From a357ffa924f7dd4d13cd8b8ce75d4a67be1f69f7 Mon Sep 17 00:00:00 2001 From: VVsssssk <88368822+VVsssssk@users.noreply.github.com> Date: Mon, 25 Oct 2021 17:25:45 +0800 Subject: [PATCH] [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 --- docs/tutorials/how_to_convert_model.md | 99 ++++++++++++++++- docs_zh_CN/tutorials/how_to_convert_model.md | 109 +++++++++++++++++++ 2 files changed, 207 insertions(+), 1 deletion(-) diff --git a/docs/tutorials/how_to_convert_model.md b/docs/tutorials/how_to_convert_model.md index db6c8b9e8..37ce95c8c 100644 --- a/docs/tutorials/how_to_convert_model.md +++ b/docs/tutorials/how_to_convert_model.md @@ -1,12 +1,109 @@ ## How to convert model + + +- [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) + + + +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 diff --git a/docs_zh_CN/tutorials/how_to_convert_model.md b/docs_zh_CN/tutorials/how_to_convert_model.md index e1af1dec0..bddc8cac4 100644 --- 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 + + + +- [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) + + + +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