# Netron

**Repository Path**: lv-huanchang/Netron

## Basic Information

- **Project Name**: Netron
- **Description**: 一款优异的模型可视化软件
- **Primary Language**: Python
- **License**: MIT
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 1
- **Forks**: 0
- **Created**: 2024-09-03
- **Last Updated**: 2024-09-03

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

<div align="center">
<img width="400px" height="100px" src="https://github.com/lutzroeder/netron/raw/main/.github/logo-light.svg#gh-light-mode-only">
<img width="400px" height="100px" src="https://github.com/lutzroeder/netron/raw/main/.github/logo-dark.svg#gh-dark-mode-only">
</div>

Netron is a viewer for neural network, deep learning and machine learning models. 

Netron supports ONNX, TensorFlow Lite, Core ML, Keras, Caffe, Darknet, MXNet, PaddlePaddle, ncnn, MNN, TensorFlow.js, Safetensors and NumPy.

Netron has experimental support for PyTorch, TorchScript, TensorFlow, OpenVINO, RKNN, ML.NET, GGUF and scikit-learn.

<p align='center'><a href='https://www.lutzroeder.com/ai'><img src='.github/screenshot.png' width='800'></a></p>

## Install

**macOS**: [**Download**](https://github.com/lutzroeder/netron/releases/latest) the `.dmg` file or run `brew install --cask netron`

**Linux**: [**Download**](https://github.com/lutzroeder/netron/releases/latest) the `.AppImage` file or run `snap install netron`

**Windows**: [**Download**](https://github.com/lutzroeder/netron/releases/latest) the `.exe` installer or run `winget install -s winget netron`

**Browser**: [**Start**](https://netron.app) the browser version.

**Python**: 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](https://github.com/onnx/models/raw/main/validated/vision/classification/squeezenet/model/squeezenet1.0-3.onnx) [[open](https://netron.app?url=https://github.com/onnx/models/raw/main/validated/vision/classification/squeezenet/model/squeezenet1.0-3.onnx)]
 * **TensorFlow Lite**: [yamnet](https://huggingface.co/thelou1s/yamnet/resolve/main/lite-model_yamnet_tflite_1.tflite) [[open](https://netron.app?url=https://huggingface.co/thelou1s/yamnet/blob/main/lite-model_yamnet_tflite_1.tflite)]
 * **TensorFlow**: [chessbot](https://github.com/srom/chessbot/raw/master/model/chessbot.pb) [[open](https://netron.app?url=https://github.com/srom/chessbot/raw/master/model/chessbot.pb)]
 * **Keras**: [mobilenet](https://github.com/aio-libs/aiohttp-demos/raw/master/demos/imagetagger/tests/data/mobilenet.h5) [[open](https://netron.app?url=https://github.com/aio-libs/aiohttp-demos/raw/master/demos/imagetagger/tests/data/mobilenet.h5)]
 * **TorchScript**: [traced_online_pred_layer](https://github.com/ApolloAuto/apollo/raw/master/modules/prediction/data/traced_online_pred_layer.pt) [[open](https://netron.app?url=https://github.com/ApolloAuto/apollo/raw/master/modules/prediction/data/traced_online_pred_layer.pt)]
 * **Core ML**: [exermote](https://github.com/Lausbert/Exermote/raw/master/ExermoteInference/ExermoteCoreML/ExermoteCoreML/Model/Exermote.mlmodel) [[open](https://netron.app?url=https://github.com/Lausbert/Exermote/raw/master/ExermoteInference/ExermoteCoreML/ExermoteCoreML/Model/Exermote.mlmodel)]
 * **Darknet**: [yolo](https://github.com/AlexeyAB/darknet/raw/master/cfg/yolo.cfg) [[open](https://netron.app?url=https://github.com/AlexeyAB/darknet/raw/master/cfg/yolo.cfg)]