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* [Feature]: Add github prebuild workflow after new release. (#1852) * add prebuild dockerfile * add prebuild test workflw * update * update * rm other workflow for test * Update docker image * add win1o prebuild * add test prebuild * add windows scripts in prebuilt package * add linux scripts in prebuilt package * generate_build_config.py * fix cudnn search * fix env * fix script * fix rpath * fix cwd * fix windows * fix lint * windows prebuild ci * linux prebuild ci * fix * update trigger * Revert "rm other workflow for test" This reverts commit 0a0387275014efab71046d33a0e52904672b4012. * update sdk build readme * update prebuild * fix dll deps for python >= 3.8 on windows * fix ci * test prebuild * update test script to avoid modify upload folder * add onnxruntime.dll to mmdeploy_python * update prebuild workflow * update prebuild * Update loader.cpp.in * remove exists prebuild files * fix opencv env * update cmake options for mmdeploy python build * remove test code * fix lint --------- Co-authored-by: RunningLeon <mnsheng@yeah.net> Co-authored-by: RunningLeon <maningsheng@sensetime.com> * rename mmdeploy_python -> mmdeploy_runtime * test master prebuild * fix trt net build * Revert "test master prebuild" This reverts commit aad5258648f5f2c410c965b295c309fd1166da22. * add master branch * fix linux set_env script * update package_tools docs * fix gcc 7.3 aligned_alloc * comment temporarily as text_det_recog can't be built with prebuild package built under manylinux --------- Co-authored-by: RunningLeon <mnsheng@yeah.net> Co-authored-by: RunningLeon <maningsheng@sensetime.com>
English | 简体中文
Highlights
The new v1.x version has been released, which is adapted to the preview version of upstream codebase, please align the version when using it.
| mmdeploy | mmengine | mmcv | mmdet | others |
|---|---|---|---|---|
| 0.x | - | <=1.x | <=2.x | 0.x |
| 1.x | 0.x | 2.x | 3.x | 1.x |
Introduction
MMDeploy is an open-source deep learning model deployment toolset. It is a part of the OpenMMLab project.
Main features
Fully support OpenMMLab models
The currently supported codebases and models are as follows, and more will be included in the future
Multiple inference backends are available
The supported Device-Platform-InferenceBackend matrix is presented as following, and more will be compatible.
The benchmark can be found from here
| Device / Platform | Linux | Windows | macOS | Android |
|---|---|---|---|---|
| x86_64 CPU |  ONNXRuntime pplnn ncnnLibTorch OpenVINO TVM |
 ONNXRuntimeOpenVINO |
- | - |
| ARM CPU | ncnn |
- | - | ncnn |
| RISC-V |  ncnn |
- | - | - |
| NVIDIA GPU | ONNXRuntimeTensorRTpplnnLibTorchTVM |
ONNXRuntimeTensorRTpplnn |
- | - |
| NVIDIA Jetson | TensorRT |
- | - | - |
| Huawei ascend310 |  CANN |
- | - | - |
| Rockchip | RKNN |
- | - | - |
| Apple M1 | - | - |  CoreML |
- |
| Adreno GPU | - | - | - |  SNPEncnn |
| Hexagon DSP | - | - | - | SNPE |
|
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
Documentation
Please read getting_started for the basic usage of MMDeploy. We also provide tutoials about:
- Build
- User Guide
- Developer Guide
- Custom Backend Ops
- FAQ
- Contributing
Benchmark and Model zoo
You can find the supported models from here and their performance in the benchmark.
Contributing
We appreciate all contributions to MMDeploy. Please refer to CONTRIBUTING.md for the contributing guideline.
Acknowledgement
We would like to sincerely thank the following teams for their contributions to MMDeploy:
Citation
If you find this project useful in your research, please consider citing:
@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.
Projects in OpenMMLab
- MMCV: OpenMMLab foundational library for computer vision.
- MIM: MIM installs OpenMMLab packages.
- MMClassification: OpenMMLab image classification toolbox and benchmark.
- MMDetection: OpenMMLab detection toolbox and benchmark.
- MMDetection3D: OpenMMLab's next-generation platform for general 3D object detection.
- MMYOLO: OpenMMLab YOLO series toolbox and benchmark
- MMRotate: OpenMMLab rotated object detection toolbox and benchmark.
- MMSegmentation: OpenMMLab semantic segmentation toolbox and benchmark.
- MMOCR: OpenMMLab text detection, recognition, and understanding toolbox.
- MMPose: OpenMMLab pose estimation toolbox and benchmark.
- MMHuman3D: OpenMMLab 3D human parametric model toolbox and benchmark.
- MMSelfSup: OpenMMLab self-supervised learning toolbox and benchmark.
- MMRazor: OpenMMLab model compression toolbox and benchmark.
- MMFewShot: OpenMMLab fewshot learning toolbox and benchmark.
- MMAction2: OpenMMLab's next-generation action understanding toolbox and benchmark.
- MMTracking: OpenMMLab video perception toolbox and benchmark.
- MMFlow: OpenMMLab optical flow toolbox and benchmark.
- MMEditing: OpenMMLab image and video editing toolbox.
- MMGeneration: OpenMMLab image and video generative models toolbox.
- MMDeploy: OpenMMLab model deployment framework.