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English | [简体中文](README_zh-CN.md)
## Introduction
MMDeploy is an open-source deep learning model deployment toolset. It is a part of the [OpenMMLab](https://openmmlab.com/) project.
<div align="center">
<img src="resources/introduction.png">
</div>
## Main features
### Fully support OpenMMLab models
The currently supported codebases and models are as follows, and more will be included in the future
- [mmcls](docs/en/04-supported-codebases/mmcls.md)
- [mmdet](docs/en/04-supported-codebases/mmdet.md)
- [mmseg](docs/en/04-supported-codebases/mmseg.md)
- [mmedit](docs/en/04-supported-codebases/mmedit.md)
- [mmocr](docs/en/04-supported-codebases/mmocr.md)
- [mmpose](docs/en/04-supported-codebases/mmpose.md)
- [mmdet3d](docs/en/04-supported-codebases/mmdet3d.md)
- [mmrotate](docs/en/04-supported-codebases/mmrotate.md)
### Multiple inference backends are available
Models can be exported and run in the following backends, and more will be compatible
| ONNX Runtime | TensorRT | ppl.nn | ncnn | OpenVINO | LibTorch | more |
| ------------ | -------- | ------ | ---- | -------- | -------- | ---------------------------------------------- |
| ✔️ | ✔️ | ✔️ | ✔️ | ✔️ | ✔️ | [benchmark](docs/en/03-benchmark/benchmark.md) |
### Efficient and scalable C/C++ SDK Framework
All kinds of modules in the SDK can be extended, such as `Transform` for image processing, `Net` for Neural Network inference, `Module` for postprocessing and so on
## Get Started
Please read [getting_started.md](docs/en/get_started.md) for the basic usage of MMDeploy. We also provide tutoials about:
- [Build](docs/en/01-how-to-build/build_from_source.md)
- [Build from Docker](docs/en/01-how-to-build/build_from_docker.md)
- [Build for Linux](docs/en/01-how-to-build/linux-x86_64.md)
- [Build for Win10](docs/en/01-how-to-build/windows.md)
- [Build for Android](docs/en/01-how-to-build/android.md)
- [Build for Jetson](docs/en/01-how-to-build/jetsons.md)
- User Guide
- [How to convert model](docs/en/02-how-to-run/convert_model.md)
- [How to write config](docs/en/02-how-to-run/write_config.md)
- [How to evaluate deployed models](docs/en/02-how-to-run/how_to_evaluate_a_model.md)
- [How to measure performance of deployed models](docs/en/02-how-to-run/how_to_measure_performance_of_models.md)
- Developer Guide
- [How to support new models](docs/en/06-developer-guide/support_new_model.md)
- [How to support new backends](docs/en/06-developer-guide/support_new_backend.md)
- [FAQ](docs/en/faq.md)
- [Contributing](.github/CONTRIBUTING.md)
## Benchmark and Model zoo
You can find the supported models from [here](docs/en/03-benchmark/supported_models.md) and their performance in the [benchmark](docs/en/03-benchmark/benchmark.md).
## Contributing
We appreciate all contributions to MMDeploy. Please refer to [CONTRIBUTING.md](.github/CONTRIBUTING.md) for the contributing guideline.
## Acknowledgement
We would like to sincerely thank the following teams for their contributions to [MMDeploy](https://github.com/open-mmlab/mmdeploy):
- [OpenPPL](https://github.com/openppl-public)
- [OpenVINO](https://github.com/openvinotoolkit/openvino)
- [ncnn](https://github.com/Tencent/ncnn)
## Citation
If you find this project useful in your research, please consider citing:
```BibTeX
@misc{=mmdeploy,
title={OpenMMLab's Model Deployment Toolbox.},
author={MMDeploy Contributors},
howpublished = {\url{https://github.com/open-mmlab/mmdeploy}},
year={2021}
}
```
## License
This project is released under the [Apache 2.0 license](LICENSE).
## Projects in OpenMMLab
- [MMCV](https://github.com/open-mmlab/mmcv): OpenMMLab foundational library for computer vision.
- [MIM](https://github.com/open-mmlab/mim): MIM installs OpenMMLab packages.
- [MMClassification](https://github.com/open-mmlab/mmclassification): OpenMMLab image classification toolbox and benchmark.
- [MMDetection](https://github.com/open-mmlab/mmdetection): OpenMMLab detection toolbox and benchmark.
- [MMDetection3D](https://github.com/open-mmlab/mmdetection3d): OpenMMLab's next-generation platform for general 3D object detection.
- [MMRotate](https://github.com/open-mmlab/mmrotate): OpenMMLab rotated object detection toolbox and benchmark.
- [MMSegmentation](https://github.com/open-mmlab/mmsegmentation): OpenMMLab semantic segmentation toolbox and benchmark.
- [MMOCR](https://github.com/open-mmlab/mmocr): OpenMMLab text detection, recognition, and understanding toolbox.
