[Docs]Add docs about How to convert model (#132)

* add ncnn test exporter in test_ops.py * add ncnn test exporter in utils.py * add onnxruntime and tensorrt ops test * fix blank line * fix comment add nms ops test * remove nms test * add test sample add dockerstring * remove nms test * fix grid_sample add type hind * fix problem * fix dockerstring * add nms batch_nms multi_level_roi_align * add test data * fix problem * rm pkl file dependent * rm file * add docstring * remove multi_level_dependce * add mmseg module unittest * add mmseg test * add mmseg model unit test * fix blankline * rename file * add syncbn2bn unit test * add apis/export * lint * lint * ?? * delete# * fix problems * add mmcv unit test * add docs about how to convert model * fix docs convert model * add list * rm mmcv test * add mmocr model in list fix decription * fix docs * fix docs * refactor docs * fix model list * add docs about how to create config file * fix how to convert model * remove other docs * add cn docs * fix args description * fix space * fix about evaluate model * fix link problems * fix cn docs Co-authored-by: SingleZombie <singlezombie@163.com>
2025-01-14 08:09:43 +08:00 · 2021-10-25 17:25:45 +08:00 · 2021-10-25 17:25:45 +08:00 · a357ffa924
commit a357ffa924
parent 097a0281d4
2 changed files with 207 additions and 1 deletions
--- a/docs/tutorials/how_to_convert_model.md
+++ b/docs/tutorials/how_to_convert_model.md
@ -1,12 +1,109 @@
 ## How to convert model

+<!-- TOC -->
+
+- [Tutorial : How to convert model](#how-to-convert-model)
+    - [How to convert models from Pytorch to BACKEND](#how-to-convert-models-from-pytorch-to-other-backends)
+        - [Prerequisite](#prerequisite)
+        - [Usage](#usage)
+        - [Description of all arguments](#description-of-all-arguments)
+    - [How to evaluate the exported models](#how-to-evaluate-the-exported-models)
+    - [List of supported models exportable to BACKEND](#list-of-supported-models-exportable-to-other-backends)
+    - [Reminders](#reminders)
+    - [FAQs](#faqs)
+
+<!-- TOC -->
+
+This tutorial briefly introduces how to export an OpenMMlab model to a specific backend using MMDeploy tools.
+Notes:
+- Supported backends are [ONNXRuntime](../backends/onnxruntime.md), [TensorRT](../backends/tensorrt.md), [NCNN](../backends/ncnn.md), [PPL](../backends/ppl.md).
+- Supported codebases are [MMClassification](../codebases/mmcls.md), [MMDetection](../codebases/mmdet.md), [MMSegmentation](../codebases/mmseg.md), [MMOCR](../codebases/mmocr.md), [MMEditing](../codebases/mmedit.md).
+
+### How to convert models from Pytorch to other backends
+
+#### Prerequisite
+
+1. Install and build your target backend. You could refer to [ONNXRuntime-install](../backends/onnxruntime.md), [TensorRT-install](../backends/tensorrt.md), [NCNN-install](../backends/ncnn.md), [PPL-install](../backends/ppl.md) for more information.
+2. Install and build your target codebase. You could refer to [MMClassification-install](https://github.com/open-mmlab/mmclassification/blob/master/docs/install.md), [MMDetection-install](https://github.com/open-mmlab/mmdetection/blob/master/docs/get_started.md), [MMSegmentation-install](https://github.com/open-mmlab/mmsegmentation/blob/master/docs/get_started.md#installation), [MMOCR-install](https://github.com/open-mmlab/mmocr/blob/main/docs/install.md), [MMEditing-install](https://github.com/open-mmlab/mmediting/blob/master/docs/install.md).
