Classification accuracy of available pretrained models. (Datasets are ImageNet1K, ImageNet11K and Place365 Challenge)
Please note that the following results are calculated with different datasets.
- ResNet accuracy from Reproduce ResNet-v2 using MXNet
- DenseNet-169 accuracy from A MXNet implementation of DenseNet with BC structure
- SE-ResNeXt-50 accuracy from SENet.mxnet
- Other accuracy from MXNet model gallery and MXNet - Image Classification - Pre-trained Models
| model | Top-1 Accuracy | Top-5 Accuracy | download size | model size (MXNet) | dataset | image shape |
|---|---|---|---|---|---|---|
| CaffeNet | 54.5% | 78.3% | 233MB | 9.3MB | ImageNet1K | 227x227 |
| SqueezeNet | 55.4% | 78.8% | 4.8MB | 4.8MB | ImageNet1K | 227x227 |
| NIN | 58.8% | 81.3% | 30MB | 30MB | ImageNet1K | 224x224 |
| ResNet-18 | 69.5% | 89.1% | 45MB | 43MB | ImageNet1K | 224x224 |
| VGG16 | 71.0% | 89.8% | 528MB | 58MB | ImageNet1K | 224x224 |
| VGG19 | 71.0% | 89.8% | 549MB | 78MB | ImageNet1K | 224x224 |
| Inception-BN | 72.5% | 90.8% | 44MB | 40MB | ImageNet1K | 224x224 |
| ResNet-34 | 72.8% | 91.1% | 84MB | 82MB | ImageNet1K | 224x224 |
| ResNet-50 | 75.6% | 92.8% | 98MB | 90MB | ImageNet1K | 224x224 |
| ResNet-101 | 77.3% | 93.4% | 171MB | 163MB | ImageNet1K | 224x224 |
| ResNet-152 | 77.8% | 93.6% | 231MB | 223MB | ImageNet1K | 224x224 |
| ResNet-200 | 77.9% | 93.8% | 248MB | 240MB | ImageNet1K | 224x224 |
| Inception-v3 | 76.9% | 93.3% | 92MB | 84MB | ImageNet1K | 299x299 |
| ResNeXt-50 | 76.9% | 93.3% | 96MB | 89MB | ImageNet1K | 224x224 |
| ResNeXt-101 | 78.3% | 94.1% | 170MB | 162MB | ImageNet1K | 224x224 |
| ResNeXt-101-64x4d | 79.1% | 94.3% | 320MB | 312MB | ImageNet1K | 224x224 |
| ResNet-152 (imagenet11k) | 41.6% | - | 311MB | 223MB | ImageNet11K | 224x224 |
| ResNet-50 (Place365 Challenge) | 31.1% | - | 181MB | 90MB | Place365ch | 224x224 |
| ResNet-152 (Place365 Challenge) | 33.6% | - | 313MB | 223MB | Place365ch | 224x224 |
| DenseNet-169 | 75.3% | 92.8% | 55MB | 48MB | ImageNet1K | 224x224 |
| SE-ResNeXt-50 | 76.7% | 93.4% | 103MB | 95MB | ImageNet1K | 224x224 |
- The
download sizeis the file size when first downloading pretrained model. - The
model sizeis the file size to be saved after fine-tuning.
To use these pretrained models, specify the following pretrained model name in config.yml.
| model | pretrained model name |
|---|---|
| CaffeNet | imagenet1k-caffenet |
| SqueezeNet | imagenet1k-squeezenet |
| NIN | imagenet1k-nin |
| VGG16 | imagenet1k-vgg16 |
| VGG19 | imagenet1k-vgg19 |
| Inception-BN | imagenet1k-inception-bn |
| ResNet-18 | imagenet1k-resnet-18 |
| ResNet-34 | imagenet1k-resnet-34 |
| ResNet-50 | imagenet1k-resnet-50 |
| ResNet-101 | imagenet1k-resnet-101 |
| ResNet-152 | imagenet1k-resnet-152 |
| ResNet-152 (imagenet11k) | imagenet11k-resnet-152 |
| ResNet-200 | imagenet1k-resnet-200 |
| Inception-v3 | imagenet1k-inception-v3 |
| ResNeXt-50 | imagenet1k-resnext-50 |
| ResNeXt-101 | imagenet1k-resnext-101 |
| ResNeXt-101-64x4d | imagenet1k-resnext-101-64x4d |
| ResNet-50 (Place365 Challenge) | imagenet11k-place365ch-resnet-50 |
| ResNet-152 (Place365 Challenge) | imagenet11k-place365ch-resnet-152 |
| DenseNet-169 | imagenet1k-densenet-169 |
| SE-ResNeXt-50 | imagenet1k-se-resnext-50 |