Netron is a viewer for neural network, deep learning and machine learning models.
Netron supports ONNX (.onnx, .pb, .pbtxt), Keras (.h5, .keras), CoreML (.mlmodel), Caffe2 (predict_net.pb, predict_net.pbtxt), MXNet (.model, -symbol.json) and TensorFlow Lite (.tflite). Netron has experimental support for Caffe (.caffemodel, .prototxt), PyTorch (.pth), Torch (.t7), CNTK (.model, .cntk), PaddlePaddle (__model__), scikit-learn (.pkl), 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 or .deb file.
Windows: Download the .exe installer.
Browser: Start the browser version.
Python Server: Run pip install netron and netron -b [MODEL_FILE]. In Python run import netron and netron.start('model.onnx').
Sample model files you can download and open:
ONNX Models: Inception v1, Inception v2, ResNet-50, SqueezeNet
Keras Models: resnet, tiny-yolo-voc
CoreML Models: MobileNet, Places205-GoogLeNet, Inception v3
TensorFlow Lite Models: Smart Reply 1.0 , Inception v3 2016
Caffe Models: BVLC AlexNet, BVLC CaffeNet, BVLC GoogleNet
Caffe2 Models: BVLC GoogleNet, Inception v2
MXNet Models: CaffeNet, SqueezeNet v1.1
TensorFlow models: Inception v3, Inception v4, Inception 5h