netron

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), Darknet (.cfg), MXNet (.model, -symbol.json), Barracuda (.nn), ncnn (.param), Tengine (.tmfile), TNN (.tnnproto), UFF (.uff) and TensorFlow Lite (.tflite).

Netron has experimental support for TorchScript (.pt, .pth), PyTorch (.pt, .pth), Torch (.t7), Arm NN (.armnn), BigDL (.bigdl, .model), Chainer (.npz, .h5), CNTK (.model, .cntk), Deeplearning4j (.zip), MediaPipe (.pbtxt), ML.NET (.zip), MNN (.mnn), PaddlePaddle (.zip, __model__), OpenVINO (.xml), scikit-learn (.pkl), TensorFlow.js (model.json, .pb) and TensorFlow (.pb, .meta, .pbtxt, .ckpt, .index).

Install

macOS: Download the .dmg file or run brew cask install netron

Linux: Download the .AppImage file or run snap install netron

Windows: Download the .exe installer or run winget install netron

Browser: Start the browser version.

Python Server: Run pip install netron and netron [FILE] or netron.start('[FILE]').

Models

Sample model files to download or open using the browser version:

• ONNX: squeezenet [open]
• CoreML: exermote [open]
• Darknet: yolo [open]
• Keras: mobilenet [open]
• MXNet: inception_v3 [open]
• TensorFlow: chessbot [open]
• TensorFlow Lite: hair_segmentation [open]
• TorchScript: traced_online_pred_layer [open]
• Caffe: mobilenet_v2 [open]