This is a collection of pre-trained models in different deep learning frameworks.
You can download the model you want by simply click the download link.
With the download model, you can convert them to different frameworks.
Next session show an example to show you how to convert pre-trained model between frameworks.
Example: Convert vgg19 model from Tensorflow to CNTK
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Install the stable version of MMdnn
pip install mmdnn
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Download Tensorflow pre-trained model
- Method 1: Directly download from below model collection
- Method 2: Use command line
$ mmdownload -f tensorflow -n vgg19 Downloading file [./vgg_19_2016_08_28.tar.gz] from [http://download.tensorflow.org/models/vgg_19_2016_08_28.tar.gz] progress: 520592.0 KB downloaded, 100% Model saved in file: ./imagenet_vgg19.ckptNOTICE: the model name after the '-n' argument must be the models appearence in the below model collection.
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Convert model architecture(*.ckpt.meta) and weights(.ckpt) from Tensorflow to IR
$ mmtoir -f tensorflow -d vgg19 -n imagenet_vgg19.ckpt.meta -w imagenet_vgg19.ckpt --dstNodeName MMdnn_Output Parse file [imagenet_vgg19.ckpt.meta] with binary format successfully. Tensorflow model file [imagenet_vgg19.ckpt.meta] loaded successfully. Tensorflow checkpoint file [imagenet_vgg19.ckpt] loaded successfully. [38] variables loaded. IR network structure is saved as [vgg19.json]. IR network structure is saved as [vgg19.pb]. IR weights are saved as [vgg19.npy].
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Convert models from IR to PyTorch code snippet and weights
$ mmtocode -f pytorch -n vgg19.pb --IRWeightPath vgg19.npy --dstModelPath pytorch_vgg19.py -dw pytorch_vgg19.npy Parse file [vgg19.pb] with binary format successfully. Target network code snippet is saved as [pytorch_vgg19.py]. Target weights are saved as [pytorch_vgg19.npy].
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Generate PyTorch model from code snippet file and weight file
$ mmtomodel -f pytorch -in pytorch_vgg19.py -iw pytorch_vgg19.npy --o pytorch_vgg19.pth PyTorch model file is saved as [pytorch_vgg19.pth], generated by [pytorch_vgg19.py] and [pytorch_vgg19.npy]. Notice that you may need [pytorch_vgg19.py] to load the model back.
| alexnet Framework: caffe Download: prototxt caffemodel Source: Link |
inception_v1 Framework: caffe Download: prototxt caffemodel Source: Link |
vgg16 Framework: caffe Download: prototxt caffemodel Source: Link |
| vgg19 Framework: caffe Download: prototxt caffemodel Source: Link |
resnet50 Framework: caffe Download: prototxt caffemodel Source: Link |
resnet101 Framework: caffe Download: prototxt caffemodel Source: Link |
| resnet152 Framework: caffe Download: prototxt caffemodel Source: Link |
squeezenet Framework: caffe Download: prototxt caffemodel Source: Link |
xception Framework: caffe Download: prototxt caffemodel Source: |
| inception_v4 Framework: caffe Download: prototxt caffemodel Source: |
alexnet Framework: cntk Download: model Source: Link |
inception_v3 Framework: cntk Download: model Source: Link |
| resnet18 Framework: cntk Download: model Source: Link |
resnet50 Framework: cntk Download: model Source: Link |
resnet101 Framework: cntk Download: model Source: Link |
| resnet152 Framework: cntk Download: model Source: Link |
inception_v3 Framework: coreml Download: mlmodel Source: |
vgg16 Framework: coreml Download: mlmodel Source: Link |
| resnet50 Framework: coreml Download: mlmodel Source: Link |
mobilenet Framework: coreml Download: mlmodel Source: Link |
imagenet1k-inception-bn Framework: mxnet Download: json params Source: Link |
| imagenet1k-resnet-18 Framework: mxnet Download: json params Source: Link |