- [MMPose](https://github.com/open-mmlab/mmpose): OpenMMLab pose estimation toolbox and benchmark.
- [MMHuman3D](https://github.com/open-mmlab/mmhuman3d): OpenMMLab 3D human parametric model toolbox and benchmark.
- [MMSelfSup](https://github.com/open-mmlab/mmselfsup): OpenMMLab self-supervised learning toolbox and benchmark.
- [MMRazor](https://github.com/open-mmlab/mmrazor): OpenMMLab model compression toolbox and benchmark.
- [MMFewShot](https://github.com/open-mmlab/mmfewshot): OpenMMLab fewshot learning toolbox and benchmark.
- [MMAction2](https://github.com/open-mmlab/mmaction2): OpenMMLab's next-generation action understanding toolbox and benchmark.
- [MMTracking](https://github.com/open-mmlab/mmtracking): OpenMMLab video perception toolbox and benchmark.
- [MMFlow](https://github.com/open-mmlab/mmflow): OpenMMLab optical flow toolbox and benchmark.
- [MMEditing](https://github.com/open-mmlab/mmediting): OpenMMLab image and video editing toolbox.
- [MMGeneration](https://github.com/open-mmlab/mmgeneration): OpenMMLab image and video generative models toolbox.
- [MMDeploy](https://github.com/open-mmlab/mmdeploy): OpenMMLab model deployment framework.
mmdeploy-master
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mmdeploy-master （1276个子文件） 
make.bat 752B make.bat 752B kitti_000008.bin 269KB CITATION.cff 262B setup.cfg 548B .clang-format 4KB MMDeploy.cmake 6KB cuda.cmake 3KB FindTENSORRT.cmake 2KB tensorrt.cmake 1KB FindONNXRUNTIME.cmake 1KB FindCUDNN.cmake 1KB post-install.cmake 292B deps.cmake 256B opencv.cmake 78B clipper.cpp 134KB onnx2ncnn.cpp 94KB fuse_pass.cpp 83KB topk.cpp 35KB test_execution.cpp 16KB keypoints_from_heatmap.cpp 15KB expand.cpp 14KB cuda_device.cpp 14KB grid_sample.cpp 12KB nms_rotated.cpp 12KB ppl_net.cpp 11KB test_resize.cpp 11KB cpu_device.cpp 11KB text_recognizer.cpp 11KB subgraph_matcher.cpp 10KB test_value.cpp 10KB trt_deform_conv.cpp 10KB device_impl.cpp 10KB trt_modulated_deform_conv.cpp 10KB openvino_net.cpp 10KB trt_batched_nms.cpp 10KB trt_batched_rotated_nms.cpp 9KB trt_multi_level_roi_align.cpp 9KB trt_multi_level_rotated_roi_align.cpp 9KB roi_align_rotated.cpp 9KB opencv_utils.cpp 9KB trt_roi_align.cpp 8KB trt_instance_norm.cpp 8KB modulated_deform_conv.cpp 8KB pose_detector.cpp 8KB text_detector.cpp 8KB net_module.cpp 7KB object_detection.cpp 7KB trt_grid_sampler.cpp 7KB trt_bicubic_interpolate.cpp 7KB topdown_affine.cpp 7KB pipeline.cpp 7KB load_impl.cpp 6KB ort_net.cpp 6KB detector.cpp 6KB trt_net.cpp 6KB tensorslice.cpp 6KB rotated_detector.cpp 6KB executor.cpp 6KB shape_inference.cpp 6KB tensor.cpp 6KB batched_nms_kernel.cpp 6KB resize_ocr.cpp 5KB classifier.cpp 5KB trt_scatternd.cpp 5KB fuse_select_assign.cpp 5KB segmentor.cpp 5KB crnn.cpp 5KB trt_grid_priors.cpp 5KB mmdeploy_TextRecognizer.cpp 5KB async_ocr.cpp 5KB test_text_recognizer.cpp 5KB restorer.cpp 5KB schedulers.cpp 5KB async_ocr_v2.cpp 5KB ncnn_net.cpp 5KB panet.cpp 5KB pixel_group.cpp 5KB resize.cpp 5KB gather.cpp 5KB common_subgraph_elimination.cpp 4KB psenet.cpp 4KB dbnet.cpp 4KB test_pad.cpp 4KB instance_segmentation.cpp 4KB zip_model_impl.cpp 4KB modulated_deform_conv_cpu.cpp 4KB pad_impl.cpp 4KB operator.cpp 4KB pad.cpp 4KB contour_expand.cpp 4KB test_crop.cpp 4KB test_value_archive.cpp 4KB oriented_object_detection.cpp 4KB panet.cpp 4KB pose_detector.cpp 4KB flatten_cls_head.cpp 4KB keypoints_from_regression.cpp 4KB test_detector.cpp 4KB mmdeploy_Detector.cpp 3KB共 1276 条
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