{"id":13443399,"url":"https://github.com/open-mmlab/mmdeploy","last_synced_at":"2025-05-13T22:03:33.667Z","repository":{"id":36966382,"uuid":"441467833","full_name":"open-mmlab/mmdeploy","owner":"open-mmlab","description":"OpenMMLab Model Deployment 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align=\"center\"\u003e\n  \u003cimg src=\"resources/mmdeploy-logo.png\" width=\"450\"/\u003e\n  \u003cdiv\u003e\u0026nbsp;\u003c/div\u003e\n  \u003cdiv align=\"center\"\u003e\n    \u003cb\u003e\u003cfont size=\"5\"\u003eOpenMMLab website\u003c/font\u003e\u003c/b\u003e\n    \u003csup\u003e\n        \u003ca href=\"https://openmmlab.com\"\u003e\n        \u003ci\u003e\u003cfont size=\"4\"\u003eHOT\u003c/font\u003e\u003c/i\u003e\n      \u003c/a\u003e\n    \u003c/sup\u003e\n    \u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\n    \u003cb\u003e\u003cfont size=\"5\"\u003eOpenMMLab platform\u003c/font\u003e\u003c/b\u003e\n    \u003csup\u003e\n      \u003ca href=\"https://platform.openmmlab.com\"\u003e\n        \u003ci\u003e\u003cfont size=\"4\"\u003eTRY IT OUT\u003c/font\u003e\u003c/i\u003e\n      \u003c/a\u003e\n    \u003c/sup\u003e\n  \u003c/div\u003e\n  \u003cdiv\u003e\u0026nbsp;\u003c/div\u003e\n\n[![docs](https://img.shields.io/badge/docs-latest-blue)](https://mmdeploy.readthedocs.io/en/latest/)\n[![badge](https://github.com/open-mmlab/mmdeploy/workflows/build/badge.svg)](https://github.com/open-mmlab/mmdeploy/actions)\n[![codecov](https://codecov.io/gh/open-mmlab/mmdeploy/branch/main/graph/badge.svg)](https://codecov.io/gh/open-mmlab/mmdeploy)\n[![license](https://img.shields.io/github/license/open-mmlab/mmdeploy.svg)](https://github.com/open-mmlab/mmdeploy/tree/main/LICENSE)\n[![issue resolution](https://img.shields.io/github/issues-closed-raw/open-mmlab/mmdeploy)](https://github.com/open-mmlab/mmdeploy/issues)\n[![open issues](https://img.shields.io/github/issues-raw/open-mmlab/mmdeploy)](https://github.com/open-mmlab/mmdeploy/issues)\n\nEnglish | [简体中文](README_zh-CN.md)\n\n\u003c/div\u003e\n\n\u003cdiv align=\"center\"\u003e\n  \u003ca href=\"https://openmmlab.medium.com/\" style=\"text-decoration:none;\"\u003e\n    \u003cimg src=\"https://user-images.githubusercontent.com/25839884/218352562-cdded397-b0f3-4ca1-b8dd-a60df8dca75b.png\" width=\"3%\" alt=\"\" /\u003e\u003c/a\u003e\n  \u003cimg src=\"https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png\" width=\"3%\" alt=\"\" /\u003e\n  \u003ca href=\"https://discord.gg/raweFPmdzG\" style=\"text-decoration:none;\"\u003e\n    \u003cimg src=\"https://user-images.githubusercontent.com/25839884/218347213-c080267f-cbb6-443e-8532-8e1ed9a58ea9.png\" width=\"3%\" alt=\"\" /\u003e\u003c/a\u003e\n  \u003cimg src=\"https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png\" width=\"3%\" alt=\"\" /\u003e\n  \u003ca href=\"https://twitter.com/OpenMMLab\" style=\"text-decoration:none;\"\u003e\n    \u003cimg src=\"https://user-images.githubusercontent.com/25839884/218346637-d30c8a0f-3eba-4699-8131-512fb06d46db.png\" width=\"3%\" alt=\"\" /\u003e\u003c/a\u003e\n  \u003cimg src=\"https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png\" width=\"3%\" alt=\"\" /\u003e\n  \u003ca href=\"https://www.youtube.com/openmmlab\" style=\"text-decoration:none;\"\u003e\n    \u003cimg src=\"https://user-images.githubusercontent.com/25839884/218346691-ceb2116a-465a-40af-8424-9f30d2348ca9.png\" width=\"3%\" alt=\"\" /\u003e\u003c/a\u003e\n\u003c/div\u003e\n\n## Highlights\n\nThe MMDeploy 1.x has been released, which is adapted to upstream codebases from OpenMMLab 2.0. Please **align the version** when using it.