Visualizer for deep learning and machine learning models
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README.md

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), TensorFlow.js (model.json, .pb) and TensorFlow (.pb, .meta, .pbtxt).

Install

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').

Download Models

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