Netron is a viewer for neural network, deep learning and machine learning models.
Netron supports ONNX (.onnx
, .pb
, .pbtxt
), Keras (.h5
, .keras
), TensorFlow Lite (.tflite
), Caffe (.caffemodel
, .prototxt
), Darknet (.cfg
), Core ML (.mlmodel
), MNN (.mnn
), MXNet (.model
, -symbol.json
), ncnn (.param
), PaddlePaddle (.zip
, __model__
), Caffe2 (predict_net.pb
), Barracuda (.nn
), Tengine (.tmfile
), TNN (.tnnproto
), RKNN (.rknn
), MindSpore Lite (.ms
), UFF (.uff
).
Netron has experimental support for TensorFlow (.pb
, .meta
, .pbtxt
, .ckpt
, .index
), PyTorch (.pt
, .pth
), TorchScript (.pt
, .pth
), OpenVINO (.xml
), Torch (.t7
), Arm NN (.armnn
), BigDL (.bigdl
, .model
), Chainer (.npz
, .h5
), CNTK (.model
, .cntk
), Deeplearning4j (.zip
), MediaPipe (.pbtxt
), ML.NET (.zip
), scikit-learn (.pkl
), TensorFlow.js (model.json
, .pb
).
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 netron
Browser: Start the browser version.
Python Server: Run pip install netron
and netron [FILE]
or netron.start('[FILE]')
.
Sample model files to download or open using the browser version:
ONNX: squeezenet [open]
MXNet: inception_v3 [open]
TensorFlow Lite: hair_segmentation [open]
TorchScript: traced_online_pred_layer [open]
Caffe: mobilenet_v2 [open]
代码语言分布