The convertor/conversion of deep learning models for different deep learning frameworks/softwares.
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README.md

The project will be updated continuously ......  

Pull requests are welcome!

Deep Learning Model Convertors

Note: This is not one convertor for all frameworks, but a collection of different converters. Because github is an open source platform, I hope we can help each other here, gather everyone's strength.

Because of these different frameworks, the awesome convertors of deep learning models for different frameworks occur. It should be noted that I did not test all the converters, so I could not guarantee that each was available. But I also hope this convertor collection may help you!

The sheet below is a overview of all convertors in github (not only contain official provided and more are user-self implementations). I just make a little work to collect these convertors. Also, hope everyone can support this project to help more people who're also crazy because of various frameworks.

convertor mxnet caffe caffe2 CNTK theano/lasagne neon pytorch torch keras darknet tensorflow chainer coreML/iOS
mxnet - MMdnn MXNet2Caffe Mxnet2Caffe MMdnn (through ONNX) MMdnn None None MMdnn None MMdnn None MMdnn None mxnet-to-coreml MMdnn
caffe mxnet/tools/caffe_converter ResNet_caffe2mxnet MMdnn - CaffeToCaffe2 MMdnn (through ONNX) crosstalkcaffe/CaffeConverter MMdnn caffe_theano_conversion caffe-model-convert caffe-to-theano caffe2neon MMdnn pytorch-caffe pytorch-resnet googlenet-caffe2torch mocha loadcaffe caffe_weight_converter caffe2keras nn_tools keras caffe2keras Deep_Learning_Model_Converter MMdnn pytorch-caffe-darknet-convert MMdnn nn_tools caffe-tensorflow None CoreMLZoo apple/coremltools MMdnn
caffe2 None None - ONNX None None ONNX None None None None None None
CNTK MMdnn MMdnn ONNX MMdnn (through ONNX) - None None ONNX MMdnn None MMdnn None MMdnn None MMdnn
theano/lasagne None None None None   -   None None None None None None None None
neon None None None None None - None None None None None None None
pytorch MMdnn MMdnn pytorch2caffe pytorch-caffe-darknet-convert onnx-caffe2 MMdnn (through ONNX) ONNX MMdnn None None - None MMdnn pytorch2keras nn-transfer pytorch-caffe-darknet-convert MMdnn pytorch2keras (over Keras) pytorch-tf None MMdnn onnx-coreml
torch None fb-caffe-exts/torch2caffe mocha trans-torch th2caffe Torch2Caffe2 None None None convert_torch_to_pytorch - None None None None torch2coreml torch2ios
keras MMdnn MMdnn nn_tools keras2caffe MMdnn (through ONNX) MMdnn None None MMdnn nn-transfer None - None nn_tools convert-to-tensorflow keras_to_tensorflow keras_to_tensorflow MMdnn None apple/coremltools model-converters keras_models MMdnn
darknet None pytorch-caffe-darknet-convert None MMdnn None None pytorch-caffe-darknet-convert None MMdnn   -   DW2TF darkflow lego_yolo None None
tensorflow MMdnn MMdnn nn_tools MMdnn (through ONNX) crosstalk MMdnn None None pytorch-tf MMdnn None model-converters nn_tools convert-to-tensorflow MMdnn None - None tfcoreml MMdnn
chainer None None None None None None chainer2pytorch None None None None - None
coreML/iOS MMdnn MMdnn MMdnn (through ONNX) MMdnn None None MMdnn None MMdnn None MMdnn None -

Brief Intro of Convertors

Open Neural Network Exchange

General framework for converting between all kinds of neural networks

ONNX is an effort to unify converters for neural networks in order to bring some sanity to the NN world. Released by Facebook and Microsoft. More info here.

MMdnn

MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between CaffeEmit, CNTK, CoreML, Keras, MXNet, ONNX, PyTorch and TensorFlow.

MXNet convertor

Convert to MXNet model.

mdering/CoreMLZoo: A few models converted from caffe to CoreMLs format

A few deep learning models converted from various formats to CoreMLs format. Models currently available:

  • SqueezeNet
  • VGG19 Please feel free to create a pull request with additional models.

mxnet/tools/caffe_converter

Key topics covered include the following:

nicklhy/ResNet_caffe2mxnet

This is a tool to convert the deep-residual-networks from caffe model to mxnet model. The weights are directly copied from caffe network blobs.

