Lutz Roeder
f7c60d5291
Update brace-style lint rule
|
пре 3 година | |
|---|---|---|
| .github | пре 3 година | |
| .vscode | пре 3 година | |
| publish | пре 3 година | |
| source | пре 3 година | |
| test | пре 3 година | |
| tools | пре 3 година | |
| .gitignore | пре 5 година | |
| CITATION.cff | пре 4 година | |
| LICENSE | пре 9 година | |
| Makefile | пре 3 година | |
| README.md | пре 4 година | |
| package.json | пре 3 година |
README.md
Netron is a viewer for neural network, deep learning and machine learning models.
Netron supports ONNX, TensorFlow Lite, Caffe, Keras, Darknet, PaddlePaddle, ncnn, MNN, Core ML, RKNN, MXNet, MindSpore Lite, TNN, Barracuda, Tengine, CNTK, TensorFlow.js, Caffe2 and UFF.
Netron has experimental support for PyTorch, TensorFlow, TorchScript, OpenVINO, Torch, Vitis AI, kmodel, Arm NN, BigDL, Chainer, Deeplearning4j, MediaPipe, ML.NET and scikit-learn.
Install
macOS: Download the .dmg file or run brew install netron
Linux: Download the .AppImage file or run snap install netron
Windows: Download the .exe installer or run winget install -s winget 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]
- TensorFlow Lite: hair_segmentation [open]
- TensorFlow: chessbot [open]
- Keras: mobilenet [open]
- TorchScript: traced_online_pred_layer [open]
- Core ML: exermote [open]
- Darknet: yolo [open]