imagenet1k-resnet-34 Framework: mxnet Download: json params Source: Link |
imagenet1k-resnet-50 Framework: mxnet Download: json params Source: Link |
| imagenet1k-resnet-101 Framework: mxnet Download: json params Source: Link |
imagenet1k-resnet-152 Framework: mxnet Download: json params Source: Link |
imagenet1k-resnext-50 Framework: mxnet Download: json params Source: Link |
| imagenet1k-resnext-101 Framework: mxnet Download: json params Source: Link |
imagenet1k-resnext-101-64x4d Framework: mxnet Download: json params Source: Link |
vgg19 Framework: mxnet Download: json params Source: Link |
| vgg16 Framework: mxnet Download: json params Source: Link |
squeezenet_v1.0 Framework: mxnet Download: json params Source: Link |
squeezenet_v1.1 Framework: mxnet Download: json params Source: Link |
| alexnet Framework: pytorch Download: pth Source: Link |
densenet121 Framework: pytorch Download: pth Source: Link |
densenet169 Framework: pytorch Download: pth Source: Link |
| densenet201 Framework: pytorch Download: pth Source: Link |
densenet161 Framework: pytorch Download: pth Source: Link |
inception_v3 Framework: pytorch Download: pth Source: Link |
| resnet18 Framework: pytorch Download: pth Source: Link |
resnet34 Framework: pytorch Download: pth Source: Link |
resnet50 Framework: pytorch Download: pth Source: Link |
| resnet101 Framework: pytorch Download: pth Source: Link |
resnet152 Framework: pytorch Download: pth Source: Link |
squeezenet1_0 Framework: pytorch Download: pth Source: Link |
| squeezenet1_1 Framework: pytorch Download: pth Source: Link |
vgg11 Framework: pytorch Download: pth Source: Link |
vgg13 Framework: pytorch Download: pth Source: Link |
| vgg16 Framework: pytorch Download: pth Source: Link |
vgg19 Framework: pytorch Download: pth Source: Link |
vgg11_bn Framework: pytorch Download: pth Source: Link |
| vgg13_bn Framework: pytorch Download: pth Source: Link |
vgg16_bn Framework: pytorch Download: pth Source: Link |
vgg19_bn Framework: pytorch Download: pth Source: Link |
| vgg16 Framework: tensorflow Download: tgz Source: Link |
vgg19 Framework: tensorflow Download: tgz Source: Link |
inception_v1 Framework: tensorflow Download: tgz Source: Link |
| inception_v1_frozen Framework: tensorflow Download: tgz Source: Link |
inception_v3 Framework: tensorflow Download: tgz Source: Link |
inception_v3_frozen Framework: tensorflow Download: tgz Source: Link |
| resnet_v1_50 Framework: tensorflow Download: tgz Source: Link |
resnet_v1_152 Framework: tensorflow Download: tgz Source: Link |
resnet_v2_50 Framework: tensorflow Download: tgz Source: Link |
| resnet_v2_152 Framework: tensorflow Download: tgz Source: Link |
resnet_v2_200 Framework: tensorflow Download: tgz Source: Link |
mobilenet_v1_1.0 Framework: tensorflow Download: tgz Source: Link |
| mobilenet_v1_1.0_frozen Framework: tensorflow Download: tgz Source: Link |
mobilenet_v2_1.0_224 Framework: tensorflow Download: tgz Source: Link |
inception_resnet_v2 Framework: tensorflow Download: tgz Source: Link |
| nasnet-a_large Framework: tensorflow Download: tgz Source: Link |
| imagenet11k-resnet-152 Framework: mxnet Download: json params Source: Link |
imagenet11k-place365ch-resnet-152 Framework: mxnet Download: json params Source: Link |
imagenet11k-place365ch-resnet-50 Framework: mxnet Download: json params Source: Link |
| voc-fcn8s Framework: caffe Download: prototxt caffemodel Source: Link |
voc-fcn16s Framework: caffe Download: prototxt caffemodel Source: Link |
voc-fcn32s Framework: caffe Download: prototxt caffemodel Source: Link |
| Fast-RCNN_Pascal Framework: cntk Download: model Source: Link |
tinyyolo Framework: coreml Download: mlmodel Source: Link |
yolov3 Framework: darknet Download: cfg weights Source: Link |
| yolov2 Framework: darknet Download: cfg weights Source: Link |
| Fast-RCNN_grocery100 Framework: cntk Download: model Source: Link |