LaMa Image Inpainting 图像修复 OnnxRuntime-GPU版 Demo.rar

<p align="center"><img width="50%" src="docs/images/ONNX_Runtime_logo_dark.png" /></p> **ONNX Runtime is a cross-platform inference and training machine-learning accelerator**. **ONNX Runtime inference** can enable faster customer experiences and lower costs, supporting models from deep learning frameworks such as PyTorch and TensorFlow/Keras as well as classical machine learning libraries such as scikit-learn, LightGBM, XGBoost, etc. ONNX Runtime is compatible with different hardware, drivers, and operating systems, and provides optimal performance by leveraging hardware accelerators where applicable alongside graph optimizations and transforms. [Learn more &rarr;](https://www.onnxruntime.ai/docs/#onnx-runtime-for-inferencing) **ONNX Runtime training** can accelerate the model training time on multi-node NVIDIA GPUs for transformer models with a one-line addition for existing PyTorch training scripts. [Learn more &rarr;](https://www.onnxruntime.ai/docs/#onnx-runtime-for-training) ## Get Started & Resources * **General Information**: [onnxruntime.ai](https://onnxruntime.ai) * **Usage documentation and tutorials**: [onnxruntime.ai/docs](https://onnxruntime.ai/docs) * **YouTube video tutorials**: [youtube.com/@ONNXRuntime](https://www.youtube.com/@ONNXRuntime) * [**Upcoming Release Roadmap**](https://github.com/microsoft/onnxruntime/wiki/Upcoming-Release-Roadmap) * **Companion sample repositories**: - ONNX Runtime Inferencing: [microsoft/onnxruntime-inference-examples](https://github.com/microsoft/onnxruntime-inference-examples) - ONNX Runtime Training: [microsoft/onnxruntime-training-examples](https://github.com/microsoft/onnxruntime-training-examples) ## Builtin Pipeline Status |System|Inference|Training| |---|---|---| |Windows|[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=9)<br>[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=10)<br>[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=47)|| |Linux|[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=11)<br>[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=64)<br>[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=12)<br>[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=45)<br>[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=55)|[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=86)<br>[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=84)<br>[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=148)| |Mac|[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=13)|| |Android|[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=53)|| |iOS|[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=134)|| |Web|[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=161)|| |Other|[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=187&repoName=microsoft%2Fonnxruntime)|| ## Third-party Pipeline Status |System|Inference|Training| |---|---|---| |Linux|[](https://github.com/Ascend/onnxruntime/actions/workflows/build-and-test.yaml)|| ## Data/Telemetry Windows distributions of this project may collect usage data and send it to Microsoft to help improve our products and services. See the [privacy statement](docs/Privacy.md) for more details. ## Contributions and Feedback We welcome contributions! Please see the [contribution guidelines](CONTRIBUTING.md). For feature requests or bug reports, please file a [GitHub Issue](https://github.com/Microsoft/onnxruntime/issues). For general discussion or questions, please use [GitHub Discussions](https://github.com/microsoft/onnxruntime/discussions). ## Code of Conduct This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/). For more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments. ## License This project is licensed under the [MIT License](LICENSE).