Netron is a viewer for neural network, deep learning and machine learning models.
Netron supports ONNX (.onnx, .pb, .pbtxt), Keras (.h5, .keras), Core ML (.mlmodel), Caffe (.caffemodel, .prototxt), Caffe2 (predict_net.pb, predict_net.pbtxt), MXNet (.model, -symbol.json), NCNN (.param) and TensorFlow Lite (.tflite).
Netron has experimental support for TorchScript (.pt, .pth), PyTorch (.pt, .pth), Torch (.t7), CNTK (.model, .cntk), Deeplearning4j (.zip), PaddlePaddle (.zip, __model__), Darknet (.cfg), scikit-learn (.pkl), ML.NET (.zip), MNN (.mnn), OpenVINO (.xml), BigDL (.bigdl, .model), Chainer, (.npz, .h5), TensorFlow.js (model.json, .pb) and TensorFlow (.pb, .meta, .pbtxt).
macOS: Download the .dmg file or run brew cask install netron
Linux: Download the .AppImage, .deb file or run snap install netron
Windows: Download the .exe installer.
Browser: Start the browser version.
Python Server: Run pip install netron and netron [FILE] or import netron; netron.start('[FILE]').
Sample model files to download and open:
- ONNX: resnet-18
- Keras: tiny-yolo-voc
- CoreML: faces_model
- TensorFlow Lite: smartreply
- MXNet: inception_v1
- Caffe: mobilenet_v2
- TensorFlow: inception_v3