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[Doc]: Fix doc (open-mmlab#219)
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* add reminder for pspnet in doc

* update table format

* fix format

* rename file

* fix comment
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RunningLeon authored Nov 25, 2021
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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -47,7 +47,7 @@ Please refer to [get_started.md](docs/get_started.md) for installation.

## Getting Started

Please read [get_started.md](docs/get_started.md) for the basic usage of MMDeploy. There are also tutorials for [how to convert a model](docs/tutorials/how_to_convert_model.md), [how to write a config](docs/tutorials/how_to_write_config.md), [how to support new models](docs/tutorials/how_to_support_new_models.md) and [how to test model](docs/tutorials/how_to_test_model.md).
Please read [how_to_convert_model.md](docs/tutorials/how_to_convert_model.md) for the basic usage of MMDeploy. There are also tutorials on [how to write config](docs/tutorials/how_to_write_config.md), [how to support new models](docs/tutorials/how_to_support_new_models.md) and [how to measure performance of models](docs/tutorials/how_to_measure_performance_of_models.md).

Please refer to [FAQ](docs/faq.md) for frequently asked questions.

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2 changes: 1 addition & 1 deletion README_zh-CN.md
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Expand Up @@ -47,7 +47,7 @@ MMDeploy 是一个开源深度学习模型部署工具箱,它是 [OpenMMLab](h

请阅读 [如何进行模型转换](docs/tutorials/how_to_convert_model.md) 来了解基本的 MMDeploy 使用。

我们还提供了诸如 [如何编写配置文件](docs/tutorials/how_to_write_config.md)[如何添加新模型支持](docs/tutorials/how_to_support_new_models.md)[如何测试模型效果](docs/tutorials/how_to_test_model.md) 等教程。
我们还提供了诸如 [如何编写配置文件](docs/tutorials/how_to_write_config.md)[如何添加新模型支持](docs/tutorials/how_to_support_new_models.md)[如何测试模型效果](docs/tutorials/how_to_measure_performance_of_models.md) 等教程。

如果遇到问题,请参考 [常见问题解答](docs/faq.md)

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16 changes: 9 additions & 7 deletions docs/codebases/mmseg.md
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Expand Up @@ -8,16 +8,18 @@ Please refer to [get_started.md](https://github.com/open-mmlab/mmsegmentation/bl

### List of MMSegmentation models supported by MMDeploy

| model | OnnxRuntime | TensorRT | NCNN | PPL | OpenVino | model config file(example) |
|:---------- | :---------: | :-----------: | :---:| :---: | :------: | :--------------------------------------------------------------------------------------- |
| FCN | Y | Y | Y | Y | ? | $PATH_TO_MMSEG/configs/fcn/fcn_r50-d8_512x1024_40k_cityscapes.py |
| PSPNet | Y | Y | N | Y | ? | $PATH_TO_MMSEG/configs/pspnet/pspnet_r50-d8_512x1024_40k_cityscapes.py |
| DeepLabV3 | Y | Y | Y | Y | ? | $PATH_TO_MMSEG/configs/deeplabv3/deeplabv3_r50-d8_512x1024_40k_cityscapes.py |
| DeepLabV3+ | Y | Y | Y | Y | ? | $PATH_TO_MMSEG/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_40k_cityscapes.py |
| model | OnnxRuntime | TensorRT | NCNN | PPL | OpenVino | model config file(example) |
|:------------------------------|:-----------:|:--------:|:----:|:---:|:--------:|:-----------------------------------------------------------------------------------|
| FCN | Y | Y | Y | Y | ? | ${MMSEG_DIR}/configs/fcn/fcn_r50-d8_512x1024_40k_cityscapes.py |
| PSPNet[*](#pspnet) | Y | Y | N | Y | ? | ${MMSEG_DIR}/configs/pspnet/pspnet_r50-d8_512x1024_40k_cityscapes.py |
| DeepLabV3 | Y | Y | Y | Y | ? | ${MMSEG_DIR}/configs/deeplabv3/deeplabv3_r50-d8_512x1024_40k_cityscapes.py |
| DeepLabV3+ | Y | Y | Y | Y | ? | ${MMSEG_DIR}/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_40k_cityscapes.py |

### Reminder

None
- Only `whole` inference mode is supported for all mmseg models.

- <i id="pspnet">PSPNet</i> only supports static shape, better to use the deployment config file of static shape such as `configs/mmseg/segmentation_tensorrt_static-512x1024.py`. Because [nn.AdaptiveAvgPool2d](https://github.com/open-mmlab/mmsegmentation/blob/97f9670c5a4a2a3b4cfb411bcc26db16b23745f7/mmseg/models/decode_heads/psp_head.py#L38) in psp_head is not supported in most of backends dynamically.

### FAQs

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2 changes: 1 addition & 1 deletion docs/index.rst
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Expand Up @@ -16,7 +16,7 @@ You can switch between Chinese and English documents in the lower-left corner of
tutorials/how_to_convert_model.md
tutorials/how_to_write_config.md
tutorials/how_to_evaluate_a_model.md
tutorials/how_to_test_model.md
tutorials/how_to_measure_performance_of_models.md
tutorials/how_to_support_new_models.md
tutorials/how_to_add_test_units_for_backend_ops.md
tutorials/how_to_test_rewritten_models.md
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## How to test model
# How to measure the performance of a model

After we convert a PyTorch model to a backend model, we may need to test the speed of the model before using it. In MMDeploy, we provide a tool to test the speed of backend models in `tools/test.py`

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