Caffe convertor

Convert to Caffe model.

pytorch2caffe

Convert PyTorch model to Caffemodel.

cypw/MXNet2Caffe

Convert MXNet model to Caffe model.

wranglerwong/Mxnet2Caffe: Convert MXNet model to Caffe model

Convert MXNet model to Caffe model.

kuangliu/mocha

Convert torch model to/from caffe model easily.

uhfband/keras2caffe: Keras to Caffe model converter tool

This tool tested with Caffe 1.0, Keras 2.1.2 and TensorFlow 1.4.0

Working conversion examples:

Problem layers:

  • ZeroPadding2D
  • MaxPooling2D and AveragePooling2D with asymmetric padding

facebook/fb-caffe-exts/torch2caffe

Some handy utility libraries and tools for the Caffe deep learning framework, which has ** A library for converting pre-trained Torch models to the equivalent Caffe models.**

pytorch-caffe-darknet-convert

Convert between pytorch, caffe and darknet models. Caffe darknet models can be load directly by pytorch.

Teaonly/trans-torch

Translating Torch model to other framework such as Caffe, MxNet ...

e-lab/th2caffe

A torch-nn to caffe converter for specific layers.

hahnyuan/nn_tools

a neural network convertor for models among caffe tensorflow keras

Caffe2 convertor

Convert to Caffe2 model.

CaffeToCaffe2

This is an official convertor, which not only provoide a script also an ipython notebook as below:

onnx-caffe2

Convert PyTorch to Caffe2 (making it especially easy to deploy on mobile devices)

CNTK convertor

Convert to CNTK model.

crosstalkcaffe/CaffeConverter

The tool will help you convert trained models from Caffe to CNTK.

Convert trained models: giving a model script and its weights file, export to CNTK model.

crosstalk

crosstalk is from CNTK contrib.

Theano/Lasagne convertor

Convert to Theano/Lasagne model.

an-kumar/caffe-theano-conversion

This is part of a project for CS231N at Stanford University, written by Ankit Kumar, Mathematics major, Class of 2015

This is a repository that allows you to convert pretrained caffe models into models in Lasagne, a thin wrapper around Theano. You can also convert a caffe model's architecture to an equivalent one in Lasagne. You do not need caffe installed to use this module.

Currently, the following caffe layers are supported:

* Convolution
* LRN
* Pooling
* Inner Product
* Relu
* Softmax

kencoken/caffe-model-convert

Convert models from Caffe to Theano format.

piergiaj/caffe-to-theano

Convert a Caffe Model to a Theano Model. This currently works on AlexNet, but should work for any Caffe model that only includes layers that have been impemented.

Neon convertor  

Convert to Neon model.

NervanaSystems/caffe2neon

Tools to convert Caffe models to neon's serialization format.

This repo contains tools to convert Caffe models into a format compatible with the neon deep learning library. The main script, "decaffeinate.py", takes as input a caffe model definition file and the corresponding model weights file and returns a neon serialized model file. This output file can be used to instantiate the neon Model object, which will generate a model in neon that should replicate the behavior of the Caffe model.

PyTorch convertor  

Convert to PyTorch model.

ruotianluo/pytorch-resnet

Convert resnet trained in caffe to pytorch model.

clcarwin/convert_torch_to_pytorch

Convert torch t7 model to pytorch model and source.

vzhong/chainer2pytorch

chainer2pytorch implements conversions from Chainer modules to PyTorch modules, setting parameters of each modules such that one can port over models on a module basis.

pytorch-caffe

Load caffe prototxt and weights directly in pytorch without explicitly converting model from caffe to pytorch.

nn-transfer

Convert between Keras and PyTorch models.

Torch convertor  

Convert to Torch model.

kmatzen/googlenet-caffe2torch

Converts bvlc_googlenet.caffemodel to a Torch nn model.

Want to use the pre-trained GoogLeNet from the BVLC Model Zoo in Torch? Do you not want to use Caffe as an additional dependency inside Torch? Use these two scripts to build the network definition in Torch and copy the learned weights from the Caffe model.

kuangliu/mocha

Convert torch model to/from caffe model easily.

szagoruyko/loadcaffe

Convert caffe model to a Torch nn.Sequential model.

Keras convertor  

Convert to Keras model.

pierluigiferrari/caffe_weight_converter

This is a Caffe-to-Keras weight converter, i.e. it converts .caffemodel weight files to Keras-2-compatible HDF5 weight files. It can also export .caffemodel weights as Numpy arrays for further processing.

This converter converts the weights of a model only (not the model definition), which has the great advantage that it doesn't break every time it encounters an unknown layer type like other converters to that try to translate the model definition as well. The downside, of course, is that you'll have to write the model definition yourself.

The repository also provides converted weights for some popular models.

qxcv/caffe2keras

Note: This converter has been adapted from code in Marc Bolaños fork of Caffe. See acks for code provenance.

This is intended to serve as a conversion module for Caffe models to Keras models.