+
+#### Usage
+
 ```bash
 python ./tools/deploy.py \
    ${DEPLOY_CFG_PATH} \
    ${MODEL_CFG_PATH} \
    ${MODEL_CHECKPOINT_PATH} \
    ${INPUT_IMG} \
+    --test-img ${TEST_IMG} \
    --work-dir ${WORK_DIR} \
+    --calib-dataset-cfg ${CALIB_DATA_CFG} \
    --device ${DEVICE} \
-    --log-level INFO
+    --log-level INFO \
+    --show \
+    --dump-info
 ```
+
+#### Description of all arguments
+
+- `deploy_cfg` : The path of deploy config file in MMDeploy codebase.
+- `model_cfg` : The path of model config file in OpenMMLab codebase.
+- `checkpoint` : The path of model checkpoint file.
+- `img` : The path of image file that used to convert model.
+- `--test-img` : The path of image file that used to test model. If not specified, it will be set to `None`.
+- `--work-dir` : The path of work directory that used to save logs and models.
+- `--calib-dataset-cfg` : Config used for calibration. If not specified, it will be set to `None`.
+- `--device` : The device used for conversion. If not specified, it will be set to `cpu`.
+- `--log-level` : To set log level which in `'CRITICAL', 'FATAL', 'ERROR', 'WARN', 'WARNING', 'INFO', 'DEBUG', 'NOTSET'`. If not specified, it will be set to `INFO`.
+- `--show` : Whether to show detection outputs.
+- `--dump-info` : Whether to output information for SDK.
+
+#### Example
+
+```bash
+python ./tools/deploy.py \
+    configs/mmdet/single-stage/single-stage_tensorrt_dynamic-320x320-1344x1344.py \
+    $PATH_TO_MMDET/configs/yolo/yolov3_d53_mstrain-608_273e_coco.py \
+    $PATH_TO_MMDET/checkpoints/yolo/yolov3_d53_mstrain-608_273e_coco.pth \
+    $PATH_TO_MMDET/demo/demo.jpg \
+    --work-dir work_dir \
+    --show
+```
+
+### How to evaluate the exported models
+
+You can try to evaluate model, referring to [how_to_evaluate_a_model](./how_to_evaluate_a_model.md).
+
+### List of supported models exportable to other backends
+
+The table below lists the models that are guaranteed to be exportable to other backend.
+
+|    Model     |     codebase     | model config file(example)                                                                | OnnxRuntime |    TensorRT   | NCNN |  PPL  |
+| :----------: | :--------------: | :---------------------------------------------------------------------------------------: | :---------: | :-----------: | :---:| :---: |
+| RetinaNet    | MMDetection      | $PATH_TO_MMDET/configs/retinanet/retinanet_r50_fpn_1x_coco.py                             |      Y      |       Y       |   Y  |   Y   |
+| Faster R-CNN | MMDetection      | $PATH_TO_MMDET/configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py                         |      Y      |       Y       |   Y  |   Y   |
+| YOLOv3       | MMDetection      | $PATH_TO_MMDET/configs/yolo/yolov3_d53_mstrain-608_273e_coco.py                           |      Y      |       Y       |   N  |   Y   |
+| FCOS         | MMDetection      | $PATH_TO_MMDET/configs/fcos/fcos_r50_caffe_fpn_gn-head_4x4_1x_coco.py                     |      Y      |       Y       |   Y  |   N   |
+| FSAF         | MMDetection      | $PATH_TO_MMDET/configs/fsaf/fsaf_r50_fpn_1x_coco.py                                       |      Y      |       Y       |   Y  |   Y   |
