OnnxGraphQt

ONNX model visualizer. You can edit model structure with GUI!

Requirements

• NodeGraphQt
• PySide2
• Qt.py
• Numpy
• onnx
• onnx-simplifier
• onnx_graphsurgeon
• simple-onnx-processing-tools
• Node.js

Install

sudo apt install python3-pyside2*
sudo apt install nodejs

git clone https://github.com/fateshelled/OnnxGraphQt
cd OnnxGraphQt
python3 -m pip install -U nvidia-pyindex
python3 -m pip install -U Qt.py
python3 -m pip install -U -r requirements.txt

Run with Docker

git clone https://github.com/fateshelled/OnnxGraphQt
cd OnnxGraphQt
# build docker image
./docker/build.bash
# run
./docker/run.bash

Usage

cd OnnxGraphQt

# Open empty graph
python3 onnxgraphqt/main.py

# Open with onnx model
python3 onnxgraphqt/main.py onnxgraphqt/data/mobilenetv2-7.onnx

Open Onnx Model

Open file dialog from menubar(File - Open) or drag and drop from file manager to main window.

Sample model is available at ONNXGraphQt/onnxgraphqt/data/mobilenetv2-7.onnx

Export

Export to ONNX file or Json file.

Node detail

Double click on Node for more information.

Node Search

Node search window can be open from menubar(View - Search). You can search node by name, type, input or output name.

simple-onnx-processing-tools

Please refer to each tool's Github repository for detailed usage.

• Generate Operator [sog4onnx]
• Add Node [sna4onnx]
• Combine Network [snc4onnx]
• Extract Network [sne4onnx]
• Rename Operator [sor4onnx]
• Modify Attributes and Constant [sam4onnx]
• Input Channel Conversion [scc4onnx]
• Initialize Batchsize [sbi4onnx]
• Change Opset [soc4onnx]
• Constant Value Shrink [scs4onnx]
• Delete Node [snd4onnx]

ToDo

• Add Simple Shape Inference tool [ssi4onnx]
• Add Simple Structure Checker[ssc4onnx]

References

• https://github.com/jchanvfx/NodeGraphQt
• https://github.com/lutzroeder/netron
• https://github.com/PINTO0309/simple-onnx-processing-tools
• https://fdwr.github.io/LostOnnxDocs/OperatorFormulas.html
• https://github.com/onnx/onnx/blob/main/docs/Operators.md