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
), Darknet (.cfg
), MXNet (.model
, -symbol.json
), ncnn (.param
) and TensorFlow Lite (.tflite
).
Netron has experimental support for TorchScript (.pt
, .pth
), PyTorch (.pt
, .pth
), Torch (.t7
), Arm NN (.armnn
), Barracuda (.nn
), BigDL (.bigdl
, .model
), Chainer (.npz
, .h5
), CNTK (.model
, .cntk
), Deeplearning4j (.zip
), MediaPipe (.pbtxt
), ML.NET (.zip
), MNN (.mnn
), OpenVINO (.xml
), PaddlePaddle (.zip
, __model__
), scikit-learn (.pkl
), Tengine (.tmfile
), TensorFlow.js (model.json
, .pb
) and TensorFlow (.pb
, .meta
, .pbtxt
, .ckpt
, .index
).
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.
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 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]