# num_output: 128 -# pad: 3 -# kernel_size: 7 -# weight_filler { -# type: "gaussian" -# std: 0.01 -# } -# bias_filler { -# type: "constant" -# } -# } -# } -# layer { -# name: "Mrelu4_stage6_L1" -# type: "ReLU" -# bottom: "Mconv4_stage6_L1" -# top: "Mconv4_stage6_L1" -# } -layer { - name: "Mconv4_stage6_L2" - type: "Convolution" - bottom: "Mconv3_stage6_L2" - top: "Mconv4_stage6_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu4_stage6_L2" - type: "ReLU" - bottom: "Mconv4_stage6_L2" - top: "Mconv4_stage6_L2" -} -# layer { -# name: "Mconv5_stage6_L1" -# type: "Convolution" -# bottom: "Mconv4_stage6_L1" -# top: "Mconv5_stage6_L1" -# param { -# lr_mult: 4.0 -# decay_mult: 1 -# } -# param { -# lr_mult: 8.0 -# decay_mult: 0 -# } -# convolution_param { -# num_output: 128 -# pad: 3 -# kernel_size: 7 -# weight_filler { -# type: "gaussian" -# std: 0.01 -# } -# bias_filler { -# type: "constant" -# } -# } -# } -# layer { -# name: "Mrelu5_stage6_L1" -# type: "ReLU" -# bottom: "Mconv5_stage6_L1" -# top: "Mconv5_stage6_L1" -# } -layer { - name: "Mconv5_stage6_L2" - type: "Convolution" - bottom: "Mconv4_stage6_L2" - top: "Mconv5_stage6_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu5_stage6_L2" - type: "ReLU" - bottom: "Mconv5_stage6_L2" - top: "Mconv5_stage6_L2" -} -# layer { -# name: "Mconv6_stage6_L1" -# type: "Convolution" -# bottom: "Mconv5_stage6_L1" -# top: "Mconv6_stage6_L1" -# param { -# lr_mult: 4.0 -# decay_mult: 1 -# } -# param { -# lr_mult: 8.0 -# decay_mult: 0 -# } -# convolution_param { -# num_output: 128 -# pad: 0 -# kernel_size: 1 -# weight_filler { -# type: "gaussian" -# std: 0.01 -# } -# bias_filler { -# type: "constant" -# } -# } -# } -# layer { -# name: "Mrelu6_stage6_L1" -# type: "ReLU" -# bottom: "Mconv6_stage6_L1" -# top: "Mconv6_stage6_L1" -# } -layer { - name: "Mconv6_stage6_L2" - type: "Convolution" - bottom: "Mconv5_stage6_L2" - top: "Mconv6_stage6_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu6_stage6_L2" - type: "ReLU" - bottom: "Mconv6_stage6_L2" - top: "Mconv6_stage6_L2" -} -# layer { -# name: "Mconv7_stage6_L1" -# type: "Convolution" -# bottom: "Mconv6_stage6_L1" -# top: "Mconv7_stage6_L1" -# param { -# lr_mult: 4.0 -# decay_mult: 1 -# } -# param { -# lr_mult: 8.0 -# decay_mult: 0 -# } -# convolution_param { -# num_output: 38 -# pad: 0 -# kernel_size: 1 -# weight_filler { -# type: "gaussian" -# std: 0.01 -# } -# bias_filler { -# type: "constant" -# } -# } -# } -layer { - name: "Mconv7_stage6_L2" - type: "Convolution" - bottom: "Mconv6_stage6_L2" - top: "Mconv7_stage6_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 19 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -# layer { -# name: "concat_stage7" -# type: "Concat" -# bottom: "Mconv7_stage6_L2" -# bottom: "Mconv7_stage6_L1" -# # top: "concat_stage7" -# top: "net_output" -# concat_param { -# axis: 1 -# } -# } diff --git a/testdata/dnn/openpose_pose_mpi.prototxt b/testdata/dnn/openpose_pose_mpi.prototxt deleted file mode 100644 index 5705cd54f..000000000 --- a/testdata/dnn/openpose_pose_mpi.prototxt +++ /dev/null @@ -1,2976 +0,0 @@ -# source: https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/models/pose/mpi/pose_deploy_linevec.prototxt -input: "image" -input_dim: 1 -input_dim: 3 -input_dim: 1 # This value will be defined at runtime -input_dim: 1 # This value will be defined at runtime -layer { - name: "conv1_1" - type: "Convolution" - bottom: "image" - top: "conv1_1" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 64 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu1_1" - type: "ReLU" - bottom: "conv1_1" - top: "conv1_1" -} -layer { - name: "conv1_2" - type: "Convolution" - bottom: "conv1_1" - top: "conv1_2" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 64 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu1_2" - type: "ReLU" - bottom: "conv1_2" - top: "conv1_2" -} -layer { - name: "pool1_stage1" - type: "Pooling" - bottom: "conv1_2" - top: "pool1_stage1" - pooling_param { - pool: MAX - kernel_size: 2 - stride: 2 - } -} -layer { - name: "conv2_1" - type: "Convolution" - bottom: "pool1_stage1" - top: "conv2_1" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu2_1" - type: "ReLU" - bottom: "conv2_1" - top: "conv2_1" -} -layer { - name: "conv2_2" - type: "Convolution" - bottom: "conv2_1" - top: "conv2_2" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu2_2" - type: "ReLU" - bottom: "conv2_2" - top: "conv2_2" -} -layer { - name: "pool2_stage1" - type: "Pooling" - bottom: "conv2_2" - top: "pool2_stage1" - pooling_param { - pool: MAX - kernel_size: 2 - stride: 2 - } -} -layer { - name: "conv3_1" - type: "Convolution" - bottom: "pool2_stage1" - top: "conv3_1" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu3_1" - type: "ReLU" - bottom: "conv3_1" - top: "conv3_1" -} -layer { - name: "conv3_2" - type: "Convolution" - bottom: "conv3_1" - top: "conv3_2" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu3_2" - type: "ReLU" - bottom: "conv3_2" - top: "conv3_2" -} -layer { - name: "conv3_3" - type: "Convolution" - bottom: "conv3_2" - top: "conv3_3" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu3_3" - type: "ReLU" - bottom: "conv3_3" - top: "conv3_3" -} -layer { - name: "conv3_4" - type: "Convolution" - bottom: "conv3_3" - top: "conv3_4" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu3_4" - type: "ReLU" - bottom: "conv3_4" - top: "conv3_4" -} -layer { - name: "pool3_stage1" - type: "Pooling" - bottom: "conv3_4" - top: "pool3_stage1" - pooling_param { - pool: MAX - kernel_size: 2 - stride: 2 - } -} -layer { - name: "conv4_1" - type: "Convolution" - bottom: "pool3_stage1" - top: "conv4_1" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 512 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu4_1" - type: "ReLU" - bottom: "conv4_1" - top: "conv4_1" -} -layer { - name: "conv4_2" - type: "Convolution" - bottom: "conv4_1" - top: "conv4_2" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 512 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu4_2" - type: "ReLU" - bottom: "conv4_2" - top: "conv4_2" -} -layer { - name: "conv4_3_CPM" - type: "Convolution" - bottom: "conv4_2" - top: "conv4_3_CPM" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu4_3_CPM" - type: "ReLU" - bottom: "conv4_3_CPM" - top: "conv4_3_CPM" -} -layer { - name: "conv4_4_CPM" - type: "Convolution" - bottom: "conv4_3_CPM" - top: "conv4_4_CPM" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu4_4_CPM" - type: "ReLU" - bottom: "conv4_4_CPM" - top: "conv4_4_CPM" -} -layer { - name: "conv5_1_CPM_L1" - type: "Convolution" - bottom: "conv4_4_CPM" - top: "conv5_1_CPM_L1" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu5_1_CPM_L1" - type: "ReLU" - bottom: "conv5_1_CPM_L1" - top: "conv5_1_CPM_L1" -} -layer { - name: "conv5_1_CPM_L2" - type: "Convolution" - bottom: "conv4_4_CPM" - top: "conv5_1_CPM_L2" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu5_1_CPM_L2" - type: "ReLU" - bottom: "conv5_1_CPM_L2" - top: "conv5_1_CPM_L2" -} -layer { - name: "conv5_2_CPM_L1" - type: "Convolution" - bottom: "conv5_1_CPM_L1" - top: "conv5_2_CPM_L1" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu5_2_CPM_L1" - type: "ReLU" - bottom: "conv5_2_CPM_L1" - top: "conv5_2_CPM_L1" -} -layer { - name: "conv5_2_CPM_L2" - type: "Convolution" - bottom: "conv5_1_CPM_L2" - top: "conv5_2_CPM_L2" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu5_2_CPM_L2" - type: "ReLU" - bottom: "conv5_2_CPM_L2" - top: "conv5_2_CPM_L2" -} -layer { - name: "conv5_3_CPM_L1" - type: "Convolution" - bottom: "conv5_2_CPM_L1" - top: "conv5_3_CPM_L1" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu5_3_CPM_L1" - type: "ReLU" - bottom: "conv5_3_CPM_L1" - top: "conv5_3_CPM_L1" -} -layer { - name: "conv5_3_CPM_L2" - type: "Convolution" - bottom: "conv5_2_CPM_L2" - top: "conv5_3_CPM_L2" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu5_3_CPM_L2" - type: "ReLU" - bottom: "conv5_3_CPM_L2" - top: "conv5_3_CPM_L2" -} -layer { - name: "conv5_4_CPM_L1" - type: "Convolution" - bottom: "conv5_3_CPM_L1" - top: "conv5_4_CPM_L1" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 512 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu5_4_CPM_L1" - type: "ReLU" - bottom: "conv5_4_CPM_L1" - top: "conv5_4_CPM_L1" -} -layer { - name: "conv5_4_CPM_L2" - type: "Convolution" - bottom: "conv5_3_CPM_L2" - top: "conv5_4_CPM_L2" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 512 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu5_4_CPM_L2" - type: "ReLU" - bottom: "conv5_4_CPM_L2" - top: "conv5_4_CPM_L2" -} -layer { - name: "conv5_5_CPM_L1" - type: "Convolution" - bottom: "conv5_4_CPM_L1" - top: "conv5_5_CPM_L1" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 28 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "conv5_5_CPM_L2" - type: "Convolution" - bottom: "conv5_4_CPM_L2" - top: "conv5_5_CPM_L2" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 16 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "concat_stage2" - type: "Concat" - bottom: "conv5_5_CPM_L1" - bottom: "conv5_5_CPM_L2" - bottom: "conv4_4_CPM" - top: "concat_stage2" - concat_param { - axis: 1 - } -} -layer { - name: "Mconv1_stage2_L1" - type: "Convolution" - bottom: "concat_stage2" - top: "Mconv1_stage2_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu1_stage2_L1" - type: "ReLU" - bottom: "Mconv1_stage2_L1" - top: "Mconv1_stage2_L1" -} -layer { - name: "Mconv1_stage2_L2" - type: "Convolution" - bottom: "concat_stage2" - top: "Mconv1_stage2_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu1_stage2_L2" - type: "ReLU" - bottom: "Mconv1_stage2_L2" - top: "Mconv1_stage2_L2" -} -layer { - name: "Mconv2_stage2_L1" - type: "Convolution" - bottom: "Mconv1_stage2_L1" - top: "Mconv2_stage2_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu2_stage2_L1" - type: "ReLU" - bottom: "Mconv2_stage2_L1" - top: "Mconv2_stage2_L1" -} -layer { - name: "Mconv2_stage2_L2" - type: "Convolution" - bottom: "Mconv1_stage2_L2" - top: "Mconv2_stage2_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu2_stage2_L2" - type: "ReLU" - bottom: "Mconv2_stage2_L2" - top: "Mconv2_stage2_L2" -} -layer { - name: "Mconv3_stage2_L1" - type: "Convolution" - bottom: "Mconv2_stage2_L1" - top: "Mconv3_stage2_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu3_stage2_L1" - type: "ReLU" - bottom: "Mconv3_stage2_L1" - top: "Mconv3_stage2_L1" -} -layer { - name: "Mconv3_stage2_L2" - type: "Convolution" - bottom: "Mconv2_stage2_L2" - top: "Mconv3_stage2_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu3_stage2_L2" - type: "ReLU" - bottom: "Mconv3_stage2_L2" - top: "Mconv3_stage2_L2" -} -layer { - name: "Mconv4_stage2_L1" - type: "Convolution" - bottom: "Mconv3_stage2_L1" - top: "Mconv4_stage2_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu4_stage2_L1" - type: "ReLU" - bottom: "Mconv4_stage2_L1" - top: "Mconv4_stage2_L1" -} -layer { - name: "Mconv4_stage2_L2" - type: "Convolution" - bottom: "Mconv3_stage2_L2" - top: "Mconv4_stage2_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu4_stage2_L2" - type: "ReLU" - bottom: "Mconv4_stage2_L2" - top: "Mconv4_stage2_L2" -} -layer { - name: "Mconv5_stage2_L1" - type: "Convolution" - bottom: "Mconv4_stage2_L1" - top: "Mconv5_stage2_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu5_stage2_L1" - type: "ReLU" - bottom: "Mconv5_stage2_L1" - top: "Mconv5_stage2_L1" -} -layer { - name: "Mconv5_stage2_L2" - type: "Convolution" - bottom: "Mconv4_stage2_L2" - top: "Mconv5_stage2_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu5_stage2_L2" - type: "ReLU" - bottom: "Mconv5_stage2_L2" - top: "Mconv5_stage2_L2" -} -layer { - name: "Mconv6_stage2_L1" - type: "Convolution" - bottom: "Mconv5_stage2_L1" - top: "Mconv6_stage2_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu6_stage2_L1" - type: "ReLU" - bottom: "Mconv6_stage2_L1" - top: "Mconv6_stage2_L1" -} -layer { - name: "Mconv6_stage2_L2" - type: "Convolution" - bottom: "Mconv5_stage2_L2" - top: "Mconv6_stage2_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu6_stage2_L2" - type: "ReLU" - bottom: "Mconv6_stage2_L2" - top: "Mconv6_stage2_L2" -} -layer { - name: "Mconv7_stage2_L1" - type: "Convolution" - bottom: "Mconv6_stage2_L1" - top: "Mconv7_stage2_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 28 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mconv7_stage2_L2" - type: "Convolution" - bottom: "Mconv6_stage2_L2" - top: "Mconv7_stage2_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 16 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "concat_stage3" - type: "Concat" - bottom: "Mconv7_stage2_L1" - bottom: "Mconv7_stage2_L2" - bottom: "conv4_4_CPM" - top: "concat_stage3" - concat_param { - axis: 1 - } -} -layer { - name: "Mconv1_stage3_L1" - type: "Convolution" - bottom: "concat_stage3" - top: "Mconv1_stage3_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu1_stage3_L1" - type: "ReLU" - bottom: "Mconv1_stage3_L1" - top: "Mconv1_stage3_L1" -} -layer { - name: "Mconv1_stage3_L2" - type: "Convolution" - bottom: "concat_stage3" - top: "Mconv1_stage3_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu1_stage3_L2" - type: "ReLU" - bottom: "Mconv1_stage3_L2" - top: "Mconv1_stage3_L2" -} -layer { - name: "Mconv2_stage3_L1" - type: "Convolution" - bottom: "Mconv1_stage3_L1" - top: "Mconv2_stage3_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu2_stage3_L1" - type: "ReLU" - bottom: "Mconv2_stage3_L1" - top: "Mconv2_stage3_L1" -} -layer { - name: "Mconv2_stage3_L2" - type: "Convolution" - bottom: "Mconv1_stage3_L2" - top: "Mconv2_stage3_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu2_stage3_L2" - type: "ReLU" - bottom: "Mconv2_stage3_L2" - top: "Mconv2_stage3_L2" -} -layer { - name: "Mconv3_stage3_L1" - type: "Convolution" - bottom: "Mconv2_stage3_L1" - top: "Mconv3_stage3_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu3_stage3_L1" - type: "ReLU" - bottom: "Mconv3_stage3_L1" - top: "Mconv3_stage3_L1" -} -layer { - name: "Mconv3_stage3_L2" - type: "Convolution" - bottom: "Mconv2_stage3_L2" - top: "Mconv3_stage3_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu3_stage3_L2" - type: "ReLU" - bottom: "Mconv3_stage3_L2" - top: "Mconv3_stage3_L2" -} -layer { - name: "Mconv4_stage3_L1" - type: "Convolution" - bottom: "Mconv3_stage3_L1" - top: "Mconv4_stage3_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu4_stage3_L1" - type: "ReLU" - bottom: "Mconv4_stage3_L1" - top: "Mconv4_stage3_L1" -} -layer { - name: "Mconv4_stage3_L2" - type: "Convolution" - bottom: "Mconv3_stage3_L2" - top: "Mconv4_stage3_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu4_stage3_L2" - type: "ReLU" - bottom: "Mconv4_stage3_L2" - top: "Mconv4_stage3_L2" -} -layer { - name: "Mconv5_stage3_L1" - type: "Convolution" - bottom: "Mconv4_stage3_L1" - top: "Mconv5_stage3_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu5_stage3_L1" - type: "ReLU" - bottom: "Mconv5_stage3_L1" - top: "Mconv5_stage3_L1" -} -layer { - name: "Mconv5_stage3_L2" - type: "Convolution" - bottom: "Mconv4_stage3_L2" - top: "Mconv5_stage3_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu5_stage3_L2" - type: "ReLU" - bottom: "Mconv5_stage3_L2" - top: "Mconv5_stage3_L2" -} -layer { - name: "Mconv6_stage3_L1" - type: "Convolution" - bottom: "Mconv5_stage3_L1" - top: "Mconv6_stage3_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu6_stage3_L1" - type: "ReLU" - bottom: "Mconv6_stage3_L1" - top: "Mconv6_stage3_L1" -} -layer { - name: "Mconv6_stage3_L2" - type: "Convolution" - bottom: "Mconv5_stage3_L2" - top: "Mconv6_stage3_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu6_stage3_L2" - type: "ReLU" - bottom: "Mconv6_stage3_L2" - top: "Mconv6_stage3_L2" -} -layer { - name: "Mconv7_stage3_L1" - type: "Convolution" - bottom: "Mconv6_stage3_L1" - top: "Mconv7_stage3_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 28 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mconv7_stage3_L2" - type: "Convolution" - bottom: "Mconv6_stage3_L2" - top: "Mconv7_stage3_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 16 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "concat_stage4" - type: "Concat" - bottom: "Mconv7_stage3_L1" - bottom: "Mconv7_stage3_L2" - bottom: "conv4_4_CPM" - top: "concat_stage4" - concat_param { - axis: 1 - } -} -layer { - name: "Mconv1_stage4_L1" - type: "Convolution" - bottom: "concat_stage4" - top: "Mconv1_stage4_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu1_stage4_L1" - type: "ReLU" - bottom: "Mconv1_stage4_L1" - top: "Mconv1_stage4_L1" -} -layer { - name: "Mconv1_stage4_L2" - type: "Convolution" - bottom: "concat_stage4" - top: "Mconv1_stage4_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu1_stage4_L2" - type: "ReLU" - bottom: "Mconv1_stage4_L2" - top: "Mconv1_stage4_L2" -} -layer { - name: "Mconv2_stage4_L1" - type: "Convolution" - bottom: "Mconv1_stage4_L1" - top: "Mconv2_stage4_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu2_stage4_L1" - type: "ReLU" - bottom: "Mconv2_stage4_L1" - top: "Mconv2_stage4_L1" -} -layer { - name: "Mconv2_stage4_L2" - type: "Convolution" - bottom: "Mconv1_stage4_L2" - top: "Mconv2_stage4_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu2_stage4_L2" - type: "ReLU" - bottom: "Mconv2_stage4_L2" - top: "Mconv2_stage4_L2" -} -layer { - name: "Mconv3_stage4_L1" - type: "Convolution" - bottom: "Mconv2_stage4_L1" - top: "Mconv3_stage4_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu3_stage4_L1" - type: "ReLU" - bottom: "Mconv3_stage4_L1" - top: "Mconv3_stage4_L1" -} -layer { - name: "Mconv3_stage4_L2" - type: "Convolution" - bottom: "Mconv2_stage4_L2" - top: "Mconv3_stage4_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu3_stage4_L2" - type: "ReLU" - bottom: "Mconv3_stage4_L2" - top: "Mconv3_stage4_L2" -} -layer { - name: "Mconv4_stage4_L1" - type: "Convolution" - bottom: "Mconv3_stage4_L1" - top: "Mconv4_stage4_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu4_stage4_L1" - type: "ReLU" - bottom: "Mconv4_stage4_L1" - top: "Mconv4_stage4_L1" -} -layer { - name: "Mconv4_stage4_L2" - type: "Convolution" - bottom: "Mconv3_stage4_L2" - top: "Mconv4_stage4_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu4_stage4_L2" - type: "ReLU" - bottom: "Mconv4_stage4_L2" - top: "Mconv4_stage4_L2" -} -layer { - name: "Mconv5_stage4_L1" - type: "Convolution" - bottom: "Mconv4_stage4_L1" - top: "Mconv5_stage4_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu5_stage4_L1" - type: "ReLU" - bottom: "Mconv5_stage4_L1" - top: "Mconv5_stage4_L1" -} -layer { - name: "Mconv5_stage4_L2" - type: "Convolution" - bottom: "Mconv4_stage4_L2" - top: "Mconv5_stage4_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu5_stage4_L2" - type: "ReLU" - bottom: "Mconv5_stage4_L2" - top: "Mconv5_stage4_L2" -} -layer { - name: "Mconv6_stage4_L1" - type: "Convolution" - bottom: "Mconv5_stage4_L1" - top: "Mconv6_stage4_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu6_stage4_L1" - type: "ReLU" - bottom: "Mconv6_stage4_L1" - top: "Mconv6_stage4_L1" -} -layer { - name: "Mconv6_stage4_L2" - type: "Convolution" - bottom: "Mconv5_stage4_L2" - top: "Mconv6_stage4_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu6_stage4_L2" - type: "ReLU" - bottom: "Mconv6_stage4_L2" - top: "Mconv6_stage4_L2" -} -layer { - name: "Mconv7_stage4_L1" - type: "Convolution" - bottom: "Mconv6_stage4_L1" - top: "Mconv7_stage4_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 28 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mconv7_stage4_L2" - type: "Convolution" - bottom: "Mconv6_stage4_L2" - top: "Mconv7_stage4_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 16 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "concat_stage5" - type: "Concat" - bottom: "Mconv7_stage4_L1" - bottom: "Mconv7_stage4_L2" - bottom: "conv4_4_CPM" - top: "concat_stage5" - concat_param { - axis: 1 - } -} -layer { - name: "Mconv1_stage5_L1" - type: "Convolution" - bottom: "concat_stage5" - top: "Mconv1_stage5_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu1_stage5_L1" - type: "ReLU" - bottom: "Mconv1_stage5_L1" - top: "Mconv1_stage5_L1" -} -layer { - name: "Mconv1_stage5_L2" - type: "Convolution" - bottom: "concat_stage5" - top: "Mconv1_stage5_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu1_stage5_L2" - type: "ReLU" - bottom: "Mconv1_stage5_L2" - top: "Mconv1_stage5_L2" -} -layer { - name: "Mconv2_stage5_L1" - type: "Convolution" - bottom: "Mconv1_stage5_L1" - top: "Mconv2_stage5_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu2_stage5_L1" - type: "ReLU" - bottom: "Mconv2_stage5_L1" - top: "Mconv2_stage5_L1" -} -layer { - name: "Mconv2_stage5_L2" - type: "Convolution" - bottom: "Mconv1_stage5_L2" - top: "Mconv2_stage5_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu2_stage5_L2" - type: "ReLU" - bottom: "Mconv2_stage5_L2" - top: "Mconv2_stage5_L2" -} -layer { - name: "Mconv3_stage5_L1" - type: "Convolution" - bottom: "Mconv2_stage5_L1" - top: "Mconv3_stage5_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu3_stage5_L1" - type: "ReLU" - bottom: "Mconv3_stage5_L1" - top: "Mconv3_stage5_L1" -} -layer { - name: "Mconv3_stage5_L2" - type: "Convolution" - bottom: "Mconv2_stage5_L2" - top: "Mconv3_stage5_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu3_stage5_L2" - type: "ReLU" - bottom: "Mconv3_stage5_L2" - top: "Mconv3_stage5_L2" -} -layer { - name: "Mconv4_stage5_L1" - type: "Convolution" - bottom: "Mconv3_stage5_L1" - top: "Mconv4_stage5_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu4_stage5_L1" - type: "ReLU" - bottom: "Mconv4_stage5_L1" - top: "Mconv4_stage5_L1" -} -layer { - name: "Mconv4_stage5_L2" - type: "Convolution" - bottom: "Mconv3_stage5_L2" - top: "Mconv4_stage5_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu4_stage5_L2" - type: "ReLU" - bottom: "Mconv4_stage5_L2" - top: "Mconv4_stage5_L2" -} -layer { - name: "Mconv5_stage5_L1" - type: "Convolution" - bottom: "Mconv4_stage5_L1" - top: "Mconv5_stage5_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu5_stage5_L1" - type: "ReLU" - bottom: "Mconv5_stage5_L1" - top: "Mconv5_stage5_L1" -} -layer { - name: "Mconv5_stage5_L2" - type: "Convolution" - bottom: "Mconv4_stage5_L2" - top: "Mconv5_stage5_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu5_stage5_L2" - type: "ReLU" - bottom: "Mconv5_stage5_L2" - top: "Mconv5_stage5_L2" -} -layer { - name: "Mconv6_stage5_L1" - type: "Convolution" - bottom: "Mconv5_stage5_L1" - top: "Mconv6_stage5_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu6_stage5_L1" - type: "ReLU" - bottom: "Mconv6_stage5_L1" - top: "Mconv6_stage5_L1" -} -layer { - name: "Mconv6_stage5_L2" - type: "Convolution" - bottom: "Mconv5_stage5_L2" - top: "Mconv6_stage5_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu6_stage5_L2" - type: "ReLU" - bottom: "Mconv6_stage5_L2" - top: "Mconv6_stage5_L2" -} -layer { - name: "Mconv7_stage5_L1" - type: "Convolution" - bottom: "Mconv6_stage5_L1" - top: "Mconv7_stage5_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 28 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mconv7_stage5_L2" - type: "Convolution" - bottom: "Mconv6_stage5_L2" - top: "Mconv7_stage5_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 16 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "concat_stage6" - type: "Concat" - bottom: "Mconv7_stage5_L1" - bottom: "Mconv7_stage5_L2" - bottom: "conv4_4_CPM" - top: "concat_stage6" - concat_param { - axis: 1 - } -} -# layer { -# name: "Mconv1_stage6_L1" -# type: "Convolution" -# bottom: "concat_stage6" -# top: "Mconv1_stage6_L1" -# param { -# lr_mult: 4.0 -# decay_mult: 1 -# } -# param { -# lr_mult: 8.0 -# decay_mult: 0 -# } -# convolution_param { -# num_output: 128 -# pad: 3 -# kernel_size: 7 -# weight_filler { -# type: "gaussian" -# std: 0.01 -# } -# bias_filler { -# type: "constant" -# } -# } -# } -# layer { -# name: "Mrelu1_stage6_L1" -# type: "ReLU" -# bottom: "Mconv1_stage6_L1" -# top: "Mconv1_stage6_L1" -# } -layer { - name: "Mconv1_stage6_L2" - type: "Convolution" - bottom: "concat_stage6" - top: "Mconv1_stage6_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu1_stage6_L2" - type: "ReLU" - bottom: "Mconv1_stage6_L2" - top: "Mconv1_stage6_L2" -} -# layer { -# name: "Mconv2_stage6_L1" -# type: "Convolution" -# bottom: "Mconv1_stage6_L1" -# top: "Mconv2_stage6_L1" -# param { -# lr_mult: 4.0 -# decay_mult: 1 -# } -# param { -# lr_mult: 8.0 -# decay_mult: 0 -# } -# convolution_param { -# num_output: 128 -# pad: 3 -# kernel_size: 7 -# weight_filler { -# type: "gaussian" -# std: 0.01 -# } -# bias_filler { -# type: "constant" -# } -# } -# } -# layer { -# name: "Mrelu2_stage6_L1" -# type: "ReLU" -# bottom: "Mconv2_stage6_L1" -# top: "Mconv2_stage6_L1" -# } -layer { - name: "Mconv2_stage6_L2" - type: "Convolution" - bottom: "Mconv1_stage6_L2" - top: "Mconv2_stage6_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu2_stage6_L2" - type: "ReLU" - bottom: "Mconv2_stage6_L2" - top: "Mconv2_stage6_L2" -} -# layer { -# name: "Mconv3_stage6_L1" -# type: "Convolution" -# bottom: "Mconv2_stage6_L1" -# top: "Mconv3_stage6_L1" -# param { -# lr_mult: 4.0 -# decay_mult: 1 -# } -# param { -# lr_mult: 8.0 -# decay_mult: 0 -# } -# convolution_param { -# num_output: 128 -# pad: 3 -# kernel_size: 7 -# weight_filler { -# type: "gaussian" -# std: 0.01 -# } -# bias_filler { -# type: "constant" -# } -# } -# } -# layer { -# name: "Mrelu3_stage6_L1" -# type: "ReLU" -# bottom: "Mconv3_stage6_L1" -# top: "Mconv3_stage6_L1" -# } -layer { - name: "Mconv3_stage6_L2" - type: "Convolution" - bottom: "Mconv2_stage6_L2" - top: "Mconv3_stage6_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu3_stage6_L2" - type: "ReLU" - bottom: "Mconv3_stage6_L2" - top: "Mconv3_stage6_L2" -} -# layer { -# name: "Mconv4_stage6_L1" -# type: "Convolution" -# bottom: "Mconv3_stage6_L1" -# top: "Mconv4_stage6_L1" -# param { -# lr_mult: 4.0 -# decay_mult: 1 -# } -# param { -# lr_mult: 8.0 -# decay_mult: 0 -# } -# convolution_param { -# num_output: 128 -# pad: 3 -# kernel_size: 7 -# weight_filler { -# type: "gaussian" -# std: 0.01 -# } -# bias_filler { -# type: "constant" -# } -# } -# } -# layer { -# name: "Mrelu4_stage6_L1" -# type: "ReLU" -# bottom: "Mconv4_stage6_L1" -# top: "Mconv4_stage6_L1" -# } -layer { - name: "Mconv4_stage6_L2" - type: "Convolution" - bottom: "Mconv3_stage6_L2" - top: "Mconv4_stage6_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu4_stage6_L2" - type: "ReLU" - bottom: "Mconv4_stage6_L2" - top: "Mconv4_stage6_L2" -} -# layer { -# name: "Mconv5_stage6_L1" -# type: "Convolution" -# bottom: "Mconv4_stage6_L1" -# top: "Mconv5_stage6_L1" -# param { -# lr_mult: 4.0 -# decay_mult: 1 -# } -# param { -# lr_mult: 8.0 -# decay_mult: 0 -# } -# convolution_param { -# num_output: 128 -# pad: 3 -# kernel_size: 7 -# weight_filler { -# type: "gaussian" -# std: 0.01 -# } -# bias_filler { -# type: "constant" -# } -# } -# } -# layer { -# name: "Mrelu5_stage6_L1" -# type: "ReLU" -# bottom: "Mconv5_stage6_L1" -# top: "Mconv5_stage6_L1" -# } -layer { - name: "Mconv5_stage6_L2" - type: "Convolution" - bottom: "Mconv4_stage6_L2" - top: "Mconv5_stage6_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu5_stage6_L2" - type: "ReLU" - bottom: "Mconv5_stage6_L2" - top: "Mconv5_stage6_L2" -} -# layer { -# name: "Mconv6_stage6_L1" -# type: "Convolution" -# bottom: "Mconv5_stage6_L1" -# top: "Mconv6_stage6_L1" -# param { -# lr_mult: 4.0 -# decay_mult: 1 -# } -# param { -# lr_mult: 8.0 -# decay_mult: 0 -# } -# convolution_param { -# num_output: 128 -# pad: 0 -# kernel_size: 1 -# weight_filler { -# type: "gaussian" -# std: 0.01 -# } -# bias_filler { -# type: "constant" -# } -# } -# } -# layer { -# name: "Mrelu6_stage6_L1" -# type: "ReLU" -# bottom: "Mconv6_stage6_L1" -# top: "Mconv6_stage6_L1" -# } -layer { - name: "Mconv6_stage6_L2" - type: "Convolution" - bottom: "Mconv5_stage6_L2" - top: "Mconv6_stage6_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu6_stage6_L2" - type: "ReLU" - bottom: "Mconv6_stage6_L2" - top: "Mconv6_stage6_L2" -} -# layer { -# name: "Mconv7_stage6_L1" -# type: "Convolution" -# bottom: "Mconv6_stage6_L1" -# top: "Mconv7_stage6_L1" -# param { -# lr_mult: 4.0 -# decay_mult: 1 -# } -# param { -# lr_mult: 8.0 -# decay_mult: 0 -# } -# convolution_param { -# num_output: 28 -# pad: 0 -# kernel_size: 1 -# weight_filler { -# type: "gaussian" -# std: 0.01 -# } -# bias_filler { -# type: "constant" -# } -# } -# } -layer { - name: "Mconv7_stage6_L2" - type: "Convolution" - bottom: "Mconv6_stage6_L2" - top: "Mconv7_stage6_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 16 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -# layer { -# name: "concat_stage7" -# type: "Concat" -# bottom: "Mconv7_stage6_L2" -# bottom: "Mconv7_stage6_L1" -# top: "net_output" -# concat_param { -# axis: 1 -# } -# } diff --git a/testdata/dnn/openpose_pose_mpi_faster_4_stages.prototxt b/testdata/dnn/openpose_pose_mpi_faster_4_stages.prototxt deleted file mode 100644 index 92a89dd04..000000000 --- a/testdata/dnn/openpose_pose_mpi_faster_4_stages.prototxt +++ /dev/null @@ -1,2082 +0,0 @@ -# source: https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/models/pose/mpi/pose_deploy_linevec_faster_4_stages.prototxt -input: "image" -input_dim: 1 -input_dim: 3 -input_dim: 1 # This value will be defined at runtime -input_dim: 1 # This value will be defined at runtime -layer { - name: "conv1_1" - type: "Convolution" - bottom: "image" - top: "conv1_1" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 64 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu1_1" - type: "ReLU" - bottom: "conv1_1" - top: "conv1_1" -} -layer { - name: "conv1_2" - type: "Convolution" - bottom: "conv1_1" - top: "conv1_2" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 64 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu1_2" - type: "ReLU" - bottom: "conv1_2" - top: "conv1_2" -} -layer { - name: "pool1_stage1" - type: "Pooling" - bottom: "conv1_2" - top: "pool1_stage1" - pooling_param { - pool: MAX - kernel_size: 2 - stride: 2 - } -} -layer { - name: "conv2_1" - type: "Convolution" - bottom: "pool1_stage1" - top: "conv2_1" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu2_1" - type: "ReLU" - bottom: "conv2_1" - top: "conv2_1" -} -layer { - name: "conv2_2" - type: "Convolution" - bottom: "conv2_1" - top: "conv2_2" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu2_2" - type: "ReLU" - bottom: "conv2_2" - top: "conv2_2" -} -layer { - name: "pool2_stage1" - type: "Pooling" - bottom: "conv2_2" - top: "pool2_stage1" - pooling_param { - pool: MAX - kernel_size: 2 - stride: 2 - } -} -layer { - name: "conv3_1" - type: "Convolution" - bottom: "pool2_stage1" - top: "conv3_1" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu3_1" - type: "ReLU" - bottom: "conv3_1" - top: "conv3_1" -} -layer { - name: "conv3_2" - type: "Convolution" - bottom: "conv3_1" - top: "conv3_2" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu3_2" - type: "ReLU" - bottom: "conv3_2" - top: "conv3_2" -} -layer { - name: "conv3_3" - type: "Convolution" - bottom: "conv3_2" - top: "conv3_3" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu3_3" - type: "ReLU" - bottom: "conv3_3" - top: "conv3_3" -} -layer { - name: "conv3_4" - type: "Convolution" - bottom: "conv3_3" - top: "conv3_4" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu3_4" - type: "ReLU" - bottom: "conv3_4" - top: "conv3_4" -} -layer { - name: "pool3_stage1" - type: "Pooling" - bottom: "conv3_4" - top: "pool3_stage1" - pooling_param { - pool: MAX - kernel_size: 2 - stride: 2 - } -} -layer { - name: "conv4_1" - type: "Convolution" - bottom: "pool3_stage1" - top: "conv4_1" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 512 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu4_1" - type: "ReLU" - bottom: "conv4_1" - top: "conv4_1" -} -layer { - name: "conv4_2" - type: "Convolution" - bottom: "conv4_1" - top: "conv4_2" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 512 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu4_2" - type: "ReLU" - bottom: "conv4_2" - top: "conv4_2" -} -layer { - name: "conv4_3_CPM" - type: "Convolution" - bottom: "conv4_2" - top: "conv4_3_CPM" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu4_3_CPM" - type: "ReLU" - bottom: "conv4_3_CPM" - top: "conv4_3_CPM" -} -layer { - name: "conv4_4_CPM" - type: "Convolution" - bottom: "conv4_3_CPM" - top: "conv4_4_CPM" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu4_4_CPM" - type: "ReLU" - bottom: "conv4_4_CPM" - top: "conv4_4_CPM" -} -layer { - name: "conv5_1_CPM_L1" - type: "Convolution" - bottom: "conv4_4_CPM" - top: "conv5_1_CPM_L1" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu5_1_CPM_L1" - type: "ReLU" - bottom: "conv5_1_CPM_L1" - top: "conv5_1_CPM_L1" -} -layer { - name: "conv5_1_CPM_L2" - type: "Convolution" - bottom: "conv4_4_CPM" - top: "conv5_1_CPM_L2" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu5_1_CPM_L2" - type: "ReLU" - bottom: "conv5_1_CPM_L2" - top: "conv5_1_CPM_L2" -} -layer { - name: "conv5_2_CPM_L1" - type: "Convolution" - bottom: "conv5_1_CPM_L1" - top: "conv5_2_CPM_L1" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu5_2_CPM_L1" - type: "ReLU" - bottom: "conv5_2_CPM_L1" - top: "conv5_2_CPM_L1" -} -layer { - name: "conv5_2_CPM_L2" - type: "Convolution" - bottom: "conv5_1_CPM_L2" - top: "conv5_2_CPM_L2" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu5_2_CPM_L2" - type: "ReLU" - bottom: "conv5_2_CPM_L2" - top: "conv5_2_CPM_L2" -} -layer { - name: "conv5_3_CPM_L1" - type: "Convolution" - bottom: "conv5_2_CPM_L1" - top: "conv5_3_CPM_L1" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu5_3_CPM_L1" - type: "ReLU" - bottom: "conv5_3_CPM_L1" - top: "conv5_3_CPM_L1" -} -layer { - name: "conv5_3_CPM_L2" - type: "Convolution" - bottom: "conv5_2_CPM_L2" - top: "conv5_3_CPM_L2" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu5_3_CPM_L2" - type: "ReLU" - bottom: "conv5_3_CPM_L2" - top: "conv5_3_CPM_L2" -} -layer { - name: "conv5_4_CPM_L1" - type: "Convolution" - bottom: "conv5_3_CPM_L1" - top: "conv5_4_CPM_L1" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 512 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu5_4_CPM_L1" - type: "ReLU" - bottom: "conv5_4_CPM_L1" - top: "conv5_4_CPM_L1" -} -layer { - name: "conv5_4_CPM_L2" - type: "Convolution" - bottom: "conv5_3_CPM_L2" - top: "conv5_4_CPM_L2" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 512 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "relu5_4_CPM_L2" - type: "ReLU" - bottom: "conv5_4_CPM_L2" - top: "conv5_4_CPM_L2" -} -layer { - name: "conv5_5_CPM_L1" - type: "Convolution" - bottom: "conv5_4_CPM_L1" - top: "conv5_5_CPM_L1" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 28 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "conv5_5_CPM_L2" - type: "Convolution" - bottom: "conv5_4_CPM_L2" - top: "conv5_5_CPM_L2" - param { - lr_mult: 1.0 - decay_mult: 1 - } - param { - lr_mult: 2.0 - decay_mult: 0 - } - convolution_param { - num_output: 16 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "concat_stage2" - type: "Concat" - bottom: "conv5_5_CPM_L1" - bottom: "conv5_5_CPM_L2" - bottom: "conv4_4_CPM" - top: "concat_stage2" - concat_param { - axis: 1 - } -} -layer { - name: "Mconv1_stage2_L1" - type: "Convolution" - bottom: "concat_stage2" - top: "Mconv1_stage2_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu1_stage2_L1" - type: "ReLU" - bottom: "Mconv1_stage2_L1" - top: "Mconv1_stage2_L1" -} -layer { - name: "Mconv1_stage2_L2" - type: "Convolution" - bottom: "concat_stage2" - top: "Mconv1_stage2_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu1_stage2_L2" - type: "ReLU" - bottom: "Mconv1_stage2_L2" - top: "Mconv1_stage2_L2" -} -layer { - name: "Mconv2_stage2_L1" - type: "Convolution" - bottom: "Mconv1_stage2_L1" - top: "Mconv2_stage2_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu2_stage2_L1" - type: "ReLU" - bottom: "Mconv2_stage2_L1" - top: "Mconv2_stage2_L1" -} -layer { - name: "Mconv2_stage2_L2" - type: "Convolution" - bottom: "Mconv1_stage2_L2" - top: "Mconv2_stage2_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu2_stage2_L2" - type: "ReLU" - bottom: "Mconv2_stage2_L2" - top: "Mconv2_stage2_L2" -} -layer { - name: "Mconv3_stage2_L1" - type: "Convolution" - bottom: "Mconv2_stage2_L1" - top: "Mconv3_stage2_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu3_stage2_L1" - type: "ReLU" - bottom: "Mconv3_stage2_L1" - top: "Mconv3_stage2_L1" -} -layer { - name: "Mconv3_stage2_L2" - type: "Convolution" - bottom: "Mconv2_stage2_L2" - top: "Mconv3_stage2_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu3_stage2_L2" - type: "ReLU" - bottom: "Mconv3_stage2_L2" - top: "Mconv3_stage2_L2" -} -layer { - name: "Mconv4_stage2_L1" - type: "Convolution" - bottom: "Mconv3_stage2_L1" - top: "Mconv4_stage2_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu4_stage2_L1" - type: "ReLU" - bottom: "Mconv4_stage2_L1" - top: "Mconv4_stage2_L1" -} -layer { - name: "Mconv4_stage2_L2" - type: "Convolution" - bottom: "Mconv3_stage2_L2" - top: "Mconv4_stage2_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu4_stage2_L2" - type: "ReLU" - bottom: "Mconv4_stage2_L2" - top: "Mconv4_stage2_L2" -} -layer { - name: "Mconv5_stage2_L1" - type: "Convolution" - bottom: "Mconv4_stage2_L1" - top: "Mconv5_stage2_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu5_stage2_L1" - type: "ReLU" - bottom: "Mconv5_stage2_L1" - top: "Mconv5_stage2_L1" -} -layer { - name: "Mconv5_stage2_L2" - type: "Convolution" - bottom: "Mconv4_stage2_L2" - top: "Mconv5_stage2_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu5_stage2_L2" - type: "ReLU" - bottom: "Mconv5_stage2_L2" - top: "Mconv5_stage2_L2" -} -layer { - name: "Mconv6_stage2_L1" - type: "Convolution" - bottom: "Mconv5_stage2_L1" - top: "Mconv6_stage2_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu6_stage2_L1" - type: "ReLU" - bottom: "Mconv6_stage2_L1" - top: "Mconv6_stage2_L1" -} -layer { - name: "Mconv6_stage2_L2" - type: "Convolution" - bottom: "Mconv5_stage2_L2" - top: "Mconv6_stage2_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu6_stage2_L2" - type: "ReLU" - bottom: "Mconv6_stage2_L2" - top: "Mconv6_stage2_L2" -} -layer { - name: "Mconv7_stage2_L1" - type: "Convolution" - bottom: "Mconv6_stage2_L1" - top: "Mconv7_stage2_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 28 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mconv7_stage2_L2" - type: "Convolution" - bottom: "Mconv6_stage2_L2" - top: "Mconv7_stage2_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 16 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "concat_stage3" - type: "Concat" - bottom: "Mconv7_stage2_L1" - bottom: "Mconv7_stage2_L2" - bottom: "conv4_4_CPM" - top: "concat_stage3" - concat_param { - axis: 1 - } -} -layer { - name: "Mconv1_stage3_L1" - type: "Convolution" - bottom: "concat_stage3" - top: "Mconv1_stage3_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu1_stage3_L1" - type: "ReLU" - bottom: "Mconv1_stage3_L1" - top: "Mconv1_stage3_L1" -} -layer { - name: "Mconv1_stage3_L2" - type: "Convolution" - bottom: "concat_stage3" - top: "Mconv1_stage3_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu1_stage3_L2" - type: "ReLU" - bottom: "Mconv1_stage3_L2" - top: "Mconv1_stage3_L2" -} -layer { - name: "Mconv2_stage3_L1" - type: "Convolution" - bottom: "Mconv1_stage3_L1" - top: "Mconv2_stage3_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu2_stage3_L1" - type: "ReLU" - bottom: "Mconv2_stage3_L1" - top: "Mconv2_stage3_L1" -} -layer { - name: "Mconv2_stage3_L2" - type: "Convolution" - bottom: "Mconv1_stage3_L2" - top: "Mconv2_stage3_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu2_stage3_L2" - type: "ReLU" - bottom: "Mconv2_stage3_L2" - top: "Mconv2_stage3_L2" -} -layer { - name: "Mconv3_stage3_L1" - type: "Convolution" - bottom: "Mconv2_stage3_L1" - top: "Mconv3_stage3_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu3_stage3_L1" - type: "ReLU" - bottom: "Mconv3_stage3_L1" - top: "Mconv3_stage3_L1" -} -layer { - name: "Mconv3_stage3_L2" - type: "Convolution" - bottom: "Mconv2_stage3_L2" - top: "Mconv3_stage3_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu3_stage3_L2" - type: "ReLU" - bottom: "Mconv3_stage3_L2" - top: "Mconv3_stage3_L2" -} -layer { - name: "Mconv4_stage3_L1" - type: "Convolution" - bottom: "Mconv3_stage3_L1" - top: "Mconv4_stage3_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu4_stage3_L1" - type: "ReLU" - bottom: "Mconv4_stage3_L1" - top: "Mconv4_stage3_L1" -} -layer { - name: "Mconv4_stage3_L2" - type: "Convolution" - bottom: "Mconv3_stage3_L2" - top: "Mconv4_stage3_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu4_stage3_L2" - type: "ReLU" - bottom: "Mconv4_stage3_L2" - top: "Mconv4_stage3_L2" -} -layer { - name: "Mconv5_stage3_L1" - type: "Convolution" - bottom: "Mconv4_stage3_L1" - top: "Mconv5_stage3_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu5_stage3_L1" - type: "ReLU" - bottom: "Mconv5_stage3_L1" - top: "Mconv5_stage3_L1" -} -layer { - name: "Mconv5_stage3_L2" - type: "Convolution" - bottom: "Mconv4_stage3_L2" - top: "Mconv5_stage3_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu5_stage3_L2" - type: "ReLU" - bottom: "Mconv5_stage3_L2" - top: "Mconv5_stage3_L2" -} -layer { - name: "Mconv6_stage3_L1" - type: "Convolution" - bottom: "Mconv5_stage3_L1" - top: "Mconv6_stage3_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu6_stage3_L1" - type: "ReLU" - bottom: "Mconv6_stage3_L1" - top: "Mconv6_stage3_L1" -} -layer { - name: "Mconv6_stage3_L2" - type: "Convolution" - bottom: "Mconv5_stage3_L2" - top: "Mconv6_stage3_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu6_stage3_L2" - type: "ReLU" - bottom: "Mconv6_stage3_L2" - top: "Mconv6_stage3_L2" -} -layer { - name: "Mconv7_stage3_L1" - type: "Convolution" - bottom: "Mconv6_stage3_L1" - top: "Mconv7_stage3_L1" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 28 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mconv7_stage3_L2" - type: "Convolution" - bottom: "Mconv6_stage3_L2" - top: "Mconv7_stage3_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 16 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "concat_stage4" - type: "Concat" - bottom: "Mconv7_stage3_L1" - bottom: "Mconv7_stage3_L2" - bottom: "conv4_4_CPM" - top: "concat_stage4" - concat_param { - axis: 1 - } -} -# layer { -# name: "Mconv1_stage4_L1" -# type: "Convolution" -# bottom: "concat_stage4" -# top: "Mconv1_stage4_L1" -# param { -# lr_mult: 4.0 -# decay_mult: 1 -# } -# param { -# lr_mult: 8.0 -# decay_mult: 0 -# } -# convolution_param { -# num_output: 128 -# pad: 3 -# kernel_size: 7 -# weight_filler { -# type: "gaussian" -# std: 0.01 -# } -# bias_filler { -# type: "constant" -# } -# } -# } -# layer { -# name: "Mrelu1_stage4_L1" -# type: "ReLU" -# bottom: "Mconv1_stage4_L1" -# top: "Mconv1_stage4_L1" -# } -layer { - name: "Mconv1_stage4_L2" - type: "Convolution" - bottom: "concat_stage4" - top: "Mconv1_stage4_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu1_stage4_L2" - type: "ReLU" - bottom: "Mconv1_stage4_L2" - top: "Mconv1_stage4_L2" -} -# layer { -# name: "Mconv2_stage4_L1" -# type: "Convolution" -# bottom: "Mconv1_stage4_L1" -# top: "Mconv2_stage4_L1" -# param { -# lr_mult: 4.0 -# decay_mult: 1 -# } -# param { -# lr_mult: 8.0 -# decay_mult: 0 -# } -# convolution_param { -# num_output: 128 -# pad: 3 -# kernel_size: 7 -# weight_filler { -# type: "gaussian" -# std: 0.01 -# } -# bias_filler { -# type: "constant" -# } -# } -# } -# layer { -# name: "Mrelu2_stage4_L1" -# type: "ReLU" -# bottom: "Mconv2_stage4_L1" -# top: "Mconv2_stage4_L1" -# } -layer { - name: "Mconv2_stage4_L2" - type: "Convolution" - bottom: "Mconv1_stage4_L2" - top: "Mconv2_stage4_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu2_stage4_L2" - type: "ReLU" - bottom: "Mconv2_stage4_L2" - top: "Mconv2_stage4_L2" -} -# layer { -# name: "Mconv3_stage4_L1" -# type: "Convolution" -# bottom: "Mconv2_stage4_L1" -# top: "Mconv3_stage4_L1" -# param { -# lr_mult: 4.0 -# decay_mult: 1 -# } -# param { -# lr_mult: 8.0 -# decay_mult: 0 -# } -# convolution_param { -# num_output: 128 -# pad: 3 -# kernel_size: 7 -# weight_filler { -# type: "gaussian" -# std: 0.01 -# } -# bias_filler { -# type: "constant" -# } -# } -# } -# layer { -# name: "Mrelu3_stage4_L1" -# type: "ReLU" -# bottom: "Mconv3_stage4_L1" -# top: "Mconv3_stage4_L1" -# } -layer { - name: "Mconv3_stage4_L2" - type: "Convolution" - bottom: "Mconv2_stage4_L2" - top: "Mconv3_stage4_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu3_stage4_L2" - type: "ReLU" - bottom: "Mconv3_stage4_L2" - top: "Mconv3_stage4_L2" -} -# layer { -# name: "Mconv4_stage4_L1" -# type: "Convolution" -# bottom: "Mconv3_stage4_L1" -# top: "Mconv4_stage4_L1" -# param { -# lr_mult: 4.0 -# decay_mult: 1 -# } -# param { -# lr_mult: 8.0 -# decay_mult: 0 -# } -# convolution_param { -# num_output: 128 -# pad: 3 -# kernel_size: 7 -# weight_filler { -# type: "gaussian" -# std: 0.01 -# } -# bias_filler { -# type: "constant" -# } -# } -# } -# layer { -# name: "Mrelu4_stage4_L1" -# type: "ReLU" -# bottom: "Mconv4_stage4_L1" -# top: "Mconv4_stage4_L1" -# } -layer { - name: "Mconv4_stage4_L2" - type: "Convolution" - bottom: "Mconv3_stage4_L2" - top: "Mconv4_stage4_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu4_stage4_L2" - type: "ReLU" - bottom: "Mconv4_stage4_L2" - top: "Mconv4_stage4_L2" -} -# layer { -# name: "Mconv5_stage4_L1" -# type: "Convolution" -# bottom: "Mconv4_stage4_L1" -# top: "Mconv5_stage4_L1" -# param { -# lr_mult: 4.0 -# decay_mult: 1 -# } -# param { -# lr_mult: 8.0 -# decay_mult: 0 -# } -# convolution_param { -# num_output: 128 -# pad: 3 -# kernel_size: 7 -# weight_filler { -# type: "gaussian" -# std: 0.01 -# } -# bias_filler { -# type: "constant" -# } -# } -# } -# layer { -# name: "Mrelu5_stage4_L1" -# type: "ReLU" -# bottom: "Mconv5_stage4_L1" -# top: "Mconv5_stage4_L1" -# } -layer { - name: "Mconv5_stage4_L2" - type: "Convolution" - bottom: "Mconv4_stage4_L2" - top: "Mconv5_stage4_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 3 - kernel_size: 7 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu5_stage4_L2" - type: "ReLU" - bottom: "Mconv5_stage4_L2" - top: "Mconv5_stage4_L2" -} -# layer { -# name: "Mconv6_stage4_L1" -# type: "Convolution" -# bottom: "Mconv5_stage4_L1" -# top: "Mconv6_stage4_L1" -# param { -# lr_mult: 4.0 -# decay_mult: 1 -# } -# param { -# lr_mult: 8.0 -# decay_mult: 0 -# } -# convolution_param { -# num_output: 128 -# pad: 0 -# kernel_size: 1 -# weight_filler { -# type: "gaussian" -# std: 0.01 -# } -# bias_filler { -# type: "constant" -# } -# } -# } -# layer { -# name: "Mrelu6_stage4_L1" -# type: "ReLU" -# bottom: "Mconv6_stage4_L1" -# top: "Mconv6_stage4_L1" -# } -layer { - name: "Mconv6_stage4_L2" - type: "Convolution" - bottom: "Mconv5_stage4_L2" - top: "Mconv6_stage4_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -layer { - name: "Mrelu6_stage4_L2" - type: "ReLU" - bottom: "Mconv6_stage4_L2" - top: "Mconv6_stage4_L2" -} -# layer { -# name: "Mconv7_stage4_L1" -# type: "Convolution" -# bottom: "Mconv6_stage4_L1" -# top: "Mconv7_stage4_L1" -# param { -# lr_mult: 4.0 -# decay_mult: 1 -# } -# param { -# lr_mult: 8.0 -# decay_mult: 0 -# } -# convolution_param { -# num_output: 28 -# pad: 0 -# kernel_size: 1 -# weight_filler { -# type: "gaussian" -# std: 0.01 -# } -# bias_filler { -# type: "constant" -# } -# } -# } -layer { - name: "Mconv7_stage4_L2" - type: "Convolution" - bottom: "Mconv6_stage4_L2" - top: "Mconv7_stage4_L2" - param { - lr_mult: 4.0 - decay_mult: 1 - } - param { - lr_mult: 8.0 - decay_mult: 0 - } - convolution_param { - num_output: 16 - pad: 0 - kernel_size: 1 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - } - } -} -# layer { -# name: "concat_stage7" -# type: "Concat" -# bottom: "Mconv7_stage4_L2" -# bottom: "Mconv7_stage4_L1" -# top: "net_output" -# concat_param { -# axis: 1 -# } -# } diff --git a/testdata/dnn/rfcn_pascal_voc_resnet50.prototxt b/testdata/dnn/rfcn_pascal_voc_resnet50.prototxt deleted file mode 100644 index 3009c14f0..000000000 --- a/testdata/dnn/rfcn_pascal_voc_resnet50.prototxt +++ /dev/null @@ -1,3888 +0,0 @@ -# Based on https://github.com/YuwenXiong/py-R-FCN/blob/master/models/pascal_voc/ResNet-50/rfcn_end2end/test_agnostic.prototxt -name: "ResNet50" - -input: "data" -input_shape { - dim: 1 - dim: 3 - dim: 224 - dim: 224 -} - -input: "im_info" -input_shape { - dim: 1 - dim: 3 -} - -layer { - bottom: "data" - top: "conv1" - name: "conv1" - type: "Convolution" - convolution_param { - num_output: 64 - kernel_size: 7 - pad: 3 - stride: 2 - } - param { - lr_mult: 0.0 - } - param { - lr_mult: 0.0 - } - -} - -layer { - bottom: "conv1" - top: "conv1" - name: "bn_conv1" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "conv1" - top: "conv1" - name: "scale_conv1" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "conv1" - top: "conv1" - name: "conv1_relu" - type: "ReLU" -} - -layer { - bottom: "conv1" - top: "pool1" - name: "pool1" - type: "Pooling" - pooling_param { - kernel_size: 3 - stride: 2 - pool: MAX - } -} - -layer { - bottom: "pool1" - top: "res2a_branch1" - name: "res2a_branch1" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 0.0 - } -} - -layer { - bottom: "res2a_branch1" - top: "res2a_branch1" - name: "bn2a_branch1" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res2a_branch1" - top: "res2a_branch1" - name: "scale2a_branch1" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "pool1" - top: "res2a_branch2a" - name: "res2a_branch2a" - type: "Convolution" - convolution_param { - num_output: 64 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 0.0 - } -} - -layer { - bottom: "res2a_branch2a" - top: "res2a_branch2a" - name: "bn2a_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res2a_branch2a" - top: "res2a_branch2a" - name: "scale2a_branch2a" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res2a_branch2a" - top: "res2a_branch2a" - name: "res2a_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res2a_branch2a" - top: "res2a_branch2b" - name: "res2a_branch2b" - type: "Convolution" - convolution_param { - num_output: 64 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } - param { - lr_mult: 0.0 - } -} - -layer { - bottom: "res2a_branch2b" - top: "res2a_branch2b" - name: "bn2a_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res2a_branch2b" - top: "res2a_branch2b" - name: "scale2a_branch2b" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res2a_branch2b" - top: "res2a_branch2b" - name: "res2a_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res2a_branch2b" - top: "res2a_branch2c" - name: "res2a_branch2c" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 0.0 - } -} - -layer { - bottom: "res2a_branch2c" - top: "res2a_branch2c" - name: "bn2a_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res2a_branch2c" - top: "res2a_branch2c" - name: "scale2a_branch2c" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res2a_branch1" - bottom: "res2a_branch2c" - top: "res2a" - name: "res2a" - type: "Eltwise" -} - -layer { - bottom: "res2a" - top: "res2a" - name: "res2a_relu" - type: "ReLU" -} - -layer { - bottom: "res2a" - top: "res2b_branch2a" - name: "res2b_branch2a" - type: "Convolution" - convolution_param { - num_output: 64 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 0.0 - } -} - -layer { - bottom: "res2b_branch2a" - top: "res2b_branch2a" - name: "bn2b_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res2b_branch2a" - top: "res2b_branch2a" - name: "scale2b_branch2a" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res2b_branch2a" - top: "res2b_branch2a" - name: "res2b_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res2b_branch2a" - top: "res2b_branch2b" - name: "res2b_branch2b" - type: "Convolution" - convolution_param { - num_output: 64 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } - param { - lr_mult: 0.0 - } -} - -layer { - bottom: "res2b_branch2b" - top: "res2b_branch2b" - name: "bn2b_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res2b_branch2b" - top: "res2b_branch2b" - name: "scale2b_branch2b" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res2b_branch2b" - top: "res2b_branch2b" - name: "res2b_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res2b_branch2b" - top: "res2b_branch2c" - name: "res2b_branch2c" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 0.0 - } -} - -layer { - bottom: "res2b_branch2c" - top: "res2b_branch2c" - name: "bn2b_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res2b_branch2c" - top: "res2b_branch2c" - name: "scale2b_branch2c" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res2a" - bottom: "res2b_branch2c" - top: "res2b" - name: "res2b" - type: "Eltwise" -} - -layer { - bottom: "res2b" - top: "res2b" - name: "res2b_relu" - type: "ReLU" -} - -layer { - bottom: "res2b" - top: "res2c_branch2a" - name: "res2c_branch2a" - type: "Convolution" - convolution_param { - num_output: 64 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 0.0 - } -} - -layer { - bottom: "res2c_branch2a" - top: "res2c_branch2a" - name: "bn2c_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res2c_branch2a" - top: "res2c_branch2a" - name: "scale2c_branch2a" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res2c_branch2a" - top: "res2c_branch2a" - name: "res2c_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res2c_branch2a" - top: "res2c_branch2b" - name: "res2c_branch2b" - type: "Convolution" - convolution_param { - num_output: 64 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } - param { - lr_mult: 0.0 - } -} - -layer { - bottom: "res2c_branch2b" - top: "res2c_branch2b" - name: "bn2c_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res2c_branch2b" - top: "res2c_branch2b" - name: "scale2c_branch2b" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res2c_branch2b" - top: "res2c_branch2b" - name: "res2c_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res2c_branch2b" - top: "res2c_branch2c" - name: "res2c_branch2c" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 0.0 - } -} - -layer { - bottom: "res2c_branch2c" - top: "res2c_branch2c" - name: "bn2c_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res2c_branch2c" - top: "res2c_branch2c" - name: "scale2c_branch2c" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res2b" - bottom: "res2c_branch2c" - top: "res2c" - name: "res2c" - type: "Eltwise" -} - -layer { - bottom: "res2c" - top: "res2c" - name: "res2c_relu" - type: "ReLU" -} - -layer { - bottom: "res2c" - top: "res3a_branch1" - name: "res3a_branch1" - type: "Convolution" - convolution_param { - num_output: 512 - kernel_size: 1 - pad: 0 - stride: 2 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res3a_branch1" - top: "res3a_branch1" - name: "bn3a_branch1" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res3a_branch1" - top: "res3a_branch1" - name: "scale3a_branch1" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res2c" - top: "res3a_branch2a" - name: "res3a_branch2a" - type: "Convolution" - convolution_param { - num_output: 128 - kernel_size: 1 - pad: 0 - stride: 2 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res3a_branch2a" - top: "res3a_branch2a" - name: "bn3a_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res3a_branch2a" - top: "res3a_branch2a" - name: "scale3a_branch2a" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res3a_branch2a" - top: "res3a_branch2a" - name: "res3a_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res3a_branch2a" - top: "res3a_branch2b" - name: "res3a_branch2b" - type: "Convolution" - convolution_param { - num_output: 128 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res3a_branch2b" - top: "res3a_branch2b" - name: "bn3a_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res3a_branch2b" - top: "res3a_branch2b" - name: "scale3a_branch2b" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res3a_branch2b" - top: "res3a_branch2b" - name: "res3a_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res3a_branch2b" - top: "res3a_branch2c" - name: "res3a_branch2c" - type: "Convolution" - convolution_param { - num_output: 512 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res3a_branch2c" - top: "res3a_branch2c" - name: "bn3a_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res3a_branch2c" - top: "res3a_branch2c" - name: "scale3a_branch2c" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res3a_branch1" - bottom: "res3a_branch2c" - top: "res3a" - name: "res3a" - type: "Eltwise" -} - -layer { - bottom: "res3a" - top: "res3a" - name: "res3a_relu" - type: "ReLU" -} - -layer { - bottom: "res3a" - top: "res3b_branch2a" - name: "res3b_branch2a" - type: "Convolution" - convolution_param { - num_output: 128 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res3b_branch2a" - top: "res3b_branch2a" - name: "bn3b_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res3b_branch2a" - top: "res3b_branch2a" - name: "scale3b_branch2a" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res3b_branch2a" - top: "res3b_branch2a" - name: "res3b_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res3b_branch2a" - top: "res3b_branch2b" - name: "res3b_branch2b" - type: "Convolution" - convolution_param { - num_output: 128 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res3b_branch2b" - top: "res3b_branch2b" - name: "bn3b_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res3b_branch2b" - top: "res3b_branch2b" - name: "scale3b_branch2b" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res3b_branch2b" - top: "res3b_branch2b" - name: "res3b_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res3b_branch2b" - top: "res3b_branch2c" - name: "res3b_branch2c" - type: "Convolution" - convolution_param { - num_output: 512 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res3b_branch2c" - top: "res3b_branch2c" - name: "bn3b_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res3b_branch2c" - top: "res3b_branch2c" - name: "scale3b_branch2c" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res3a" - bottom: "res3b_branch2c" - top: "res3b" - name: "res3b" - type: "Eltwise" -} - -layer { - bottom: "res3b" - top: "res3b" - name: "res3b_relu" - type: "ReLU" -} - -layer { - bottom: "res3b" - top: "res3c_branch2a" - name: "res3c_branch2a" - type: "Convolution" - convolution_param { - num_output: 128 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res3c_branch2a" - top: "res3c_branch2a" - name: "bn3c_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res3c_branch2a" - top: "res3c_branch2a" - name: "scale3c_branch2a" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res3c_branch2a" - top: "res3c_branch2a" - name: "res3c_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res3c_branch2a" - top: "res3c_branch2b" - name: "res3c_branch2b" - type: "Convolution" - convolution_param { - num_output: 128 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res3c_branch2b" - top: "res3c_branch2b" - name: "bn3c_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res3c_branch2b" - top: "res3c_branch2b" - name: "scale3c_branch2b" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res3c_branch2b" - top: "res3c_branch2b" - name: "res3c_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res3c_branch2b" - top: "res3c_branch2c" - name: "res3c_branch2c" - type: "Convolution" - convolution_param { - num_output: 512 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res3c_branch2c" - top: "res3c_branch2c" - name: "bn3c_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res3c_branch2c" - top: "res3c_branch2c" - name: "scale3c_branch2c" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res3b" - bottom: "res3c_branch2c" - top: "res3c" - name: "res3c" - type: "Eltwise" -} - -layer { - bottom: "res3c" - top: "res3c" - name: "res3c_relu" - type: "ReLU" -} - -layer { - bottom: "res3c" - top: "res3d_branch2a" - name: "res3d_branch2a" - type: "Convolution" - convolution_param { - num_output: 128 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res3d_branch2a" - top: "res3d_branch2a" - name: "bn3d_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res3d_branch2a" - top: "res3d_branch2a" - name: "scale3d_branch2a" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res3d_branch2a" - top: "res3d_branch2a" - name: "res3d_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res3d_branch2a" - top: "res3d_branch2b" - name: "res3d_branch2b" - type: "Convolution" - convolution_param { - num_output: 128 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res3d_branch2b" - top: "res3d_branch2b" - name: "bn3d_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res3d_branch2b" - top: "res3d_branch2b" - name: "scale3d_branch2b" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res3d_branch2b" - top: "res3d_branch2b" - name: "res3d_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res3d_branch2b" - top: "res3d_branch2c" - name: "res3d_branch2c" - type: "Convolution" - convolution_param { - num_output: 512 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res3d_branch2c" - top: "res3d_branch2c" - name: "bn3d_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res3d_branch2c" - top: "res3d_branch2c" - name: "scale3d_branch2c" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res3c" - bottom: "res3d_branch2c" - top: "res3d" - name: "res3d" - type: "Eltwise" -} - -layer { - bottom: "res3d" - top: "res3d" - name: "res3d_relu" - type: "ReLU" -} - -layer { - bottom: "res3d" - top: "res4a_branch1" - name: "res4a_branch1" - type: "Convolution" - convolution_param { - num_output: 1024 - kernel_size: 1 - pad: 0 - stride: 2 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res4a_branch1" - top: "res4a_branch1" - name: "bn4a_branch1" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4a_branch1" - top: "res4a_branch1" - name: "scale4a_branch1" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res3d" - top: "res4a_branch2a" - name: "res4a_branch2a" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 1 - pad: 0 - stride: 2 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res4a_branch2a" - top: "res4a_branch2a" - name: "bn4a_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4a_branch2a" - top: "res4a_branch2a" - name: "scale4a_branch2a" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4a_branch2a" - top: "res4a_branch2a" - name: "res4a_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res4a_branch2a" - top: "res4a_branch2b" - name: "res4a_branch2b" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res4a_branch2b" - top: "res4a_branch2b" - name: "bn4a_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4a_branch2b" - top: "res4a_branch2b" - name: "scale4a_branch2b" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4a_branch2b" - top: "res4a_branch2b" - name: "res4a_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res4a_branch2b" - top: "res4a_branch2c" - name: "res4a_branch2c" - type: "Convolution" - convolution_param { - num_output: 1024 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res4a_branch2c" - top: "res4a_branch2c" - name: "bn4a_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4a_branch2c" - top: "res4a_branch2c" - name: "scale4a_branch2c" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4a_branch1" - bottom: "res4a_branch2c" - top: "res4a" - name: "res4a" - type: "Eltwise" -} - -layer { - bottom: "res4a" - top: "res4a" - name: "res4a_relu" - type: "ReLU" -} - -layer { - bottom: "res4a" - top: "res4b_branch2a" - name: "res4b_branch2a" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res4b_branch2a" - top: "res4b_branch2a" - name: "bn4b_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4b_branch2a" - top: "res4b_branch2a" - name: "scale4b_branch2a" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4b_branch2a" - top: "res4b_branch2a" - name: "res4b_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res4b_branch2a" - top: "res4b_branch2b" - name: "res4b_branch2b" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res4b_branch2b" - top: "res4b_branch2b" - name: "bn4b_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4b_branch2b" - top: "res4b_branch2b" - name: "scale4b_branch2b" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4b_branch2b" - top: "res4b_branch2b" - name: "res4b_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res4b_branch2b" - top: "res4b_branch2c" - name: "res4b_branch2c" - type: "Convolution" - convolution_param { - num_output: 1024 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res4b_branch2c" - top: "res4b_branch2c" - name: "bn4b_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4b_branch2c" - top: "res4b_branch2c" - name: "scale4b_branch2c" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4a" - bottom: "res4b_branch2c" - top: "res4b" - name: "res4b" - type: "Eltwise" -} - -layer { - bottom: "res4b" - top: "res4b" - name: "res4b_relu" - type: "ReLU" -} - -layer { - bottom: "res4b" - top: "res4c_branch2a" - name: "res4c_branch2a" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res4c_branch2a" - top: "res4c_branch2a" - name: "bn4c_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4c_branch2a" - top: "res4c_branch2a" - name: "scale4c_branch2a" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4c_branch2a" - top: "res4c_branch2a" - name: "res4c_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res4c_branch2a" - top: "res4c_branch2b" - name: "res4c_branch2b" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res4c_branch2b" - top: "res4c_branch2b" - name: "bn4c_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4c_branch2b" - top: "res4c_branch2b" - name: "scale4c_branch2b" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4c_branch2b" - top: "res4c_branch2b" - name: "res4c_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res4c_branch2b" - top: "res4c_branch2c" - name: "res4c_branch2c" - type: "Convolution" - convolution_param { - num_output: 1024 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res4c_branch2c" - top: "res4c_branch2c" - name: "bn4c_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4c_branch2c" - top: "res4c_branch2c" - name: "scale4c_branch2c" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4b" - bottom: "res4c_branch2c" - top: "res4c" - name: "res4c" - type: "Eltwise" -} - -layer { - bottom: "res4c" - top: "res4c" - name: "res4c_relu" - type: "ReLU" -} - -layer { - bottom: "res4c" - top: "res4d_branch2a" - name: "res4d_branch2a" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res4d_branch2a" - top: "res4d_branch2a" - name: "bn4d_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4d_branch2a" - top: "res4d_branch2a" - name: "scale4d_branch2a" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4d_branch2a" - top: "res4d_branch2a" - name: "res4d_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res4d_branch2a" - top: "res4d_branch2b" - name: "res4d_branch2b" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res4d_branch2b" - top: "res4d_branch2b" - name: "bn4d_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4d_branch2b" - top: "res4d_branch2b" - name: "scale4d_branch2b" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4d_branch2b" - top: "res4d_branch2b" - name: "res4d_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res4d_branch2b" - top: "res4d_branch2c" - name: "res4d_branch2c" - type: "Convolution" - convolution_param { - num_output: 1024 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res4d_branch2c" - top: "res4d_branch2c" - name: "bn4d_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4d_branch2c" - top: "res4d_branch2c" - name: "scale4d_branch2c" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4c" - bottom: "res4d_branch2c" - top: "res4d" - name: "res4d" - type: "Eltwise" -} - -layer { - bottom: "res4d" - top: "res4d" - name: "res4d_relu" - type: "ReLU" -} - -layer { - bottom: "res4d" - top: "res4e_branch2a" - name: "res4e_branch2a" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res4e_branch2a" - top: "res4e_branch2a" - name: "bn4e_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4e_branch2a" - top: "res4e_branch2a" - name: "scale4e_branch2a" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4e_branch2a" - top: "res4e_branch2a" - name: "res4e_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res4e_branch2a" - top: "res4e_branch2b" - name: "res4e_branch2b" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res4e_branch2b" - top: "res4e_branch2b" - name: "bn4e_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4e_branch2b" - top: "res4e_branch2b" - name: "scale4e_branch2b" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4e_branch2b" - top: "res4e_branch2b" - name: "res4e_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res4e_branch2b" - top: "res4e_branch2c" - name: "res4e_branch2c" - type: "Convolution" - convolution_param { - num_output: 1024 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res4e_branch2c" - top: "res4e_branch2c" - name: "bn4e_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4e_branch2c" - top: "res4e_branch2c" - name: "scale4e_branch2c" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4d" - bottom: "res4e_branch2c" - top: "res4e" - name: "res4e" - type: "Eltwise" -} - -layer { - bottom: "res4e" - top: "res4e" - name: "res4e_relu" - type: "ReLU" -} - -layer { - bottom: "res4e" - top: "res4f_branch2a" - name: "res4f_branch2a" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res4f_branch2a" - top: "res4f_branch2a" - name: "bn4f_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4f_branch2a" - top: "res4f_branch2a" - name: "scale4f_branch2a" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4f_branch2a" - top: "res4f_branch2a" - name: "res4f_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res4f_branch2a" - top: "res4f_branch2b" - name: "res4f_branch2b" - type: "Convolution" - convolution_param { - num_output: 256 - kernel_size: 3 - pad: 1 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res4f_branch2b" - top: "res4f_branch2b" - name: "bn4f_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4f_branch2b" - top: "res4f_branch2b" - name: "scale4f_branch2b" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4f_branch2b" - top: "res4f_branch2b" - name: "res4f_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res4f_branch2b" - top: "res4f_branch2c" - name: "res4f_branch2c" - type: "Convolution" - convolution_param { - num_output: 1024 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res4f_branch2c" - top: "res4f_branch2c" - name: "bn4f_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4f_branch2c" - top: "res4f_branch2c" - name: "scale4f_branch2c" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4e" - bottom: "res4f_branch2c" - top: "res4f" - name: "res4f" - type: "Eltwise" -} - -layer { - bottom: "res4f" - top: "res4f" - name: "res4f_relu" - type: "ReLU" -} - -layer { - bottom: "res4f" - top: "res5a_branch1" - name: "res5a_branch1" - type: "Convolution" - convolution_param { - num_output: 2048 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res5a_branch1" - top: "res5a_branch1" - name: "bn5a_branch1" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res5a_branch1" - top: "res5a_branch1" - name: "scale5a_branch1" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res4f" - top: "res5a_branch2a" - name: "res5a_branch2a" - type: "Convolution" - convolution_param { - num_output: 512 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res5a_branch2a" - top: "res5a_branch2a" - name: "bn5a_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res5a_branch2a" - top: "res5a_branch2a" - name: "scale5a_branch2a" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res5a_branch2a" - top: "res5a_branch2a" - name: "res5a_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res5a_branch2a" - top: "res5a_branch2b" - name: "res5a_branch2b" - type: "Convolution" - convolution_param { - num_output: 512 - kernel_size: 3 - dilation: 2 - pad: 2 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res5a_branch2b" - top: "res5a_branch2b" - name: "bn5a_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res5a_branch2b" - top: "res5a_branch2b" - name: "scale5a_branch2b" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res5a_branch2b" - top: "res5a_branch2b" - name: "res5a_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res5a_branch2b" - top: "res5a_branch2c" - name: "res5a_branch2c" - type: "Convolution" - convolution_param { - num_output: 2048 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res5a_branch2c" - top: "res5a_branch2c" - name: "bn5a_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res5a_branch2c" - top: "res5a_branch2c" - name: "scale5a_branch2c" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res5a_branch1" - bottom: "res5a_branch2c" - top: "res5a" - name: "res5a" - type: "Eltwise" -} - -layer { - bottom: "res5a" - top: "res5a" - name: "res5a_relu" - type: "ReLU" -} - -layer { - bottom: "res5a" - top: "res5b_branch2a" - name: "res5b_branch2a" - type: "Convolution" - convolution_param { - num_output: 512 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res5b_branch2a" - top: "res5b_branch2a" - name: "bn5b_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res5b_branch2a" - top: "res5b_branch2a" - name: "scale5b_branch2a" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res5b_branch2a" - top: "res5b_branch2a" - name: "res5b_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res5b_branch2a" - top: "res5b_branch2b" - name: "res5b_branch2b" - type: "Convolution" - convolution_param { - num_output: 512 - kernel_size: 3 - dilation: 2 - pad: 2 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res5b_branch2b" - top: "res5b_branch2b" - name: "bn5b_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res5b_branch2b" - top: "res5b_branch2b" - name: "scale5b_branch2b" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res5b_branch2b" - top: "res5b_branch2b" - name: "res5b_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res5b_branch2b" - top: "res5b_branch2c" - name: "res5b_branch2c" - type: "Convolution" - convolution_param { - num_output: 2048 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res5b_branch2c" - top: "res5b_branch2c" - name: "bn5b_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res5b_branch2c" - top: "res5b_branch2c" - name: "scale5b_branch2c" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res5a" - bottom: "res5b_branch2c" - top: "res5b" - name: "res5b" - type: "Eltwise" -} - -layer { - bottom: "res5b" - top: "res5b" - name: "res5b_relu" - type: "ReLU" -} - -layer { - bottom: "res5b" - top: "res5c_branch2a" - name: "res5c_branch2a" - type: "Convolution" - convolution_param { - num_output: 512 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res5c_branch2a" - top: "res5c_branch2a" - name: "bn5c_branch2a" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res5c_branch2a" - top: "res5c_branch2a" - name: "scale5c_branch2a" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res5c_branch2a" - top: "res5c_branch2a" - name: "res5c_branch2a_relu" - type: "ReLU" -} - -layer { - bottom: "res5c_branch2a" - top: "res5c_branch2b" - name: "res5c_branch2b" - type: "Convolution" - convolution_param { - num_output: 512 - kernel_size: 3 - dilation: 2 - pad: 2 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res5c_branch2b" - top: "res5c_branch2b" - name: "bn5c_branch2b" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res5c_branch2b" - top: "res5c_branch2b" - name: "scale5c_branch2b" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res5c_branch2b" - top: "res5c_branch2b" - name: "res5c_branch2b_relu" - type: "ReLU" -} - -layer { - bottom: "res5c_branch2b" - top: "res5c_branch2c" - name: "res5c_branch2c" - type: "Convolution" - convolution_param { - num_output: 2048 - kernel_size: 1 - pad: 0 - stride: 1 - bias_term: false - } - param { - lr_mult: 1.0 - } -} - -layer { - bottom: "res5c_branch2c" - top: "res5c_branch2c" - name: "bn5c_branch2c" - type: "BatchNorm" - batch_norm_param { - use_global_stats: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res5c_branch2c" - top: "res5c_branch2c" - name: "scale5c_branch2c" - type: "Scale" - scale_param { - bias_term: true - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } - param { - lr_mult: 0.0 - decay_mult: 0.0 - } -} - -layer { - bottom: "res5b" - bottom: "res5c_branch2c" - top: "res5c" - name: "res5c" - type: "Eltwise" -} - -layer { - bottom: "res5c" - top: "res5c" - name: "res5c_relu" - type: "ReLU" -} - -#========= RPN ============ - -layer { - name: "rpn_conv/3x3" - type: "Convolution" - bottom: "res4f" - top: "rpn/output" - param { lr_mult: 1.0 decay_mult: 1.0 } - param { lr_mult: 2.0 decay_mult: 0 } - convolution_param { - num_output: 512 - kernel_size: 3 pad: 1 stride: 1 - weight_filler { type: "gaussian" std: 0.01 } - bias_filler { type: "constant" value: 0 } - } -} -layer { - name: "rpn_relu/3x3" - type: "ReLU" - bottom: "rpn/output" - top: "rpn/output" -} - -layer { - name: "rpn_cls_score" - type: "Convolution" - bottom: "rpn/output" - top: "rpn_cls_score" - param { lr_mult: 1.0 decay_mult: 1.0 } - param { lr_mult: 2.0 decay_mult: 0 } - convolution_param { - num_output: 18 # 2(bg/fg) * 9(anchors) - kernel_size: 1 pad: 0 stride: 1 - weight_filler { type: "gaussian" std: 0.01 } - bias_filler { type: "constant" value: 0 } - } -} -layer { - name: "rpn_bbox_pred" - type: "Convolution" - bottom: "rpn/output" - top: "rpn_bbox_pred" - param { lr_mult: 1.0 decay_mult: 1.0 } - param { lr_mult: 2.0 decay_mult: 0 } - convolution_param { - num_output: 36 # 4 * 9(anchors) - kernel_size: 1 pad: 0 stride: 1 - weight_filler { type: "gaussian" std: 0.01 } - bias_filler { type: "constant" value: 0 } - } -} -layer { - bottom: "rpn_cls_score" - top: "rpn_cls_score_reshape" - name: "rpn_cls_score_reshape" - type: "Reshape" - reshape_param { shape { dim: 0 dim: 2 dim: -1 dim: 0 } } -} - -#========= RoI Proposal ============ - -layer { - name: "rpn_cls_prob" - type: "Softmax" - bottom: "rpn_cls_score_reshape" - top: "rpn_cls_prob" -} -layer { - name: 'rpn_cls_prob_reshape' - type: 'Reshape' - bottom: 'rpn_cls_prob' - top: 'rpn_cls_prob_reshape' - reshape_param { shape { dim: 0 dim: 18 dim: -1 dim: 0 } } -} -layer { - name: "proposal" - type: "Proposal" - bottom: "rpn_cls_prob_reshape" - bottom: "rpn_bbox_pred" - bottom: "im_info" - top: "rois" - proposal_param { - feat_stride: 16 - base_size: 16 - min_size: 16 - ratio: 0.5 - ratio: 1.0 - ratio: 2.0 - scale: 8 - scale: 16 - scale: 32 - pre_nms_topn: 6000 - post_nms_topn: 300 - nms_thresh: 0.6 - } -} - -#----------------------new conv layer------------------ -layer { - bottom: "res5c" - top: "conv_new_1" - name: "conv_new_1" - type: "Convolution" - convolution_param { - num_output: 1024 - kernel_size: 1 - pad: 0 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - value: 0 - } - } - param { - lr_mult: 1.0 - } - param { - lr_mult: 2.0 - } -} - -layer { - bottom: "conv_new_1" - top: "conv_new_1" - name: "conv_new_1_relu" - type: "ReLU" -} - -layer { - bottom: "conv_new_1" - top: "rfcn_cls" - name: "rfcn_cls" - type: "Convolution" - convolution_param { - num_output: 1029 #21*(7^2) cls_num*(score_maps_size^2) - kernel_size: 1 - pad: 0 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - value: 0 - } - } - param { - lr_mult: 1.0 - } - param { - lr_mult: 2.0 - } -} -layer { - bottom: "conv_new_1" - top: "rfcn_bbox" - name: "rfcn_bbox" - type: "Convolution" - convolution_param { - num_output: 392 #2*4*(7^2) (bg/fg)*(dx, dy, dw, dh)*(score_maps_size^2) - kernel_size: 1 - pad: 0 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - value: 0 - } - } - param { - lr_mult: 1.0 - } - param { - lr_mult: 2.0 - } -} - -#--------------position sensitive RoI pooling-------------- -layer { - bottom: "rfcn_cls" - bottom: "rois" - top: "psroipooled_cls_rois" - name: "psroipooled_cls_rois" - type: "PSROIPooling" - psroi_pooling_param { - spatial_scale: 0.0625 - output_dim: 21 - group_size: 7 - } -} - -layer { - bottom: "psroipooled_cls_rois" - top: "cls_score" - name: "ave_cls_score_rois" - type: "Pooling" - pooling_param { - pool: AVE - kernel_size: 7 - stride: 7 - } -} - - -layer { - bottom: "rfcn_bbox" - bottom: "rois" - top: "psroipooled_loc_rois" - name: "psroipooled_loc_rois" - type: "PSROIPooling" - psroi_pooling_param { - spatial_scale: 0.0625 - output_dim: 8 - group_size: 7 - } -} - -layer { - bottom: "psroipooled_loc_rois" - top: "bbox_pred_pre" - name: "ave_bbox_pred_rois" - type: "Pooling" - pooling_param { - pool: AVE - kernel_size: 7 - stride: 7 - } -} - - -#-----------------------output------------------------ -layer { - name: "cls_prob" - type: "Softmax" - bottom: "cls_score" - top: "cls_prob_pre" -} - -# ======= Postprocessing ======== -layer { - name: "cls_prob_reshape" - type: "Reshape" - bottom: "cls_prob_pre" - top: "cls_prob_reshape" - reshape_param { - shape { - dim: 1 - dim: -1 - } - } -} -layer { - name: "bbox_pred_reshape" - type: "Reshape" - bottom: "bbox_pred_pre" - top: "bbox_pred_reshape" - reshape_param { - shape { - dim: 1 - dim: -1 - dim: 8 - dim: 1 - } - } -} -layer { - name: "bbox_pred_target_shape" - type: "Reshape" - bottom: "bbox_pred_pre" - top: "bbox_pred_target_shape" - reshape_param { - shape { - dim: 1 - dim: -1 - dim: 4 - dim: 1 - } - } -} -# Split to background bounding boxes predictions and objects. -layer { - name: "bbox_pred_fg" - type: "Crop" - bottom: "bbox_pred_reshape" - bottom: "bbox_pred_target_shape" - top: "bbox_pred_fg" - crop_param { - axis: 2 - offset: 4 - offset: 0 - } -} -# Reshape proposals to [1 x numPriors x 5 x 1]. -layer { - name: "rois_reshape" - type: "Reshape" - bottom: "rois" - top: "rois_reshape" - reshape_param { - shape { - dim: 1 - dim: -1 - dim: 5 - dim: 1 - } - } -} -# Proposal layer generates [numPriors x 5] blob where 0th column are batch indices -# and only the rest are bounding boxes. -layer { - name: "proposal_crop" - type: "Crop" - bottom: "rois_reshape" - bottom: "bbox_pred_fg" - top: "proposal_bboxes" - crop_param { - axis: 2 - offset: 1 - offset: 0 - } -} -# Reshape it to [1 x 1 x numPriors*4 x 1] -layer { - name: "proposal_reshape" - type: "Reshape" - bottom: "proposal_bboxes" - top: "proposal_reshape" - reshape_param { - shape { - dim: 1 - dim: 1 - dim: -1 - dim: 1 # Reshape to 4d to enable clDNN from Intel's Inference Engine - } - } -} -layer { - name: "detection_out" - type: "DetectionOutput" - bottom: "bbox_pred_fg" - bottom: "cls_prob_reshape" - bottom: "proposal_reshape" - top: "detection_out" - detection_output_param { - num_classes: 21 - share_location: true - background_label_id: 0 - nms_param { - nms_threshold: 0.3 - } - code_type: CENTER_SIZE - keep_top_k: 100 - variance_encoded_in_target: true - normalized_bbox: false - } -} diff --git a/testdata/dnn/squeezenet_v1.1.prototxt b/testdata/dnn/squeezenet_v1.1.prototxt deleted