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ultralytics 8.0.80 single-line docstring fixes (#2060)

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Glenn Jocher 2023-04-16 15:20:11 +02:00 • committed by GitHub
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48 changed files with 418 additions and 420 deletions
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16
ultralytics/yolo/utils/tal.py
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@ -48,7 +48,7 @@ def select_highest_overlaps(mask_pos, overlaps, n_max_boxes):
is_max_overlaps = is_max_overlaps.permute(0, 2, 1).to(overlaps.dtype) # (b, n_max_boxes, h*w)
mask_pos = torch.where(mask_multi_gts, is_max_overlaps, mask_pos) # (b, n_max_boxes, h*w)
fg_mask = mask_pos.sum(-2)
# find each grid serve which gt(index)
# Find each grid serve which gt(index)
target_gt_idx = mask_pos.argmax(-2) # (b, h*w)
return target_gt_idx, fg_mask, mask_pos
@ -112,10 +112,10 @@ class TaskAlignedAssigner(nn.Module):
target_gt_idx, fg_mask, mask_pos = select_highest_overlaps(mask_pos, overlaps, self.n_max_boxes)
# assigned target
# Assigned target
target_labels, target_bboxes, target_scores = self.get_targets(gt_labels, gt_bboxes, target_gt_idx, fg_mask)
# normalize
# Normalize
align_metric *= mask_pos
pos_align_metrics = align_metric.amax(axis=-1, keepdim=True) # b, max_num_obj
pos_overlaps = (overlaps * mask_pos).amax(axis=-1, keepdim=True) # b, max_num_obj
@ -125,13 +125,13 @@ class TaskAlignedAssigner(nn.Module):
return target_labels, target_bboxes, target_scores, fg_mask.bool(), target_gt_idx
def get_pos_mask(self, pd_scores, pd_bboxes, gt_labels, gt_bboxes, anc_points, mask_gt):
# get in_gts mask, (b, max_num_obj, h*w)
"""Get in_gts mask, (b, max_num_obj, h*w)."""
mask_in_gts = select_candidates_in_gts(anc_points, gt_bboxes)
# get anchor_align metric, (b, max_num_obj, h*w)
# Get anchor_align metric, (b, max_num_obj, h*w)
align_metric, overlaps = self.get_box_metrics(pd_scores, pd_bboxes, gt_labels, gt_bboxes, mask_in_gts * mask_gt)
# get topk_metric mask, (b, max_num_obj, h*w)
# Get topk_metric mask, (b, max_num_obj, h*w)
mask_topk = self.select_topk_candidates(align_metric, topk_mask=mask_gt.repeat([1, 1, self.topk]).bool())
# merge all mask to a final mask, (b, max_num_obj, h*w)
# Merge all mask to a final mask, (b, max_num_obj, h*w)
mask_pos = mask_topk * mask_in_gts * mask_gt
return mask_pos, align_metric, overlaps
@ -145,7 +145,7 @@ class TaskAlignedAssigner(nn.Module):
ind = torch.zeros([2, self.bs, self.n_max_boxes], dtype=torch.long) # 2, b, max_num_obj
ind[0] = torch.arange(end=self.bs).view(-1, 1).repeat(1, self.n_max_boxes) # b, max_num_obj
ind[1] = gt_labels.long().squeeze(-1) # b, max_num_obj
# get the scores of each grid for each gt cls
# Get the scores of each grid for each gt cls
bbox_scores[mask_gt] = pd_scores[ind[0], :, ind[1]][mask_gt] # b, max_num_obj, h*w
# (b, max_num_obj, 1, 4), (b, 1, h*w, 4)