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support htc (#2438)
* support htc * update mmdet.yml
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‎docs/en/04-supported-codebases/mmdet.md‎

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@@ -214,6 +214,7 @@ Besides python API, mmdeploy SDK also provides other FFI (Foreign Function Inter
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| [CenterNet](https://github.com/open-mmlab/mmdetection/tree/main/configs/centernet) | Object Detection | Y | Y | N | ? | Y |
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| [RTMDet](https://github.com/open-mmlab/mmdetection/tree/main/configs/rtmdet) | Object Detection | Y | Y | N | ? | Y |
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| [Cascade Mask R-CNN](https://github.com/open-mmlab/mmdetection/tree/main/configs/cascade_rcnn) | Instance Segmentation | Y | Y | N | N | Y |
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| [HTC](https://github.com/open-mmlab/mmdetection/tree/main/configs/htc) | Instance Segmentation | Y | Y | N | ? | Y |
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| [Mask R-CNN](https://github.com/open-mmlab/mmdetection/tree/main/configs/mask_rcnn) | Instance Segmentation | Y | Y | N | N | Y |
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| [Swin Transformer](https://github.com/open-mmlab/mmdetection/tree/main/configs/swin) | Instance Segmentation | Y | Y | N | N | Y |
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| [SOLO](https://github.com/open-mmlab/mmdetection/tree/main/configs/solo) | Instance Segmentation | Y | N | N | N | Y |

‎docs/zh_cn/04-supported-codebases/mmdet.md‎

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| [CenterNet](https://github.com/open-mmlab/mmdetection/tree/main/configs/centernet) | Object Detection | Y | Y | N | ? | Y |
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| [RTMDet](https://github.com/open-mmlab/mmdetection/tree/main/configs/rtmdet) | Object Detection | Y | Y | N | ? | Y |
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| [Cascade Mask R-CNN](https://github.com/open-mmlab/mmdetection/tree/main/configs/cascade_rcnn) | Instance Segmentation | Y | Y | N | N | Y |
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| [HTC](https://github.com/open-mmlab/mmdetection/tree/main/configs/htc) | Instance Segmentation | Y | Y | N | ? | Y |
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| [Mask R-CNN](https://github.com/open-mmlab/mmdetection/tree/main/configs/mask_rcnn) | Instance Segmentation | Y | Y | N | N | Y |
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| [Swin Transformer](https://github.com/open-mmlab/mmdetection/tree/main/configs/swin) | Instance Segmentation | Y | Y | N | N | Y |
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| [SOLO](https://github.com/open-mmlab/mmdetection/tree/main/configs/solo) | Instance Segmentation | Y | N | N | N | Y |

‎mmdeploy/codebase/mmdet/models/roi_heads/__init__.py‎

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from . import bbox_head # noqa: F401,F403
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from . import cascade_roi_head # noqa: F401,F403
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from . import fcn_mask_head # noqa: F401,F403
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from . import htc_roi_head # noqa: F401,F403
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from . import single_level_roi_extractor # noqa: F401,F403
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from . import standard_roi_head # noqa: F401,F403

‎mmdeploy/codebase/mmdet/models/roi_heads/cascade_roi_head.py‎

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batch_img_metas: List[dict],
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rpn_results_list: List[Tensor],
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rcnn_test_cfg: ConfigType,
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rescale: bool = False) -> List[Tensor]:
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rescale: bool = False,
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**kwargs) -> List[Tensor]:
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"""Rewrite `predict_bbox` of `CascadeRoIHead` for default backend.
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Args:
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ms_scores = []
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max_shape = batch_img_metas[0]['img_shape']
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for i in range(self.num_stages):
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bbox_results = self._bbox_forward(i, x, rois)
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bbox_results = self._bbox_forward(i, x, rois, **kwargs)
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cls_score = bbox_results['cls_score']
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bbox_pred = bbox_results['bbox_pred']
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# Recover the batch dimension

‎mmdeploy/codebase/mmdet/models/roi_heads/htc_roi_head.py‎

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# Copyright (c) OpenMMLab. All rights reserved.
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from typing import List, Tuple
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import torch
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from torch import Tensor
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from mmdeploy.core import FUNCTION_REWRITER
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@FUNCTION_REWRITER.register_rewriter(
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'mmdet.models.roi_heads.htc_roi_head.HybridTaskCascadeRoIHead.predict_mask'
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)
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def htc_roi_head__predict_mask(self,
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x: Tuple[Tensor],
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semantic_heat: Tensor,
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batch_img_metas: List[dict],
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results_list: List[Tensor],
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rescale: bool = False) -> List[Tensor]:
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dets, det_labels = results_list
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batch_size = dets.size(0)
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det_bboxes = dets[..., :4]
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batch_index = torch.arange(
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det_bboxes.size(0),
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device=det_bboxes.device).float().view(-1, 1, 1).expand(
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det_bboxes.size(0), det_bboxes.size(1), 1)
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mask_rois = torch.cat([batch_index, det_bboxes], dim=-1)
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mask_rois = mask_rois.view(-1, 5)
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mask_results = self._mask_forward(
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stage=-1,
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x=x,
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rois=mask_rois,
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semantic_feat=semantic_heat,
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training=False)
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mask_preds = mask_results['mask_preds'][0]
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num_det = det_bboxes.shape[1]
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segm_results = self.mask_head[-1].predict_by_feat(
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mask_preds,
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results_list,
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batch_img_metas,
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self.test_cfg,
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rescale=rescale)
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segm_results = segm_results.reshape(batch_size, num_det,
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segm_results.shape[-2],
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segm_results.shape[-1])
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return dets, det_labels, segm_results

‎tests/regression/mmdet.yml‎

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backend_test: *default_backend_test
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- deploy_config: configs/mmdet/instance-seg/instance-seg_tensorrt_dynamic-320x320-1344x1344.py
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backend_test: *default_backend_test
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- name: HTC
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metafile: configs/htc/metafile.yml
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model_configs:
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- configs/htc/htc_r50_fpn_1x_coco.py
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pipelines:
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- *pipeline_seg_ort_dynamic_fp32
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- *pipeline_seg_trt_dynamic_fp32

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