file mode 100644 index 1c12e69fe..000000000 --- a/testdata/dnn/squeezenet_v1.1.prototxt +++ /dev/null @@ -1,639 +0,0 @@ -# please cite: -# @article{SqueezeNet, -# Author = {Forrest N. Iandola and Matthew W. Moskewicz and Khalid Ashraf and Song Han and William J. Dally and Kurt Keutzer}, -# Title = {SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and $<$1MB model size}, -# Journal = {arXiv:1602.07360}, -# Year = {2016} -# } -input: "data" -input_shape { - dim: 1 - dim: 3 - dim: 227 - dim: 227 -} -layer { - name: "conv1" - type: "Convolution" - bottom: "data" - top: "conv1" - convolution_param { - num_output: 64 - kernel_size: 3 - stride: 2 - weight_filler { - type: "xavier" - } - } -} -layer { - name: "relu_conv1" - type: "ReLU" - bottom: "conv1" - top: "conv1" -} -layer { - name: "pool1" - type: "Pooling" - bottom: "conv1" - top: "pool1" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 2 - } -} -layer { - name: "fire2/squeeze1x1" - type: "Convolution" - bottom: "pool1" - top: "fire2/squeeze1x1" - convolution_param { - num_output: 16 - kernel_size: 1 - weight_filler { - type: "xavier" - } - } -} -layer { - name: "fire2/relu_squeeze1x1" - type: "ReLU" - bottom: "fire2/squeeze1x1" - top: "fire2/squeeze1x1" -} -layer { - name: "fire2/expand1x1" - type: "Convolution" - bottom: "fire2/squeeze1x1" - top: "fire2/expand1x1" - convolution_param { - num_output: 64 - kernel_size: 1 - weight_filler { - type: "xavier" - } - } -} -layer { - name: "fire2/relu_expand1x1" - type: "ReLU" - bottom: "fire2/expand1x1" - top: "fire2/expand1x1" -} -layer { - name: "fire2/expand3x3" - type: "Convolution" - bottom: "fire2/squeeze1x1" - top: "fire2/expand3x3" - convolution_param { - num_output: 64 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - } -} -layer { - name: "fire2/relu_expand3x3" - type: "ReLU" - bottom: "fire2/expand3x3" - top: "fire2/expand3x3" -} -layer { - name: "fire2/concat" - type: "Concat" - bottom: "fire2/expand1x1" - bottom: "fire2/expand3x3" - top: "fire2/concat" -} -layer { - name: "fire3/squeeze1x1" - type: "Convolution" - bottom: "fire2/concat" - top: "fire3/squeeze1x1" - convolution_param { - num_output: 16 - kernel_size: 1 - weight_filler { - type: "xavier" - } - } -} -layer { - name: "fire3/relu_squeeze1x1" - type: "ReLU" - bottom: "fire3/squeeze1x1" - top: "fire3/squeeze1x1" -} -layer { - name: "fire3/expand1x1" - type: "Convolution" - bottom: "fire3/squeeze1x1" - top: "fire3/expand1x1" - convolution_param { - num_output: 64 - kernel_size: 1 - weight_filler { - type: "xavier" - } - } -} -layer { - name: "fire3/relu_expand1x1" - type: "ReLU" - bottom: "fire3/expand1x1" - top: "fire3/expand1x1" -} -layer { - name: "fire3/expand3x3" - type: "Convolution" - bottom: "fire3/squeeze1x1" - top: "fire3/expand3x3" - convolution_param { - num_output: 64 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - } -} -layer { - name: "fire3/relu_expand3x3" - type: "ReLU" - bottom: "fire3/expand3x3" - top: "fire3/expand3x3" -} -layer { - name: "fire3/concat" - type: "Concat" - bottom: "fire3/expand1x1" - bottom: "fire3/expand3x3" - top: "fire3/concat" -} -layer { - name: "pool3" - type: "Pooling" - bottom: "fire3/concat" - top: "pool3" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 2 - } -} -layer { - name: "fire4/squeeze1x1" - type: "Convolution" - bottom: "pool3" - top: "fire4/squeeze1x1" - convolution_param { - num_output: 32 - kernel_size: 1 - weight_filler { - type: "xavier" - } - } -} -layer { - name: "fire4/relu_squeeze1x1" - type: "ReLU" - bottom: "fire4/squeeze1x1" - top: "fire4/squeeze1x1" -} -layer { - name: "fire4/expand1x1" - type: "Convolution" - bottom: "fire4/squeeze1x1" - top: "fire4/expand1x1" - convolution_param { - num_output: 128 - kernel_size: 1 - weight_filler { - type: "xavier" - } - } -} -layer { - name: "fire4/relu_expand1x1" - type: "ReLU" - bottom: "fire4/expand1x1" - top: "fire4/expand1x1" -} -layer { - name: "fire4/expand3x3" - type: "Convolution" - bottom: "fire4/squeeze1x1" - top: "fire4/expand3x3" - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - } -} -layer { - name: "fire4/relu_expand3x3" - type: "ReLU" - bottom: "fire4/expand3x3" - top: "fire4/expand3x3" -} -layer { - name: "fire4/concat" - type: "Concat" - bottom: "fire4/expand1x1" - bottom: "fire4/expand3x3" - top: "fire4/concat" -} -layer { - name: "fire5/squeeze1x1" - type: "Convolution" - bottom: "fire4/concat" - top: "fire5/squeeze1x1" - convolution_param { - num_output: 32 - kernel_size: 1 - weight_filler { - type: "xavier" - } - } -} -layer { - name: "fire5/relu_squeeze1x1" - type: "ReLU" - bottom: "fire5/squeeze1x1" - top: "fire5/squeeze1x1" -} -layer { - name: "fire5/expand1x1" - type: "Convolution" - bottom: "fire5/squeeze1x1" - top: "fire5/expand1x1" - convolution_param { - num_output: 128 - kernel_size: 1 - weight_filler { - type: "xavier" - } - } -} -layer { - name: "fire5/relu_expand1x1" - type: "ReLU" - bottom: "fire5/expand1x1" - top: "fire5/expand1x1" -} -layer { - name: "fire5/expand3x3" - type: "Convolution" - bottom: "fire5/squeeze1x1" - top: "fire5/expand3x3" - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - } -} -layer { - name: "fire5/relu_expand3x3" - type: "ReLU" - bottom: "fire5/expand3x3" - top: "fire5/expand3x3" -} -layer { - name: "fire5/concat" - type: "Concat" - bottom: "fire5/expand1x1" - bottom: "fire5/expand3x3" - top: "fire5/concat" -} -layer { - name: "pool5" - type: "Pooling" - bottom: "fire5/concat" - top: "pool5" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 2 - } -} -layer { - name: "fire6/squeeze1x1" - type: "Convolution" - bottom: "pool5" - top: "fire6/squeeze1x1" - convolution_param { - num_output: 48 - kernel_size: 1 - weight_filler { - type: "xavier" - } - } -} -layer { - name: "fire6/relu_squeeze1x1" - type: "ReLU" - bottom: "fire6/squeeze1x1" - top: "fire6/squeeze1x1" -} -layer { - name: "fire6/expand1x1" - type: "Convolution" - bottom: "fire6/squeeze1x1" - top: "fire6/expand1x1" - convolution_param { - num_output: 192 - kernel_size: 1 - weight_filler { - type: "xavier" - } - } -} -layer { - name: "fire6/relu_expand1x1" - type: "ReLU" - bottom: "fire6/expand1x1" - top: "fire6/expand1x1" -} -layer { - name: "fire6/expand3x3" - type: "Convolution" - bottom: "fire6/squeeze1x1" - top: "fire6/expand3x3" - convolution_param { - num_output: 192 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - } -} -layer { - name: "fire6/relu_expand3x3" - type: "ReLU" - bottom: "fire6/expand3x3" - top: "fire6/expand3x3" -} -layer { - name: "fire6/concat" - type: "Concat" - bottom: "fire6/expand1x1" - bottom: "fire6/expand3x3" - top: "fire6/concat" -} -layer { - name: "fire7/squeeze1x1" - type: "Convolution" - bottom: "fire6/concat" - top: "fire7/squeeze1x1" - convolution_param { - num_output: 48 - kernel_size: 1 - weight_filler { - type: "xavier" - } - } -} -layer { - name: "fire7/relu_squeeze1x1" - type: "ReLU" - bottom: "fire7/squeeze1x1" - top: "fire7/squeeze1x1" -} -layer { - name: "fire7/expand1x1" - type: "Convolution" - bottom: "fire7/squeeze1x1" - top: "fire7/expand1x1" - convolution_param { - num_output: 192 - kernel_size: 1 - weight_filler { - type: "xavier" - } - } -} -layer { - name: "fire7/relu_expand1x1" - type: "ReLU" - bottom: "fire7/expand1x1" - top: "fire7/expand1x1" -} -layer { - name: "fire7/expand3x3" - type: "Convolution" - bottom: "fire7/squeeze1x1" - top: "fire7/expand3x3" - convolution_param { - num_output: 192 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - } -} -layer { - name: "fire7/relu_expand3x3" - type: "ReLU" - bottom: "fire7/expand3x3" - top: "fire7/expand3x3" -} -layer { - name: "fire7/concat" - type: "Concat" - bottom: "fire7/expand1x1" - bottom: "fire7/expand3x3" - top: "fire7/concat" -} -layer { - name: "fire8/squeeze1x1" - type: "Convolution" - bottom: "fire7/concat" - top: "fire8/squeeze1x1" - convolution_param { - num_output: 64 - kernel_size: 1 - weight_filler { - type: "xavier" - } - } -} -layer { - name: "fire8/relu_squeeze1x1" - type: "ReLU" - bottom: "fire8/squeeze1x1" - top: "fire8/squeeze1x1" -} -layer { - name: "fire8/expand1x1" - type: "Convolution" - bottom: "fire8/squeeze1x1" - top: "fire8/expand1x1" - convolution_param { - num_output: 256 - kernel_size: 1 - weight_filler { - type: "xavier" - } - } -} -layer { - name: "fire8/relu_expand1x1" - type: "ReLU" - bottom: "fire8/expand1x1" - top: "fire8/expand1x1" -} -layer { - name: "fire8/expand3x3" - type: "Convolution" - bottom: "fire8/squeeze1x1" - top: "fire8/expand3x3" - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - } -} -layer { - name: "fire8/relu_expand3x3" - type: "ReLU" - bottom: "fire8/expand3x3" - top: "fire8/expand3x3" -} -layer { - name: "fire8/concat" - type: "Concat" - bottom: "fire8/expand1x1" - bottom: "fire8/expand3x3" - top: "fire8/concat" -} -layer { - name: "fire9/squeeze1x1" - type: "Convolution" - bottom: "fire8/concat" - top: "fire9/squeeze1x1" - convolution_param { - num_output: 64 - kernel_size: 1 - weight_filler { - type: "xavier" - } - } -} -layer { - name: "fire9/relu_squeeze1x1" - type: "ReLU" - bottom: "fire9/squeeze1x1" - top: "fire9/squeeze1x1" -} -layer { - name: "fire9/expand1x1" - type: "Convolution" - bottom: "fire9/squeeze1x1" - top: "fire9/expand1x1" - convolution_param { - num_output: 256 - kernel_size: 1 - weight_filler { - type: "xavier" - } - } -} -layer { - name: "fire9/relu_expand1x1" - type: "ReLU" - bottom: "fire9/expand1x1" - top: "fire9/expand1x1" -} -layer { - name: "fire9/expand3x3" - type: "Convolution" - bottom: "fire9/squeeze1x1" - top: "fire9/expand3x3" - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - } -} -layer { - name: "fire9/relu_expand3x3" - type: "ReLU" - bottom: "fire9/expand3x3" - top: "fire9/expand3x3" -} -layer { - name: "fire9/concat" - type: "Concat" - bottom: "fire9/expand1x1" - bottom: "fire9/expand3x3" - top: "fire9/concat" -} -layer { - name: "drop9" - type: "Dropout" - bottom: "fire9/concat" - top: "fire9/concat" - dropout_param { - dropout_ratio: 0.5 - } -} -layer { - name: "conv10" - type: "Convolution" - bottom: "fire9/concat" - top: "conv10" - convolution_param { - num_output: 1000 - kernel_size: 1 - weight_filler { - type: "gaussian" - mean: 0.0 - std: 0.01 - } - } -} -layer { - name: "relu_conv10" - type: "ReLU" - bottom: "conv10" - top: "conv10" -} -layer { - name: "pool10" - type: "Pooling" - bottom: "conv10" - top: "pool10" - pooling_param { - pool: AVE - global_pooling: true - } -} -layer { - bottom: "pool10" - top: "pool10_flatten" - name: "pool10_flatten" - type: "Flatten" -} -layer { - bottom: "pool10_flatten" - top: "prob" - name: "prob" - type: "Softmax" -} diff --git a/testdata/dnn/ssd_vgg16.prototxt b/testdata/dnn/ssd_vgg16.prototxt deleted file mode 100644 index 750d7c52a..000000000 --- a/testdata/dnn/ssd_vgg16.prototxt +++ /dev/null @@ -1,1615 +0,0 @@ -name: "VGG_ILSVRC2016_SSD_300x300_deploy" -input: "data" -input_shape { - dim: 1 - dim: 3 - dim: 300 - dim: 300 -} -layer { - name: "conv1_1" - type: "Convolution" - bottom: "data" - top: "conv1_1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "relu1_1" - type: "ReLU" - bottom: "conv1_1" - top: "conv1_1" -} -layer { - name: "conv1_2" - type: "Convolution" - bottom: "conv1_1" - top: "conv1_2" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "relu1_2" - type: "ReLU" - bottom: "conv1_2" - top: "conv1_2" -} -layer { - name: "pool1" - type: "Pooling" - bottom: "conv1_2" - top: "pool1" - pooling_param { - pool: MAX - kernel_size: 2 - stride: 2 - } -} -layer { - name: "conv2_1" - type: "Convolution" - bottom: "pool1" - top: "conv2_1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "relu2_1" - type: "ReLU" - bottom: "conv2_1" - top: "conv2_1" -} -layer { - name: "conv2_2" - type: "Convolution" - bottom: "conv2_1" - top: "conv2_2" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "relu2_2" - type: "ReLU" - bottom: "conv2_2" - top: "conv2_2" -} -layer { - name: "pool2" - type: "Pooling" - bottom: "conv2_2" - top: "pool2" - pooling_param { - pool: MAX - kernel_size: 2 - stride: 2 - } -} -layer { - name: "conv3_1" - type: "Convolution" - bottom: "pool2" - top: "conv3_1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "relu3_1" - type: "ReLU" - bottom: "conv3_1" - top: "conv3_1" -} -layer { - name: "conv3_2" - type: "Convolution" - bottom: "conv3_1" - top: "conv3_2" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "relu3_2" - type: "ReLU" - bottom: "conv3_2" - top: "conv3_2" -} -layer { - name: "conv3_3" - type: "Convolution" - bottom: "conv3_2" - top: "conv3_3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "relu3_3" - type: "ReLU" - bottom: "conv3_3" - top: "conv3_3" -} -layer { - name: "pool3" - type: "Pooling" - bottom: "conv3_3" - top: "pool3" - pooling_param { - pool: MAX - kernel_size: 2 - stride: 2 - } -} -layer { - name: "conv4_1" - type: "Convolution" - bottom: "pool3" - top: "conv4_1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 512 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "relu4_1" - type: "ReLU" - bottom: "conv4_1" - top: "conv4_1" -} -layer { - name: "conv4_2" - type: "Convolution" - bottom: "conv4_1" - top: "conv4_2" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 512 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "relu4_2" - type: "ReLU" - bottom: "conv4_2" - top: "conv4_2" -} -layer { - name: "conv4_3" - type: "Convolution" - bottom: "conv4_2" - top: "conv4_3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 512 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "relu4_3" - type: "ReLU" - bottom: "conv4_3" - top: "conv4_3" -} -layer { - name: "pool4" - type: "Pooling" - bottom: "conv4_3" - top: "pool4" - pooling_param { - pool: MAX - kernel_size: 2 - stride: 2 - } -} -layer { - name: "conv5_1" - type: "Convolution" - bottom: "pool4" - top: "conv5_1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 