Introduction

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.

Steps to Convert Model

Example: Convert vgg19 model from Tensorflow to CNTK

Install the stable version of MMdnn
```
 pip install mmdnn
```

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.ckpt

NOTICE: the model name after the ‘-n’ argument must be the models appearence in the below model collection.

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].

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].

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.

Model Collection

Image Classification

imagenet

| | | | |-|-|-| |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


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

Object Detection

Pascal VOC

| | | | |-|-|-| |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

grocery100


Fast-RCNN_grocery100 Framework: cntk Download: model Source: Link