+| Mask R-CNN   | MMDetection      | $PATH_TO_MMDET/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py                             |      Y      |       Y       |   N  |   Y   |
+| ResNet       | MMClassification | $PATH_TO_MMCLS/configs/resnet/resnet18_b32x8_imagenet.py                                  |      Y      |       Y       |   Y  |   Y   |
+| ResNeXt      | MMClassification | $PATH_TO_MMCLS/configs/resnext/resnext50_32x4d_b32x8_imagenet.py                          |      Y      |       Y       |   Y  |   Y   |
+| SE-ResNet    | MMClassification | $PATH_TO_MMCLS/configs/seresnet/seresnet50_b32x8_imagenet.py                              |      Y      |       Y       |   Y  |   Y   |
+| MobileNetV2  | MMClassification | $PATH_TO_MMCLS/configs/mobilenet_v2/mobilenet_v2_b32x8_imagenet.py                        |      Y      |       Y       |   Y  |   Y   |
+| ShuffleNetV1 | MMClassification | $PATH_TO_MMCLS/configs/shufflenet_v1/shufflenet_v1_1x_b64x16_linearlr_bn_nowd_imagenet.py |      Y      |       Y       |   N  |   Y   |
+| ShuffleNetV2 | MMClassification | $PATH_TO_MMCLS/configs/shufflenet_v2/shufflenet_v2_1x_b64x16_linearlr_bn_nowd_imagenet.py |      Y      |       Y       |   N  |   Y   |
+| FCN          | MMSegmentation   | $PATH_TO_MMSEG/configs/fcn/fcn_r50-d8_512x1024_40k_cityscapes.py                          |      Y      |       Y       |   Y  |   Y   |
+| PSPNet       | MMSegmentation   | $PATH_TO_MMSEG/configs/pspnet/pspnet_r50-d8_512x1024_40k_cityscapes.py                    |      Y      |       Y       |   N  |   Y   |
+| DeepLabV3    | MMSegmentation   | $PATH_TO_MMSEG/configs/deeplabv3/deeplabv3_r50-d8_512x1024_40k_cityscapes.py              |      Y      |       Y       |   Y  |   Y   |
+| DeepLabV3+   | MMSegmentation   | $PATH_TO_MMSEG/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_40k_cityscapes.py      |      Y      |       Y       |   Y  |   Y   |
+| SRCNN        | MMEditing        | $PATH_TO_MMSEG/configs/restorers/srcnn/srcnn_x4k915_g1_1000k_div2k.py                     |      Y      |       Y       |   N  |   Y   |
+| ESRGAN       | MMEditing        | $PATH_TO_MMSEG/configs/restorers/esrgan/esrgan_psnr_x4c64b23g32_g1_1000k_div2k.py         |      Y      |       Y       |   N  |   Y   |
+| DBNet        | MMOCR            | $PATH_TO_MMOCR/configs/textdet/dbnet/dbnet_r50dcnv2_fpnc_1200e_icdar2015.py               |      Y      |       Y       |   Y  |   Y   |
+| CRNN         | MMOCR            | $PATH_TO_MMOCR/configs/textrecog/tps/crnn_tps_academic_dataset.py                         |      Y      |       Y       |   Y  |   N   |
+
+### Reminders
+
+- None
+
+### FAQs
+
+- None
--- a/docs_zh_CN/tutorials/how_to_convert_model.md
+++ b/docs_zh_CN/tutorials/how_to_convert_model.md
@ -1 +1,110 @@
 ## 如何转换模型
+
+<!-- TOC -->
+
+- [教程 : 如何转换模型](#如何转换模型)
+    - [如何将模型从pytorch形式转换成其他后端形式](#如何将模型从pytorch形式转换成其他后端形式)
+        - [准备工作](#准备工作)
+        - [使用方法](#使用方法)
+        - [参数描述](#参数描述)
+    - [如何评测模型](#如何评测模型)
+    - [各后端已支持导出的模型列表](#各后端已支持导出的模型列表)
+    - [注意事项](#注意事项)
+    - [问答](#问答)
+
+<!-- TOC -->
+
+这篇教程介绍了如何使用 MMDeploy 的工具将一个 OpenMMlab 模型转换成某个后端的模型文件。
+
