https://github.com/zjykzj/modelflow
Model Export & Inference & Validation
https://github.com/zjykzj/modelflow
cmake cplusplus cpp linux mnn nvidia onnx onnxruntime openvino python pytorch tensorrt tensorrt-engine yolov5 yolov8
Last synced: 3 months ago
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Model Export & Inference & Validation
- Host: GitHub
- URL: https://github.com/zjykzj/modelflow
- Owner: zjykzj
- License: apache-2.0
- Created: 2021-07-03T06:53:32.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2025-07-12T12:23:03.000Z (3 months ago)
- Last Synced: 2025-07-12T14:40:32.216Z (3 months ago)
- Topics: cmake, cplusplus, cpp, linux, mnn, nvidia, onnx, onnxruntime, openvino, python, pytorch, tensorrt, tensorrt-engine, yolov5, yolov8
- Language: Python
- Homepage:
- Size: 6.41 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
Pytorch -> ONNX -> ONNXRuntime/OpenCV/MNN/TensorRT/OpenVINO
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Background](#background)
- [Maintainers](#maintainers)
- [Thanks](#thanks)
- [Contributing](#contributing)
- [License](#license)
## Background
As a computer vision engineer, how to better apply image algorithms to landing scenes is crucial. In practice, C++ can provide a faster reasoning speed and a more practical deployment platform; In addition, Python can provide more convenient simulation and processing.
## Requirements
* [2.4.0 NNAPI后端/CUDA后端支持量化模型](https://github.com/alibaba/MNN/releases/tag/2.4.0)
* [ONNX Runtime v1.14.1](https://github.com/microsoft/onnxruntime/releases/tag/v1.14.1)
* [OpenCV 4.7.0](https://github.com/opencv/opencv/releases/tag/4.7.0)
* [ultralytics/yolov5 v7.0 - YOLOv5 SOTA Realtime Instance Segmentation](https://github.com/ultralytics/yolov5/releases/tag/v7.0)
## Troubleshooting
```text
[ERROR:0@2.663] global onnx_importer.cpp:1051 handleNode DNN/ONNX: ERROR during processing node with 2 inputs and 3 outputs: [Split]:(onnx_node!/model.24/Split) from domain='ai.onnx'
```
* [global onnx_importer.cpp:1051 handleNode DNN/ONNX](https://github.com/opencv/opencv/issues/23227)
* [OPENCV部署ONNX模型报错 ERROR during processing node with 1 inputs and 1 outputs](https://ask.csdn.net/questions/7795689)
>In short, OpenCV 4.7.0 only supports ONNX models with fixed input sizes, and this issue will be resolved after the 5. X. X series
## Maintainers
* zhujian - *Initial work* - [zjykzj](https://github.com/zjykzj)
## Thanks
* [Open Neural Network Exchange](https://onnx.ai/)
* [pytorch/pytorch](https://github.com/pytorch/pytorch)
* [pytorch/vision](https://github.com/pytorch/vision)
* [alibaba/MNN](https://github.com/alibaba/MNN)
* [microsoft/onnxruntime](https://github.com/microsoft/onnxruntime)
* [rockchip-linux/rknn-toolkit2](https://github.com/rockchip-linux/rknn-toolkit2)
* [libjpeg-turbo/libjpeg-turbo](https://github.com/libjpeg-turbo/libjpeg-turbo)
* [opencv/opencv](https://github.com/search?q=opencv)
* [opencv/opencv-python](https://github.com/opencv/opencv-python)
* [ermig1979/Simd](https://github.com/ermig1979/Simd)
* [nothings/stb](https://github.com/nothings/stb)
* [gabime/spdlog](https://github.com/gabime/spdlog)
* [facebookresearch/faiss](https://github.com/facebookresearch/faiss)
* [NVIDIA/TensorRT](https://github.com/NVIDIA/TensorRT/tree/release/8.6/quickstart)
* [NVIDIA Deep Learning TensorRT Documentation](https://docs.nvidia.com/deeplearning/tensorrt/quick-start-guide/index.html#install)
## Contributing
Anyone's participation is welcome! Open an [issue](https://github.com/zjykzj/onnx/issues) or submit PRs.
Small note:
* Git submission specifications should be complied
with [Conventional Commits](https://www.conventionalcommits.org/en/v1.0.0-beta.4/)
* If versioned, please conform to the [Semantic Versioning 2.0.0](https://semver.org) specification
* If editing the README, please conform to the [standard-readme](https://github.com/RichardLitt/standard-readme)
specification.
## License
[Apache License 2.0](LICENSE) © 2021 zjykzj