\nThe default branch has been switched to `main` from `master`. MMDeploy 0.x (`master`) will be deprecated and new features will only be added to MMDeploy 1.x (`main`) in future.\n\n| mmdeploy | mmengine |   mmcv   |  mmdet   | others |\n| :------: | :------: | :------: | :------: | :----: |\n|  0.x.y   |    -     | \\\u003c=1.x.y | \\\u003c=2.x.y | 0.x.y  |\n|  1.x.y   |  0.x.y   |  2.x.y   |  3.x.y   | 1.x.y  |\n\n[deploee](https://platform.openmmlab.com/deploee/) offers over 2,300 AI models in ONNX, NCNN, TRT and OpenVINO formats. Featuring a built-in list of real hardware devices, deploee enables users to convert Torch models into any target inference format for profiling purposes.\n\n## Introduction\n\nMMDeploy is an open-source deep learning model deployment toolset. It is a part of the [OpenMMLab](https://openmmlab.com/) project.\n\n\u003cdiv align=\"center\"\u003e\n  \u003cimg src=\"resources/introduction.png\"\u003e\n\u003c/div\u003e\n\n## Main features\n\n### Fully support OpenMMLab models\n\nThe currently supported codebases and models are as follows, and more will be included in the future\n\n- [mmpretrain](docs/en/04-supported-codebases/mmpretrain.md)\n- [mmdet](docs/en/04-supported-codebases/mmdet.md)\n- [mmseg](docs/en/04-supported-codebases/mmseg.md)\n- [mmagic](docs/en/04-supported-codebases/mmagic.md)\n- [mmocr](docs/en/04-supported-codebases/mmocr.md)\n- [mmpose](docs/en/04-supported-codebases/mmpose.md)\n- [mmdet3d](docs/en/04-supported-codebases/mmdet3d.md)\n- [mmrotate](docs/en/04-supported-codebases/mmrotate.md)\n- [mmaction2](docs/en/04-supported-codebases/mmaction2.md)\n\n### Multiple inference backends are available\n\nThe supported Device-Platform-InferenceBackend matrix is presented as following, and more will be compatible.\n\nThe benchmark can be found from [here](docs/en/03-benchmark/benchmark.md)\n\n\u003cdiv style=\"width: fit-content; margin: auto;\"\u003e\n\u003ctable\u003e\n  \u003ctr\u003e\n    \u003cth\u003eDevice / \u003cbr\u003e Platform\u003c/th\u003e\n    \u003cth\u003eLinux\u003c/th\u003e\n    \u003cth\u003eWindows\u003c/th\u003e\n    \u003cth\u003emacOS\u003c/th\u003e\n    \u003cth\u003eAndroid\u003c/th\u003e\n  \u003c/tr\u003e\n  \u003ctr\u003e\n    \u003cth\u003ex86_64 \u003cbr\u003e CPU\u003c/th\u003e\n    \u003ctd\u003e\n        \u003csub\u003e\u003ca href=\"https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-ort.yml\"\u003e\u003cimg src=\"https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-ort.yml\"\u003e\u003c/a\u003e\u003c/sub\u003e \u003csub\u003eonnxruntime\u003c/sub\u003e \u003cbr\u003e\n        \u003csub\u003e\u003ca href=\"https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-pplnn.yml\"\u003e\u003cimg src=\"https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-pplnn.yml\"\u003e\u003c/a\u003e\u003c/sub\u003e \u003csub\u003epplnn\u003c/sub\u003e \u003cbr\u003e\n        \u003csub\u003e\u003ca href=\"https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-ncnn.yml\"\u003e\u003cimg src=\"https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-ncnn.yml\"\u003e\u003c/a\u003e\u003c/sub\u003e \u003csub\u003encnn\u003c/sub\u003e \u003cbr\u003e\n        \u003csub\u003e\u003ca href=\"https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-torchscript.yml\"\u003e\u003cimg src=\"https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-torchscript.yml\"\u003e\u003c/a\u003e\u003c/sub\u003e \u003csub\u003eLibTorch\u003c/sub\u003e \u003cbr\u003e\n        \u003csub\u003e\u003cimg src=\"https://img.shields.io/badge/build-no%20status-lightgrey\"\u003e\u003c/sub\u003e \u003csub\u003eOpenVINO\u003c/sub\u003e \u003cbr\u003e\n        \u003csub\u003e\u003cimg src=\"https://img.shields.io/badge/build-no%20status-lightgrey\"\u003e\u003c/sub\u003e \u003csub\u003eTVM\u003c/sub\u003e \u003cbr\u003e\n    \u003c/td\u003e\n    \u003ctd\u003e\n        \u003csub\u003e\u003cimg src=\"https://img.shields.io/badge/build-no%20status-lightgrey\"\u003e\u003c/sub\u003e \u003csub\u003eonnxruntime\u003c/sub\u003e \u003cbr\u003e\n        \u003csub\u003e\u003cimg src=\"https://img.shields.io/badge/build-no%20status-lightgrey\"\u003e\u003c/sub\u003e \u003csub\u003eOpenVINO\u003c/sub\u003e \u003cbr\u003e\n        \u003csub\u003e\u003cimg src=\"https://img.shields.io/badge/build-no%20status-lightgrey\"\u003e\u003c/sub\u003e \u003csub\u003encnn\u003c/sub\u003e \u003cbr\u003e\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n        -\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n        -\n    \u003c/td\u003e\n  \u003c/tr\u003e\n\n\u003ctr\u003e\n    \u003cth\u003eARM \u003cbr\u003e CPU\u003c/th\u003e\n    \u003ctd\u003e\n        \u003csub\u003e\u003ca href=\"https://github.com/open-mmlab/mmdeploy/actions/workflows/build.yml\"\u003e\u003cimg src=\"https://byob.yarr.is/open-mmlab/mmdeploy/cross_build_aarch64\"\u003e\u003c/a\u003e\u003c/sub\u003e \u003csub\u003encnn\u003c/sub\u003e \u003cbr\u003e\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n        -\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n        -\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n        \u003csub\u003e\u003ca href=\"https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-ncnn.yml\"\u003e\u003cimg src=\"https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-ncnn.yml\"\u003e\u003c/a\u003e\u003c/sub\u003e \u003csub\u003encnn\u003c/sub\u003e \u003cbr\u003e\n    \u003c/td\u003e\n  \u003c/tr\u003e\n\n\u003ctr\u003e\n    \u003cth\u003eRISC-V\u003c/th\u003e\n    \u003ctd\u003e\n        \u003csub\u003e\u003ca href=\"https://github.com/open-mmlab/mmdeploy/actions/workflows/linux-riscv64-gcc.yml\"\u003e\u003cimg src=\"https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/linux-riscv64-gcc.yml\"\u003e\u003c/a\u003e\u003c/sub\u003e \u003csub\u003encnn\u003c/sub\u003e \u003cbr\u003e\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n        -\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n        -\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n        -\n    \u003c/td\u003e\n  \u003c/tr\u003e\n\n\u003ctr\u003e\n    \u003cth\u003eNVIDIA \u003cbr\u003e GPU\u003c/th\u003e\n    \u003ctd\u003e\n        \u003csub\u003e\u003ca href=\"https://github.com/open-mmlab/mmdeploy/actions/workflows/build.yml\"\u003e\u003cimg src=\"https://byob.yarr.is/open-mmlab/mmdeploy/build_cuda113_linux\"\u003e\u003c/a\u003e\u003c/sub\u003e \u003csub\u003eonnxruntime\u003c/sub\u003e \u003cbr\u003e\n        \u003csub\u003e\u003ca href=\"https://github.com/open-mmlab/mmdeploy/actions/workflows/build.yml\"\u003e\u003cimg src=\"https://byob.yarr.is/open-mmlab/mmdeploy/build_cuda113_linux\"\u003e\u003c/a\u003e\u003c/sub\u003e \u003csub\u003eTensorRT\u003c/sub\u003e \u003cbr\u003e\n        \u003csub\u003e\u003cimg src=\"https://img.shields.io/badge/build-no%20status-lightgrey\"\u003e\u003c/sub\u003e \u003csub\u003eLibTorch\u003c/sub\u003e \u003cbr\u003e\n        \u003csub\u003e\u003ca