512 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "relu5_1" - type: "ReLU" - bottom: "conv5_1" - top: "conv5_1" -} -layer { - name: "conv5_2" - type: "Convolution" - bottom: "conv5_1" - top: "conv5_2" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 512 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "relu5_2" - type: "ReLU" - bottom: "conv5_2" - top: "conv5_2" -} -layer { - name: "conv5_3" - type: "Convolution" - bottom: "conv5_2" - top: "conv5_3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 512 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "relu5_3" - type: "ReLU" - bottom: "conv5_3" - top: "conv5_3" -} -layer { - name: "pool5" - type: "Pooling" - bottom: "conv5_3" - top: "pool5" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - name: "fc6" - type: "Convolution" - bottom: "pool5" - top: "fc6" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 1024 - pad: 6 - kernel_size: 3 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - dilation: 6 - } -} -layer { - name: "relu6" - type: "ReLU" - bottom: "fc6" - top: "fc6" -} -layer { - name: "fc7" - type: "Convolution" - bottom: "fc6" - top: "fc7" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 1024 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "relu7" - type: "ReLU" - bottom: "fc7" - top: "fc7" -} -layer { - name: "conv6_1" - type: "Convolution" - bottom: "fc7" - top: "conv6_1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv6_1_relu" - type: "ReLU" - bottom: "conv6_1" - top: "conv6_1" -} -layer { - name: "conv6_2" - type: "Convolution" - bottom: "conv6_1" - top: "conv6_2" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 512 - pad: 1 - kernel_size: 3 - stride: 2 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv6_2_relu" - type: "ReLU" - bottom: "conv6_2" - top: "conv6_2" -} -layer { - name: "conv7_1" - type: "Convolution" - bottom: "conv6_2" - top: "conv7_1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv7_1_relu" - type: "ReLU" - bottom: "conv7_1" - top: "conv7_1" -} -layer { - name: "conv7_2" - type: "Convolution" - bottom: "conv7_1" - top: "conv7_2" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - stride: 2 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv7_2_relu" - type: "ReLU" - bottom: "conv7_2" - top: "conv7_2" -} -layer { - name: "conv8_1" - type: "Convolution" - bottom: "conv7_2" - top: "conv8_1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv8_1_relu" - type: "ReLU" - bottom: "conv8_1" - top: "conv8_1" -} -layer { - name: "conv8_2" - type: "Convolution" - bottom: "conv8_1" - top: "conv8_2" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 0 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv8_2_relu" - type: "ReLU" - bottom: "conv8_2" - top: "conv8_2" -} -layer { - name: "conv9_1" - type: "Convolution" - bottom: "conv8_2" - top: "conv9_1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv9_1_relu" - type: "ReLU" - bottom: "conv9_1" - top: "conv9_1" -} -layer { - name: "conv9_2" - type: "Convolution" - bottom: "conv9_1" - top: "conv9_2" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 0 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv9_2_relu" - type: "ReLU" - bottom: "conv9_2" - top: "conv9_2" -} -layer { - name: "conv4_3_norm" - type: "Normalize" - bottom: "conv4_3" - top: "conv4_3_norm" - norm_param { - across_spatial: false - scale_filler { - type: "constant" - value: 20 - } - channel_shared: false - } -} -layer { - name: "conv4_3_norm_mbox_loc" - type: "Convolution" - bottom: "conv4_3_norm" - top: "conv4_3_norm_mbox_loc" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 16 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv4_3_norm_mbox_loc_perm" - type: "Permute" - bottom: "conv4_3_norm_mbox_loc" - top: "conv4_3_norm_mbox_loc_perm" - permute_param { - order: 0 - order: 2 - order: 3 - order: 1 - } -} -layer { - name: "conv4_3_norm_mbox_loc_flat" - type: "Flatten" - bottom: "conv4_3_norm_mbox_loc_perm" - top: "conv4_3_norm_mbox_loc_flat" - flatten_param { - axis: 1 - } -} -layer { - name: "conv4_3_norm_mbox_conf" - type: "Convolution" - bottom: "conv4_3_norm" - top: "conv4_3_norm_mbox_conf" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 804 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv4_3_norm_mbox_conf_perm" - type: "Permute" - bottom: "conv4_3_norm_mbox_conf" - top: "conv4_3_norm_mbox_conf_perm" - permute_param { - order: 0 - order: 2 - order: 3 - order: 1 - } -} -layer { - name: "conv4_3_norm_mbox_conf_flat" - type: "Flatten" - bottom: "conv4_3_norm_mbox_conf_perm" - top: "conv4_3_norm_mbox_conf_flat" - flatten_param { - axis: 1 - } -} -layer { - name: "conv4_3_norm_mbox_priorbox" - type: "PriorBox" - bottom: "conv4_3_norm" - bottom: "data" - top: "conv4_3_norm_mbox_priorbox" - prior_box_param { - min_size: 30.0 - max_size: 60.0 - aspect_ratio: 2 - flip: true - clip: false - variance: 0.1 - variance: 0.1 - variance: 0.2 - variance: 0.2 - step: 8 - } -} -layer { - name: "fc7_mbox_loc" - type: "Convolution" - bottom: "fc7" - top: "fc7_mbox_loc" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 24 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "fc7_mbox_loc_perm" - type: "Permute" - bottom: "fc7_mbox_loc" - top: "fc7_mbox_loc_perm" - permute_param { - order: 0 - order: 2 - order: 3 - order: 1 - } -} -layer { - name: "fc7_mbox_loc_flat" - type: "Flatten" - bottom: "fc7_mbox_loc_perm" - top: "fc7_mbox_loc_flat" - flatten_param { - axis: 1 - } -} -layer { - name: "fc7_mbox_conf" - type: "Convolution" - bottom: "fc7" - top: "fc7_mbox_conf" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 1206 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "fc7_mbox_conf_perm" - type: "Permute" - bottom: "fc7_mbox_conf" - top: "fc7_mbox_conf_perm" - permute_param { - order: 0 - order: 2 - order: 3 - order: 1 - } -} -layer { - name: "fc7_mbox_conf_flat" - type: "Flatten" - bottom: "fc7_mbox_conf_perm" - top: "fc7_mbox_conf_flat" - flatten_param { - axis: 1 - } -} -layer { - name: "fc7_mbox_priorbox" - type: "PriorBox" - bottom: "fc7" - bottom: "data" - top: "fc7_mbox_priorbox" - prior_box_param { - min_size: 60.0 - max_size: 111.0 - aspect_ratio: 2 - aspect_ratio: 3 - flip: true - clip: false - variance: 0.1 - variance: 0.1 - variance: 0.2 - variance: 0.2 - step: 16 - } -} -layer { - name: "conv6_2_mbox_loc" - type: "Convolution" - bottom: "conv6_2" - top: "conv6_2_mbox_loc" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 24 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv6_2_mbox_loc_perm" - type: "Permute" - bottom: "conv6_2_mbox_loc" - top: "conv6_2_mbox_loc_perm" - permute_param { - order: 0 - order: 2 - order: 3 - order: 1 - } -} -layer { - name: "conv6_2_mbox_loc_flat" - type: "Flatten" - bottom: "conv6_2_mbox_loc_perm" - top: "conv6_2_mbox_loc_flat" - flatten_param { - axis: 1 - } -} -layer { - name: "conv6_2_mbox_conf" - type: "Convolution" - bottom: "conv6_2" - top: "conv6_2_mbox_conf" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 1206 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv6_2_mbox_conf_perm" - type: "Permute" - bottom: "conv6_2_mbox_conf" - top: "conv6_2_mbox_conf_perm" - permute_param { - order: 0 - order: 2 - order: 3 - order: 1 - } -} -layer { - name: "conv6_2_mbox_conf_flat" - type: "Flatten" - bottom: "conv6_2_mbox_conf_perm" - top: "conv6_2_mbox_conf_flat" - flatten_param { - axis: 1 - } -} -layer { - name: "conv6_2_mbox_priorbox" - type: "PriorBox" - bottom: "conv6_2" - bottom: "data" - top: "conv6_2_mbox_priorbox" - prior_box_param { - min_size: 111.0 - max_size: 162.0 - aspect_ratio: 2 - aspect_ratio: 3 - flip: true - clip: false - variance: 0.1 - variance: 0.1 - variance: 0.2 - variance: 0.2 - step: 32 - } -} -layer { - name: "conv7_2_mbox_loc" - type: "Convolution" - bottom: "conv7_2" - top: "conv7_2_mbox_loc" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 24 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv7_2_mbox_loc_perm" - type: "Permute" - bottom: "conv7_2_mbox_loc" - top: "conv7_2_mbox_loc_perm" - permute_param { - order: 0 - order: 2 - order: 3 - order: 1 - } -} -layer { - name: "conv7_2_mbox_loc_flat" - type: "Flatten" - bottom: "conv7_2_mbox_loc_perm" - top: "conv7_2_mbox_loc_flat" - flatten_param { - axis: 1 - } -} -layer { - name: "conv7_2_mbox_conf" - type: "Convolution" - bottom: "conv7_2" - top: "conv7_2_mbox_conf" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 1206 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv7_2_mbox_conf_perm" - type: "Permute" - bottom: "conv7_2_mbox_conf" - top: "conv7_2_mbox_conf_perm" - permute_param { - order: 0 - order: 2 - order: 3 - order: 1 - } -} -layer { - name: "conv7_2_mbox_conf_flat" - type: "Flatten" - bottom: "conv7_2_mbox_conf_perm" - top: "conv7_2_mbox_conf_flat" - flatten_param { - axis: 1 - } -} -layer { - name: "conv7_2_mbox_priorbox" - type: "PriorBox" - bottom: "conv7_2" - bottom: "data" - top: "conv7_2_mbox_priorbox" - prior_box_param { - min_size: 162.0 - max_size: 213.0 - aspect_ratio: 2 - aspect_ratio: 3 - flip: true - clip: false - variance: 0.1 - variance: 0.1 - variance: 0.2 - variance: 0.2 - step: 64 - } -} -layer { - name: "conv8_2_mbox_loc" - type: "Convolution" - bottom: "conv8_2" - top: "conv8_2_mbox_loc" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 16 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv8_2_mbox_loc_perm" - type: "Permute" - bottom: "conv8_2_mbox_loc" - top: "conv8_2_mbox_loc_perm" - permute_param { - order: 0 - order: 2 - order: 3 - order: 1 - } -} -layer { - name: "conv8_2_mbox_loc_flat" - type: "Flatten" - bottom: "conv8_2_mbox_loc_perm" - top: "conv8_2_mbox_loc_flat" - flatten_param { - axis: 1 - } -} -layer { - name: "conv8_2_mbox_conf" - type: "Convolution" - bottom: "conv8_2" - top: "conv8_2_mbox_conf" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 804 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv8_2_mbox_conf_perm" - type: "Permute" - bottom: "conv8_2_mbox_conf" - top: "conv8_2_mbox_conf_perm" - permute_param { - order: 0 - order: 2 - order: 3 - order: 1 - } -} -layer { - name: "conv8_2_mbox_conf_flat" - type: "Flatten" - bottom: "conv8_2_mbox_conf_perm" - top: "conv8_2_mbox_conf_flat" - flatten_param { - axis: 1 - } -} -layer { - name: "conv8_2_mbox_priorbox" - type: "PriorBox" - bottom: "conv8_2" - bottom: "data" - top: "conv8_2_mbox_priorbox" - prior_box_param { - min_size: 213.0 - max_size: 264.0 - aspect_ratio: 2 - flip: true - clip: false - variance: 0.1 - variance: 0.1 - variance: 0.2 - variance: 0.2 - step: 100 - } -} -layer { - name: "conv9_2_mbox_loc" - type: "Convolution" - bottom: "conv9_2" - top: "conv9_2_mbox_loc" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 16 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv9_2_mbox_loc_perm" - type: "Permute" - bottom: "conv9_2_mbox_loc" - top: "conv9_2_mbox_loc_perm" - permute_param { - order: 0 - order: 2 - order: 3 - order: 1 - } -} -layer { - name: "conv9_2_mbox_loc_flat" - type: "Flatten" - bottom: "conv9_2_mbox_loc_perm" - top: "conv9_2_mbox_loc_flat" - flatten_param { - axis: 1 - } -} -layer { - name: "conv9_2_mbox_conf" - type: "Convolution" - bottom: "conv9_2" - top: "conv9_2_mbox_conf" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 804 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "conv9_2_mbox_conf_perm" - type: "Permute" - bottom: "conv9_2_mbox_conf" - top: "conv9_2_mbox_conf_perm" - permute_param { - order: 0 - order: 2 - order: 3 - order: 1 - } -} -layer { - name: "conv9_2_mbox_conf_flat" - type: "Flatten" - bottom: "conv9_2_mbox_conf_perm" - top: "conv9_2_mbox_conf_flat" - flatten_param { - axis: 1 - } -} -layer { - name: "conv9_2_mbox_priorbox" - type: "PriorBox" - bottom: "conv9_2" - bottom: "data" - top: "conv9_2_mbox_priorbox" - prior_box_param { - min_size: 264.0 - max_size: 315.0 - aspect_ratio: 2 - flip: true - clip: false - variance: 0.1 - variance: 0.1 - variance: 0.2 - variance: 0.2 - step: 300 - } -} -layer { - name: "mbox_loc" - type: "Concat" - bottom: "conv4_3_norm_mbox_loc_flat" - bottom: "fc7_mbox_loc_flat" - bottom: "conv6_2_mbox_loc_flat" - bottom: "conv7_2_mbox_loc_flat" - bottom: "conv8_2_mbox_loc_flat" - bottom: "conv9_2_mbox_loc_flat" - top: "mbox_loc" - concat_param { - axis: 1 - } -} -layer { - name: "mbox_conf" - type: "Concat" - bottom: "conv4_3_norm_mbox_conf_flat" - bottom: "fc7_mbox_conf_flat" - bottom: "conv6_2_mbox_conf_flat" - bottom: "conv7_2_mbox_conf_flat" - bottom: "conv8_2_mbox_conf_flat" - bottom: "conv9_2_mbox_conf_flat" - top: "mbox_conf" - concat_param { - axis: 1 - } -} -layer { - name: "mbox_priorbox" - type: "Concat" - bottom: "conv4_3_norm_mbox_priorbox" - bottom: "fc7_mbox_priorbox" - bottom: "conv6_2_mbox_priorbox" - bottom: "conv7_2_mbox_priorbox" - bottom: "conv8_2_mbox_priorbox" - bottom: "conv9_2_mbox_priorbox" - top: "mbox_priorbox" - concat_param { - axis: 2 - } -} -layer { - name: "mbox_conf_reshape" - type: "Reshape" - bottom: "mbox_conf" - top: "mbox_conf_reshape" - reshape_param { - shape { - dim: 0 - dim: -1 - dim: 201 - } - } -} -layer { - name: "mbox_conf_softmax" - type: "Softmax" - bottom: "mbox_conf_reshape" - top: "mbox_conf_softmax" - softmax_param { - axis: 2 - } -} -layer { - name: "mbox_conf_flatten" - type: "Flatten" - bottom: "mbox_conf_softmax" - top: "mbox_conf_flatten" - flatten_param { - axis: 1 - } -} -layer { - name: "detection_out" - type: "DetectionOutput" - bottom: "mbox_loc" - bottom: "mbox_conf_flatten" - bottom: "mbox_priorbox" - top: "detection_out" - include { - phase: TEST - } - detection_output_param { - num_classes: 201 - share_location: true - background_label_id: 0 - nms_param { - nms_threshold: 0.45 - top_k: 400 - } - save_output_param { - label_map_file: "data/ILSVRC2016/labelmap_ilsvrc_det.prototxt" - } - code_type: CENTER_SIZE - keep_top_k: 200 - confidence_threshold: 0.01 - } -} -