+注意:
+- 现在已支持的后端包括 [ONNX Runtime](../backends/onnxruntime.md) ，[TensorRT](../backends/tensorrt.md) ，[NCNN](../backends/ncnn.md) ，[PPL](../backends/ppl.md)。
+- 现在已支持的代码库包括 [MMClassification](../codebases/mmcls.md) ，[MMDetection](../codebases/mmdet.md) ，[MMSegmentation](../codebases/mmseg.md) ，[MMOCR](../codebases/mmocr.md) ，[MMEditing](../codebases/mmedit.md)。
+
+### 如何将模型从pytorch形式转换成其他后端形式
+
+#### 准备工作
+
+1. 安装你的目标后端。 你可以参考 [ONNXRuntime-install](../backends/onnxruntime.md) ，[TensorRT-install](../backends/tensorrt.md) ，[NCNN-install](../backends/ncnn.md) ，[PPL-install](../backends/ppl.md)。
+2. 安装你的目标代码库。 你可以参考 [MMClassification-install](https://github.com/open-mmlab/mmclassification/blob/master/docs/install.md) ，[MMDetection-install](https://github.com/open-mmlab/mmdetection/blob/master/docs/get_started.md) ，[MMSegmentation-install](https://github.com/open-mmlab/mmsegmentation/blob/master/docs/get_started.md#installation) ，[MMOCR-install](https://github.com/open-mmlab/mmocr/blob/main/docs/install.md) ，[MMEditing-install](https://github.com/open-mmlab/mmediting/blob/master/docs/install.md) 。
+
+#### 使用方法
+
+```bash
+python ./tools/deploy.py \
+    ${DEPLOY_CFG_PATH} \
+    ${MODEL_CFG_PATH} \
+    ${MODEL_CHECKPOINT_PATH} \
+    ${INPUT_IMG} \
+    --test-img ${TEST_IMG} \
+    --work-dir ${WORK_DIR} \
+    --calib-dataset-cfg ${CALIB_DATA_CFG} \
+    --device ${DEVICE} \
+    --log-level INFO \
+    --show \
+    --dump-info
+```
+
+#### 参数描述
+
+- `deploy_cfg` : MMDeploy 中用于部署的配置文件路径。
+- `model_cfg` : OpenMMLab 系列代码库中使用的模型配置文件路径。
+- `checkpoint` : OpenMMLab 系列代码库的模型文件路径。
+- `img` : 用于模型转换时使用的图像文件路径。
+- `--test-img` : 用于测试模型的图像文件路径。默认设置成`None`。
+- `--work-dir` : 工作目录，用来保存日志和模型文件。
+- `--calib-dataset-cfg` : 用于校准的配置文件。默认是`None`。
+- `--device` : 用于模型转换的设备。 默认是`cpu`。
+- `--log-level` : 设置日记的等级，选项包括`'CRITICAL'， 'FATAL'， 'ERROR'， 'WARN'， 'WARNING'， 'INFO'， 'DEBUG'， 'NOTSET'`。 默认是`INFO`。
+- `--show` : 是否显示检测的结果。
+- `--dump-info` : 是否输出 SDK 信息。
+
+#### 示例
+
+```bash
+python ./tools/deploy.py \
+    configs/mmdet/single-stage/single-stage_tensorrt_dynamic-320x320-1344x1344.py \
+    $PATH_TO_MMDET/configs/yolo/yolov3_d53_mstrain-608_273e_coco.py \
+    $PATH_TO_MMDET/checkpoints/yolo/yolov3_d53_mstrain-608_273e_coco.pth \
+    $PATH_TO_MMDET/demo/demo.jpg \
+    --work-dir work_dir \
+    --show
+```
+
+### 如何评测模型
+
+你可以尝试去评测转换出来的模型 ，参考 [how_to_evaluate_a_model](./how_to_evaluate_a_model.md)。
+
+### 各后端已支持导出的模型列表
+
+下列列表显示了目前哪些模型是可以导出的以及其支持的后端。
+
+|    模型       |     代码库        | 模型配置文件(示例)                                                                           | OnnxRuntime |    TensorRT   | NCNN |  PPL  |
+| :----------: | :--------------: | :---------------------------------------------------------------------------------------: | :---------: | :-----------: | :---:| :---: |
+| RetinaNet    | MMDetection      | $PATH_TO_MMDET/configs/retinanet/retinanet_r50_fpn_1x_coco.py                             |      Y      |       Y       |   Y  |   Y   |
+| Faster R-CNN | MMDetection      | $PATH_TO_MMDET/configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py                         |      Y      |       Y       |   Y  |   Y   |
