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[Doc]polish docs #6623

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Dec 2, 2021
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[Doc]polish docs #6623

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67e49ca
polish docs
jshilong Nov 29, 2021
7bd36f0
Merge branch 'master' of https://github.com/open-mmlab/mmdetection in…
jshilong Dec 2, 2021
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4 changes: 2 additions & 2 deletions mmdet/models/dense_heads/base_dense_head.py
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Original file line number Diff line number Diff line change
Expand Up @@ -227,13 +227,13 @@ def _bbox_post_process(self,
"""bbox post-processing method.

The boxes would be rescaled to the original image scale and do
the nms operation. Usually with_nms is False is used for aug test.
the nms operation. Usually `with_nms` is False is used for aug test.

Args:
mlvl_scores (list[Tensor]): Box scores from all scale
levels of a single image, each item has shape
(num_bboxes, ).
mlvl_labels (list[Tensor]): Box class labels from all scale
mlvl_labels (list[Tensor]): Box class labels from all scale
levels of a single image, each item has shape
(num_bboxes, ).
mlvl_bboxes (list[Tensor]): Decoded bboxes from all scale
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9 changes: 4 additions & 5 deletions mmdet/models/dense_heads/rpn_head.py
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Expand Up @@ -190,22 +190,21 @@ def _bbox_post_process(self, mlvl_scores, mlvl_bboxes, mlvl_valid_anchors,
level_ids, cfg, img_shape, **kwargs):
"""bbox post-processing method.

The boxes would be rescaled to the original image scale and do
the nms operation. Usually with_nms is False is used for aug test.
Do the nms operation for bboxes in same level.

Args:
mlvl_scores (list[Tensor]): Box scores from all scale
levels of a single image, each item has shape
(num_bboxes, num_class).
(num_bboxes, ).
mlvl_bboxes (list[Tensor]): Decoded bboxes from all scale
levels of a single image, each item has shape (num_bboxes, 4).
mlvl_valid_anchors (list[Tensor]): Anchors of all scale level
each item has shape (num_bboxes, 4).
level_ids (list[Tensor]): Indexes from all scale levels of a
single image, each item has shape (num_bboxes, ).
cfg (mmcv.Config): Test / postprocessing configuration,
if None, test_cfg would be used.
img_shape (tuple(int)): Shape of current image.
if None, `self.test_cfg` would be used.
img_shape (tuple(int)): The shape of model's input image.

Returns:
Tensor: Labeled boxes in shape (n, 5), where the first 4 columns
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9 changes: 5 additions & 4 deletions mmdet/models/roi_heads/bbox_heads/bbox_head.py
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Expand Up @@ -131,11 +131,12 @@ def _get_target_single(self, pos_bboxes, neg_bboxes, pos_gt_bboxes,
neg_bboxes (Tensor): Contains all the negative boxes,
has shape (num_neg, 4), the last dimension 4
represents [tl_x, tl_y, br_x, br_y].
pos_gt_bboxes (Tensor): Contains all the gt_boxes,
has shape (num_gt, 4), the last dimension 4
pos_gt_bboxes (Tensor): Contains gt_boxes for
all positive samples, has shape (num_pos, 4),
the last dimension 4
represents [tl_x, tl_y, br_x, br_y].
pos_gt_labels (Tensor): Contains all the gt_labels,
has shape (num_gt).
pos_gt_labels (Tensor): Contains gt_labels for
all positive samples, has shape (num_pos, ).
cfg (obj:`ConfigDict`): `train_cfg` of R-CNN.

Returns:
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9 changes: 5 additions & 4 deletions mmdet/models/roi_heads/bbox_heads/dii_head.py
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Expand Up @@ -305,11 +305,12 @@ def _get_target_single(self, pos_inds, neg_inds, pos_bboxes, neg_bboxes,
neg_bboxes (Tensor): Contains all the negative boxes,
has shape (num_neg, 4), the last dimension 4
represents [tl_x, tl_y, br_x, br_y].
pos_gt_bboxes (Tensor): Contains all the gt_boxes,
has shape (num_gt, 4), the last dimension 4
pos_gt_bboxes (Tensor): Contains gt_boxes for
all positive samples, has shape (num_pos, 4),
the last dimension 4
represents [tl_x, tl_y, br_x, br_y].
pos_gt_labels (Tensor): Contains all the gt_labels,
has shape (num_gt).
pos_gt_labels (Tensor): Contains gt_labels for
all positive samples, has shape (num_pos, ).
cfg (obj:`ConfigDict`): `train_cfg` of R-CNN.

Returns:
Expand Down