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## How to convert model
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<!-- 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:
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- Supported backends are [ONNXRuntime ](../backends/onnxruntime.md ), [TensorRT ](../backends/tensorrt.md ), [NCNN ](../backends/ncnn.md ), [PPL ](../backends/ppl.md ), [OpenVINO ](../backends/openvino.md ).
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- 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
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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 ), [OpenVINO-install ](../backends/openvino.md ) for more information.
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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
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```bash
python ./tools/deploy.py \
${DEPLOY_CFG_PATH} \
${MODEL_CFG_PATH} \
${MODEL_CHECKPOINT_PATH} \
${INPUT_IMG} \
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--test-img ${TEST_IMG} \
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--work-dir ${WORK_DIR} \
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--calib-dataset-cfg ${CALIB_DATA_CFG} \
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--device ${DEVICE} \
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--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 \
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--show \
--device cuda:0
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```
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### 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.
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| Model | codebase | model config file(example) | OnnxRuntime | TensorRT | NCNN | PPL | OpenVINO |
| :----------------: | :--------------: | :---------------------------------------------------------------------------------------: | :---------: | :-----------: | :---:| :---: | :-------: |
| RetinaNet | MMDetection | $PATH_TO_MMDET/configs/retinanet/retinanet_r50_fpn_1x_coco.py | Y | 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 | Y |
| YOLOv3 | MMDetection | $PATH_TO_MMDET/configs/yolo/yolov3_d53_mstrain-608_273e_coco.py | Y | Y | N | Y | N |
| FCOS | MMDetection | $PATH_TO_MMDET/configs/fcos/fcos_r50_caffe_fpn_gn-head_4x4_1x_coco.py | Y | Y | Y | N | Y |
| FSAF | MMDetection | $PATH_TO_MMDET/configs/fsaf/fsaf_r50_fpn_1x_coco.py | Y | 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 | Y |
| SSD | MMDetection | $PATH_TO_MMDET/configs/ssd/ssd300_coco.py | Y | ? | ? | ? | Y |
| Cascade R-CNN | MMDetection | $PATH_TO_MMDET/configs/cascade_rcnn/cascade_rcnn_r50_fpn_1x_coco.py | Y | ? | ? | ? | Y |
| Cascade Mask R-CNN | MMDetection | $PATH_TO_MMDET/configs/cascade_rcnn/cascade_mask_rcnn_r50_fpn_1x_coco.py | Y | ? | ? | ? | Y |
| ResNet | MMClassification | $PATH_TO_MMCLS/configs/resnet/resnet18_b32x8_imagenet.py | Y | Y | Y | Y | N |
| ResNeXt | MMClassification | $PATH_TO_MMCLS/configs/resnext/resnext50_32x4d_b32x8_imagenet.py | Y | Y | Y | Y | N |
| SE-ResNet | MMClassification | $PATH_TO_MMCLS/configs/seresnet/seresnet50_b32x8_imagenet.py | Y | Y | Y | Y | N |
| MobileNetV2 | MMClassification | $PATH_TO_MMCLS/configs/mobilenet_v2/mobilenet_v2_b32x8_imagenet.py | Y | Y | Y | Y | N |
| ShuffleNetV1 | MMClassification | $PATH_TO_MMCLS/configs/shufflenet_v1/shufflenet_v1_1x_b64x16_linearlr_bn_nowd_imagenet.py | Y | Y | N | Y | N |
| ShuffleNetV2 | MMClassification | $PATH_TO_MMCLS/configs/shufflenet_v2/shufflenet_v2_1x_b64x16_linearlr_bn_nowd_imagenet.py | Y | Y | N | Y | N |
| FCN | MMSegmentation | $PATH_TO_MMSEG/configs/fcn/fcn_r50-d8_512x1024_40k_cityscapes.py | Y | Y | Y | Y | N |
| PSPNet | MMSegmentation | $PATH_TO_MMSEG/configs/pspnet/pspnet_r50-d8_512x1024_40k_cityscapes.py | Y | Y | N | Y | N |
| DeepLabV3 | MMSegmentation | $PATH_TO_MMSEG/configs/deeplabv3/deeplabv3_r50-d8_512x1024_40k_cityscapes.py | Y | Y | Y | Y | N |
| DeepLabV3+ | MMSegmentation | $PATH_TO_MMSEG/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_40k_cityscapes.py | Y | Y | Y | Y | N |
| SRCNN | MMEditing | $PATH_TO_MMSEG/configs/restorers/srcnn/srcnn_x4k915_g1_1000k_div2k.py | Y | Y | N | Y | N |
| ESRGAN | MMEditing | $PATH_TO_MMSEG/configs/restorers/esrgan/esrgan_psnr_x4c64b23g32_g1_1000k_div2k.py | Y | Y | N | Y | N |
| DBNet | MMOCR | $PATH_TO_MMOCR/configs/textdet/dbnet/dbnet_r50dcnv2_fpnc_1200e_icdar2015.py | Y | Y | Y | Y | N |
| CRNN | MMOCR | $PATH_TO_MMOCR/configs/textrecog/tps/crnn_tps_academic_dataset.py | Y | Y | Y | N | N |
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### Reminders
- None
### FAQs
- None