href=\"https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-pplnn.yml\"\u003e\u003cimg src=\"https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-pplnn.yml\"\u003e\u003c/a\u003e\u003c/sub\u003e \u003csub\u003epplnn\u003c/sub\u003e \u003cbr\u003e\n    \u003c/td\u003e\n    \u003ctd\u003e\n        \u003csub\u003e\u003ca href=\"https://github.com/open-mmlab/mmdeploy/actions/workflows/build.yml\"\u003e\u003cimg src=\"https://byob.yarr.is/open-mmlab/mmdeploy/build_cuda113_windows\"\u003e\u003c/a\u003e\u003c/sub\u003e \u003csub\u003eonnxruntime\u003c/sub\u003e \u003cbr\u003e\n        \u003csub\u003e\u003ca href=\"https://github.com/open-mmlab/mmdeploy/actions/workflows/build.yml\"\u003e\u003cimg src=\"https://byob.yarr.is/open-mmlab/mmdeploy/build_cuda113_windows\"\u003e\u003c/a\u003e\u003c/sub\u003e \u003csub\u003eTensorRT\u003c/sub\u003e \u003cbr\u003e\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n        -\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n        -\n    \u003c/td\u003e\n  \u003c/tr\u003e\n\n\u003ctr\u003e\n    \u003cth\u003eNVIDIA \u003cbr\u003e Jetson\u003c/th\u003e\n    \u003ctd\u003e\n        \u003csub\u003e\u003cimg src=\"https://img.shields.io/badge/build-no%20status-lightgrey\"\u003e\u003c/sub\u003e \u003csub\u003eTensorRT\u003c/sub\u003e \u003cbr\u003e\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n        -\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n        -\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n        -\n    \u003c/td\u003e\n  \u003c/tr\u003e\n\n\u003ctr\u003e\n    \u003cth\u003eHuawei \u003cbr\u003e ascend310\u003c/th\u003e\n    \u003ctd\u003e\n        \u003csub\u003e\u003ca href=\"https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-ascend.yml\"\u003e\u003cimg src=\"https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-ascend.yml\"\u003e\u003c/a\u003e\u003c/sub\u003e \u003csub\u003eCANN\u003c/sub\u003e \u003cbr\u003e\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n        -\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n        -\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n        -\n    \u003c/td\u003e\n  \u003c/tr\u003e\n\n\u003ctr\u003e\n    \u003cth\u003eRockchip\u003c/th\u003e\n    \u003ctd\u003e\n        \u003csub\u003e\u003ca href=\"https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-rknn.yml\"\u003e\u003cimg src=\"https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-rknn.yml\"\u003e\u003c/a\u003e\u003c/sub\u003e \u003csub\u003eRKNN\u003c/sub\u003e \u003cbr\u003e\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n        -\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n        -\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n        -\n    \u003c/td\u003e\n  \u003c/tr\u003e\n\n\u003ctr\u003e\n    \u003cth\u003eApple M1\u003c/th\u003e\n    \u003ctd align=\"center\"\u003e\n        -\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n        -\n    \u003c/td\u003e\n    \u003ctd\u003e\n        \u003csub\u003e\u003ca href=\"https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-coreml.yml\"\u003e\u003cimg src=\"https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-coreml.yml\"\u003e\u003c/a\u003e\u003c/sub\u003e \u003csub\u003eCoreML\u003c/sub\u003e \u003cbr\u003e\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n        -\n    \u003c/td\u003e\n  \u003c/tr\u003e\n\n\u003ctr\u003e\n    \u003cth\u003eAdreno \u003cbr\u003e GPU\u003c/th\u003e\n    \u003ctd align=\"center\"\u003e\n        -\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n        -\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n        -\n    \u003c/td\u003e\n    \u003ctd\u003e\n        \u003csub\u003e\u003ca href=\"https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-snpe.yml\"\u003e\u003cimg src=\"https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-snpe.yml\"\u003e\u003c/a\u003e\u003c/sub\u003e \u003csub\u003eSNPE\u003c/sub\u003e \u003cbr\u003e\n        \u003csub\u003e\u003ca href=\"https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-ncnn.yml\"\u003e\u003cimg src=\"https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-ncnn.yml\"\u003e\u003c/a\u003e\u003c/sub\u003e \u003csub\u003encnn\u003c/sub\u003e \u003cbr\u003e\n    \u003c/td\u003e\n  \u003c/tr\u003e\n\n\u003ctr\u003e\n    \u003cth\u003eHexagon \u003cbr\u003e DSP\u003c/th\u003e\n    \u003ctd align=\"center\"\u003e\n        -\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n        -\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n        -\n    \u003c/td\u003e\n    \u003ctd\u003e\n        \u003csub\u003e\u003ca href=\"https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-snpe.yml\"\u003e\u003cimg src=\"https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-snpe.yml\"\u003e\u003c/a\u003e\u003c/sub\u003e \u003csub\u003eSNPE\u003c/sub\u003e \u003cbr\u003e\n    \u003c/td\u003e\n  \u003c/tr\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\n### Efficient and scalable C/C++ SDK Framework\n\nAll 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\n\n## [Documentation](https://mmdeploy.readthedocs.io/en/latest/)\n\nPlease read [getting_started](docs/en/get_started.md) for the basic usage of MMDeploy. We also provide tutoials about:\n\n- [Build](docs/en/01-how-to-build/build_from_source.md)\n  - [Build from Docker](docs/en/01-how-to-build/build_from_docker.md)\n  - [Build from Script](docs/en/01-how-to-build/build_from_script.md)\n  - [Build for Linux](docs/en/01-how-to-build/linux-x86_64.md)\n  - [Build for macOS](docs/en/01-how-to-build/macos-arm64.md)\n  - [Build for Win10](docs/en/01-how-to-build/windows.md)\n  - [Build for Android](docs/en/01-how-to-build/android.md)\n  - [Build for Jetson](docs/en/01-how-to-build/jetsons.md)\n  - [Build for SNPE](docs/en/01-how-to-build/snpe.md)\n  - [Cross Build for aarch64](docs/en/01-how-to-build/cross_build_ncnn_aarch64.md)\n- User Guide\n  - [How to convert model](docs/en/02-how-to-run/convert_model.md)\n  - [How to write config](docs/en/02-how-to-run/write_config.md)\n  - [How to profile model](docs/en/02-how-to-run/profile_model.md)\n  - [How to quantize model](docs/en/02-how-to-run/quantize_model.md)\n  - [Useful tools](docs/en/02-how-to-run/useful_tools.md)\n- Developer Guide\n  - [Architecture](docs/en/07-developer-guide/architecture.md)\n  - [How to support new models](docs/en/07-developer-guide/support_new_model.md)\n  - [How to support new backends](docs/en/07-developer-guide/support_new_backend.md)\n  - [How to partition model](docs/en/07-developer-guide/partition_model.md)\n  - [How to test rewritten model](docs/en/07-developer-guide/test_rewritten_models.md)\n  - [How to test backend ops](docs/en/07-developer-guide/add_backend_ops_unittest.md)\n  - [How to do regression test](docs/en/07-developer-guide/regression_test.md)\n- Custom Backend Ops\n  - [ncnn](docs/en/06-custom-ops/ncnn.md)\n  - [ONNXRuntime](docs/en/06-custom-ops/onnxruntime.md)\n  - [tensorrt](docs/en/06-custom-ops/tensorrt.md)\n- [FAQ](docs/en/faq.md)\n- [Contributing](.github/CONTRIBUTING.md)\n\n## Benchmark and Model zoo\n\nYou 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).