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reformat supported backends table in readme (#1109) 

* reformat supported device and platforms

* use capital CPU
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lvhan028 2022-09-27 05:05:32 -07:00 committed by GitHub
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19
README.md
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@ -53,11 +53,22 @@ The currently supported codebases and models are as follows, and more will be in
### Multiple inference backends are available
Models can be exported and run in the following backends, and more will be compatible
The supported Device-Platform-InferenceBackend matrix is presented as following, and more will be compatible.
| ONNX Runtime | TensorRT | ppl.nn | ncnn | OpenVINO | LibTorch | snpe | Ascend | Core ML | RKNN | more |
| ------------ | -------- | ------ | ---- | -------- | -------- | ---- | ------ | ------- | ---- | ---------------------------------------------- |
| ✔️ | ✔️ | ✔️ | ✔️ | ✔️ | ✔️ | ✔️ | ✔️ | ✔️ | ✔️ | [benchmark](docs/en/03-benchmark/benchmark.md) |
The benchmark can be found from [here](docs/en/03-benchmark/benchmark.md)
| Device / Platform | Linux | Windows | macOS | Android |
| ----------------- | --------------------------------------------------------------- | --------------------------------------- | -------- | ---------------- |
| x86_64 CPU | ✔️ONNX Runtime<br>✔️pplnn<br>✔️ncnn<br>✔️OpenVINO<br>✔️LibTorch | ✔️ONNX Runtime<br>✔️OpenVINO | - | - |
| ARM CPU | ✔️ncnn | - | - | ✔️ncnn |
| RISC-V | ✔️ncnn | - | - | - |
| NVIDIA GPU | ✔️ONNX Runtime<br>✔️TensorRT<br>✔️pplnn<br>✔️LibTorch | ✔️ONNX Runtime<br>✔️TensorRT<br>✔️pplnn | - | - |
| NVIDIA Jetson | ✔️TensorRT | ✔️TensorRT | - | - |
| Huawei ascend310 | ✔️CANN | - | - | - |
| Rockchip | ✔️RKNN | - | - | - |
| Apple M1 | - | - | ✔️CoreML | - |
| Adreno GPU | - | - | - | ✔️ncnn<br>✔️SNPE |
| Hexagon DSP | - | - | - | ✔️SNPE |
### Efficient and scalable C/C++ SDK Framework

35
README_zh-CN.md
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@ -42,20 +42,31 @@ MMDeploy 是 [OpenMMLab](https://openmmlab.com/) 模型部署工具箱，**为
### 支持超多 OpenMMLab 算法库
- [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)
- [mmcls](docs/zh_cn/04-supported-codebases/mmcls.md)
- [mmdet](docs/zh_cn/04-supported-codebases/mmdet.md)
- [mmseg](docs/zh_cn/04-supported-codebases/mmseg.md)
- [mmedit](docs/zh_cn/04-supported-codebases/mmedit.md)
- [mmocr](docs/zh_cn/04-supported-codebases/mmocr.md)
- [mmpose](docs/zh_cn/04-supported-codebases/mmpose.md)
- [mmdet3d](docs/zh_cn/04-supported-codebases/mmdet3d.md)
- [mmrotate](docs/zh_cn/04-supported-codebases/mmrotate.md)
### 支持多种推理后端
| ONNX Runtime | TensorRT | ppl.nn | ncnn | OpenVINO | LibTorch | snpe | Ascend | Core ML | RKNN | more |
| ------------ | -------- | ------ | ---- | -------- | -------- | ---- | ------ | ------- | ---- | ---------------------------------------------- |
| ✔️ | ✔️ | ✔️ | ✔️ | ✔️ | ✔️ | ✔️ | ✔️ | ✔️ | ✔️ | [benchmark](docs/en/03-benchmark/benchmark.md) |
支持的设备平台和推理引擎如下表所示。benchmark请参考[这里](docs/zh_cn/03-benchmark/benchmark.md)
| Device / Platform | Linux | Windows | macOS | Android |
| ----------------- | --------------------------------------------------------------- | --------------------------------------- | -------- | ---------------- |
| x86_64 CPU | ✔️ONNX Runtime<br>✔️pplnn<br>✔️ncnn<br>✔️OpenVINO<br>✔️LibTorch | ✔️ONNX Runtime<br>✔️OpenVINO | - | - |
| ARM CPU | ✔️ncnn | - | - | ✔️ncnn |
| RISC-V | ✔️ncnn | - | - | - |
| NVIDIA GPU | ✔️ONNX Runtime<br>✔️TensorRT<br>✔️pplnn<br>✔️LibTorch | ✔️ONNX Runtime<br>✔️TensorRT<br>✔️pplnn | - | - |
| NVIDIA Jetson | ✔️TensorRT | ✔️TensorRT | - | - |
| Huawei ascend310 | ✔️CANN | - | - | - |
| Rockchip | ✔️RKNN | - | - | - |
| Apple M1 | - | - | ✔️CoreML | - |
| Adreno GPU | - | - | - | ✔️ncnn<br>✔️SNPE |
| Hexagon DSP | - | - | - | ✔️SNPE |
### SDK 可高度定制化
@ -73,7 +84,7 @@ MMDeploy 是 [OpenMMLab](https://openmmlab.com/) 模型部署工具箱，**为
- [Build for macOS](docs/zh_cn/01-how-to-build/macos-arm64.md)
- [Build for Win10](docs/zh_cn/01-how-to-build/windows.md)
- [Build for Android](docs/zh_cn/01-how-to-build/android.md)
- [Build for Jetson](docs/en/01-how-to-build/jetsons.md)
- [Build for Jetson](docs/zh_cn/01-how-to-build/jetsons.md)
- [Build for SNPE](docs/zh_cn/01-how-to-build/snpe.md)
- 使用
- [把模型转换到推理 Backend](docs/zh_cn/02-how-to-run/convert_model.md)