+| YOLOv3       | MMDetection      | $PATH_TO_MMDET/configs/yolo/yolov3_d53_mstrain-608_273e_coco.py                           |      Y      |       Y       |   N  |   Y   |
+| FCOS         | MMDetection      | $PATH_TO_MMDET/configs/fcos/fcos_r50_caffe_fpn_gn-head_4x4_1x_coco.py                     |      Y      |       Y       |   Y  |   N   |
+| FSAF         | MMDetection      | $PATH_TO_MMDET/configs/fsaf/fsaf_r50_fpn_1x_coco.py                                       |      Y      |       Y       |   Y  |   Y   |
+| Mask R-CNN   | MMDetection      | $PATH_TO_MMDET/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py                             |      Y      |       Y       |   N  |   Y   |
+| ResNet       | MMClassification | $PATH_TO_MMCLS/configs/resnet/resnet18_b32x8_imagenet.py                                  |      Y      |       Y       |   Y  |   Y   |
+| ResNeXt      | MMClassification | $PATH_TO_MMCLS/configs/resnext/resnext50_32x4d_b32x8_imagenet.py                          |      Y      |       Y       |   Y  |   Y   |
+| SE-ResNet    | MMClassification | $PATH_TO_MMCLS/configs/seresnet/seresnet50_b32x8_imagenet.py                              |      Y      |       Y       |   Y  |   Y   |
+| MobileNetV2  | MMClassification | $PATH_TO_MMCLS/configs/mobilenet_v2/mobilenet_v2_b32x8_imagenet.py                        |      Y      |       Y       |   Y  |   Y   |
+| ShuffleNetV1 | MMClassification | $PATH_TO_MMCLS/configs/shufflenet_v1/shufflenet_v1_1x_b64x16_linearlr_bn_nowd_imagenet.py |      Y      |       Y       |   N  |   Y   |
+| ShuffleNetV2 | MMClassification | $PATH_TO_MMCLS/configs/shufflenet_v2/shufflenet_v2_1x_b64x16_linearlr_bn_nowd_imagenet.py |      Y      |       Y       |   N  |   Y   |
+| FCN          | MMSegmentation   | $PATH_TO_MMSEG/configs/fcn/fcn_r50-d8_512x1024_40k_cityscapes.py                          |      Y      |       Y       |   Y  |   Y   |
+| PSPNet       | MMSegmentation   | $PATH_TO_MMSEG/configs/pspnet/pspnet_r50-d8_512x1024_40k_cityscapes.py                    |      Y      |       Y       |   N  |   Y   |
+| DeepLabV3    | MMSegmentation   | $PATH_TO_MMSEG/configs/deeplabv3/deeplabv3_r50-d8_512x1024_40k_cityscapes.py              |      Y      |       Y       |   Y  |   Y   |
+| DeepLabV3+   | MMSegmentation   | $PATH_TO_MMSEG/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_40k_cityscapes.py      |      Y      |       Y       |   Y  |   Y   |
+| SRCNN        | MMEditing        | $PATH_TO_MMSEG/configs/restorers/srcnn/srcnn_x4k915_g1_1000k_div2k.py                     |      Y      |       Y       |   N  |   Y   |
+| ESRGAN       | MMEditing        | $PATH_TO_MMSEG/configs/restorers/esrgan/esrgan_psnr_x4c64b23g32_g1_1000k_div2k.py         |      Y      |       Y       |   N  |   Y   |
+| DBNet        | MMOCR            | $PATH_TO_MMOCR/configs/textdet/dbnet/dbnet_r50dcnv2_fpnc_1200e_icdar2015.py               |      Y      |       Y       |   Y  |   Y   |
+| CRNN         | MMOCR            | $PATH_TO_MMOCR/configs/textrecog/tps/crnn_tps_academic_dataset.py                         |      Y      |       Y       |   Y  |   N   |
+
+### 注意事项
+
+- None
+
+### 问答
+
+- None