ultralytics 8.0.197 save P, R, F1 curves to metrics (#5354)
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: erminkev1 <83356055+erminkev1@users.noreply.github.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Andy <39454881+yermandy@users.noreply.github.com>
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33 changed files with 337 additions and 195 deletions
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@ -188,7 +188,7 @@ def get_cdn_group(batch,
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num_group = num_dn // max_nums
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num_group = 1 if num_group == 0 else num_group
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# pad gt to max_num of a batch
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# Pad gt to max_num of a batch
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bs = len(gt_groups)
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gt_cls = batch['cls'] # (bs*num, )
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gt_bbox = batch['bboxes'] # bs*num, 4
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@ -204,10 +204,10 @@ def get_cdn_group(batch,
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neg_idx = torch.arange(total_num * num_group, dtype=torch.long, device=gt_bbox.device) + num_group * total_num
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if cls_noise_ratio > 0:
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# half of bbox prob
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# Half of bbox prob
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mask = torch.rand(dn_cls.shape) < (cls_noise_ratio * 0.5)
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idx = torch.nonzero(mask).squeeze(-1)
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# randomly put a new one here
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# Randomly put a new one here
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new_label = torch.randint_like(idx, 0, num_classes, dtype=dn_cls.dtype, device=dn_cls.device)
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dn_cls[idx] = new_label
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@ -240,9 +240,9 @@ def get_cdn_group(batch,
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tgt_size = num_dn + num_queries
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attn_mask = torch.zeros([tgt_size, tgt_size], dtype=torch.bool)
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# match query cannot see the reconstruct
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# Match query cannot see the reconstruct
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attn_mask[num_dn:, :num_dn] = True
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# reconstruct cannot see each other
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# Reconstruct cannot see each other
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for i in range(num_group):
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if i == 0:
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attn_mask[max_nums * 2 * i:max_nums * 2 * (i + 1), max_nums * 2 * (i + 1):num_dn] = True
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