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# CSRNet-mxnet | ||
CVPR CSRNet Mxnet implement | ||
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## | ||
实验采用TRANCOS_v3数据 http://agamenon.tsc.uah.es/Personales/rlopez/data/trancos/ | ||
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使用data_process.py处理原始数据,生成mask之后的image作为输入,根据txt文件夹中的文件生成densitymap 作为ground truth,作为标签。 | ||
然后使用CSRnet中代码进行训练评估以及对自己的数据进行密度和数量统计。 | ||
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训练模型 | ||
train_model() | ||
评估模型 | ||
eval_model() | ||
评估自己的数据 | ||
predict_dir_image_car_num('dir_name') |