\n\n## Contributing\n\nWe appreciate all contributions to MMDeploy. Please refer to [CONTRIBUTING.md](.github/CONTRIBUTING.md) for the contributing guideline.\n\n## Acknowledgement\n\nWe would like to sincerely thank the following teams for their contributions to [MMDeploy](https://github.com/open-mmlab/mmdeploy):\n\n- [OpenPPL](https://github.com/openppl-public)\n- [OpenVINO](https://github.com/openvinotoolkit/openvino)\n- [ncnn](https://github.com/Tencent/ncnn)\n\n## Citation\n\nIf you find this project useful in your research, please consider citing:\n\n```BibTeX\n@misc{=mmdeploy,\n    title={OpenMMLab's Model Deployment Toolbox.},\n    author={MMDeploy Contributors},\n    howpublished = {\\url{https://github.com/open-mmlab/mmdeploy}},\n    year={2021}\n}\n```\n\n## License\n\nThis project is released under the [Apache 2.0 license](LICENSE).\n\n## Projects in OpenMMLab\n\n- [MMEngine](https://github.com/open-mmlab/mmengine): OpenMMLab foundational library for training deep learning models.\n- [MMCV](https://github.com/open-mmlab/mmcv): OpenMMLab foundational library for computer vision.\n- [MMPretrain](https://github.com/open-mmlab/mmpretrain): OpenMMLab pre-training toolbox and benchmark.\n- [MMagic](https://github.com/open-mmlab/mmagic): Open**MM**Lab **A**dvanced, **G**enerative and **I**ntelligent **C**reation toolbox.\n- [MMDetection](https://github.com/open-mmlab/mmdetection): OpenMMLab detection toolbox and benchmark.\n- [MMDetection3D](https://github.com/open-mmlab/mmdetection3d): OpenMMLab's next-generation platform for general 3D object detection.\n- [MMYOLO](https://github.com/open-mmlab/mmyolo): OpenMMLab YOLO series toolbox and benchmark\n- [MMRotate](https://github.com/open-mmlab/mmrotate): OpenMMLab rotated object detection toolbox and benchmark.\n- [MMTracking](https://github.com/open-mmlab/mmtracking): OpenMMLab video perception toolbox and benchmark.\n- [MMSegmentation](https://github.com/open-mmlab/mmsegmentation): OpenMMLab semantic segmentation toolbox and benchmark.\n- [MMOCR](https://github.com/open-mmlab/mmocr): OpenMMLab text detection, recognition, and understanding toolbox.\n- [MMPose](https://github.com/open-mmlab/mmpose): OpenMMLab pose estimation toolbox and benchmark.\n- [MMHuman3D](https://github.com/open-mmlab/mmhuman3d): OpenMMLab 3D human parametric model toolbox and benchmark.\n- [MMFewShot](https://github.com/open-mmlab/mmfewshot): OpenMMLab fewshot learning toolbox and benchmark.\n- [MMAction2](https://github.com/open-mmlab/mmaction2): OpenMMLab's next-generation action understanding toolbox and benchmark.\n- [MMFlow](https://github.com/open-mmlab/mmflow): OpenMMLab optical flow toolbox and benchmark.\n- [MMDeploy](https://github.com/open-mmlab/mmdeploy): OpenMMLab model deployment framework.\n- [MMRazor](https://github.com/open-mmlab/mmrazor): OpenMMLab model compression toolbox and benchmark.\n- [MIM](https://github.com/open-mmlab/mim): MIM installs OpenMMLab packages.\n- [Playground](https://github.com/open-mmlab/playground): A central hub for gathering and showcasing amazing projects built upon OpenMMLab.\n","funding_links":[],"categories":["Python","Computer Vision"],"sub_categories":["General Purpose CV"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fopen-mmlab%2Fmmdeploy","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fopen-mmlab%2Fmmdeploy","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fopen-mmlab%2Fmmdeploy/lists"}