Please, be aware that this module is not regularly maintained. Thus, some layers or parameter definitions introduced in newer versions of either Keras or Caffe might not be compatible with the converter. Pull requests welcome!

hahnyuan/nn_tools

a neural network convertor for models among caffe tensorflow keras

MarcBS/keras

Keras' fork with several new functionalities. Caffe2Keras converter, multimodal layers, etc. https://github.com/MarcBS/keras

This fork of Keras offers the following contributions:

Caffe to Keras conversion module Layer-specific learning rates New layers for multimodal data Contact email: marc.bolanos@ub.edu

GitHub page: https://github.com/MarcBS

MarcBS/keras is compatible with: Python 2.7 and Theano only.

OdinLin/caffe2keras

a simple tool to translate caffe model to keras model.

jamescfli/Deep_Learning_Model_Converter

nn-transfer

Convert between Keras and PyTorch models.

pytorch2keras

Convert pytorch models to Keras.

Darknet convertor  

Convert to Darknet model.

pytorch-caffe-darknet-convert

Convert between pytorch, caffe and darknet models. Caffe darknet models can be load directly by pytorch.

TensorFlow convertor  

Convert to TensorFlow model.

crosstalk

crosstalk is from CNTK.

triagemd/model-converters: Tools for converting Keras models for use with other ML frameworks

Tools for converting Keras models for use with other ML frameworks (coreML, TensorFlow).

hahnyuan/nn_tools

a neural network convertor for models among caffe tensorflow keras

ethereon/caffe-tensorflow: Caffe models in TensorFlow

Convert Caffe models to TensorFlow.

goranrauker/convert-to-tensorflow

Converts a variety of trained models to a frozen tensorflow protocol buffer file for use with the c++ tensorflow api. C++ code is included for using the frozen models.

thtrieu/darkflow

Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices.

dEcmir/lego_yolo

Tensorflow code to to retrain yolo on a new dataset using weights from darknet

This repository contains experiments of transfer learning using YOLO on a new synthetical LEGO data set ROUGH AND UNDOCUMENTED!

alanswx/keras_to_tensorflow

Convert keras models to tensorflow frozen graph for use on cell phones, etc.

amir-abdi/keras_to_tensorflow

General code to convert a trained keras model into an inference tensorflow model.

leonidk/pytorch-tf

Converting a pretrained pytorch model to tensorflow

pytorch2keras

Convert pytorch models to Tensorflow (via Keras)

jinyu121/DW2TF: Darknet Weights to TensorFlow

This is a simple convector which converts Darknet weights file (.weights) to Tensorflow weights file (.ckpt).

leonidk/pytorch-tf

No readme.

Chainer convertor  

Convert to Chainer model.

coreML convertor  

Convert to coreML model.

Apple: Converting Trained Models to Core ML

Convert trained models created with third-party machine learning tools to the Core ML model format.

If your model is created and trained using a supported third-party machine learning tool, you can use Core ML Tools to convert it to the Core ML model format. Table 1 lists the supported models and third-party tools.

Model type Supported models Supported tools
Neural networks Feedforward, convolutional, recurrent Caffe v1
Keras 1.2.2+
Tree ensembles Random forests, boosted trees, decision trees scikit-learn 0.18
XGBoost 0.6
Support vector machines Scalar regression, multiclass classification scikit-learn 0.18
LIBSVM 3.22
Generalized linear models Linear regression, logistic regression scikit-learn 0.18
Feature engineering Sparse vectorization, dense vectorization, categorical processing scikit-learn 0.18
Pipeline models Sequentially chained models scikit-learn 0.18

mxnet/tools/mxnet-to-coreml

Convert MXNet models into Apple CoreML format. This tool helps convert MXNet models into Apple CoreML format which can then be run on Apple devices.

prisma-ai/torch2coreml: Torch7 -> CoreML

This tool helps convert Torch7 models into Apple CoreML format which can then be run on Apple devices.

woffle/torch2ios: Torch7 Library - Convert NN Models To iOS Format

Torch7 Library - Convert NN Models To iOS Format.

Small lib to serialise Torch7 Networks for iOS. Supported Layers include Fully Connected, Pooling and Convolution Layers at present. The library stores the weights & biases (if any) for each layer necesarry for inference on iOS devices.

Bulochkin/keras_models: Keras models with python-based convertor to provide embedding in IOS platform

Keras models with python-based convertor to provide embedding in IOS platform.

triagemd/model-converters: Tools for converting Keras models for use with other ML frameworks

Tools for converting Keras models for use with other ML frameworks (coreML, TensorFlow).

Apple & Google: Tensorflow to CoreML converter

Google collaborated with Apple to create a Tensorflow to CoreML converter announcement.

Support for Core ML is provided through a tool that takes a TensorFlow model and converts it to the Core ML Model Format (.mlmodel).