Fix2 `check_anchor_order()` in pixel-space not grid-space (#7067)
Follows https://github.com/ultralytics/yolov5/pull/7060 which provided only a partial solution to this issue. #7060 resolved occurences in yolo.py, this applies the same fix in autoanchor.py.
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@ -40,7 +40,8 @@ def check_anchors(dataset, model, thr=4.0, imgsz=640):
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bpr = (best > 1 / thr).float().mean() # best possible recall
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bpr = (best > 1 / thr).float().mean() # best possible recall
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return bpr, aat
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return bpr, aat
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anchors = m.anchors.clone() * m.stride.to(m.anchors.device).view(-1, 1, 1) # current anchors
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stride = m.stride.to(m.anchors.device).view(-1, 1, 1) # model strides
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anchors = m.anchors.clone() * stride # current anchors
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bpr, aat = metric(anchors.cpu().view(-1, 2))
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bpr, aat = metric(anchors.cpu().view(-1, 2))
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s = f'\n{PREFIX}{aat:.2f} anchors/target, {bpr:.3f} Best Possible Recall (BPR). '
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s = f'\n{PREFIX}{aat:.2f} anchors/target, {bpr:.3f} Best Possible Recall (BPR). '
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if bpr > 0.98: # threshold to recompute
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if bpr > 0.98: # threshold to recompute
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@ -55,8 +56,9 @@ def check_anchors(dataset, model, thr=4.0, imgsz=640):
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new_bpr = metric(anchors)[0]
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new_bpr = metric(anchors)[0]
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if new_bpr > bpr: # replace anchors
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if new_bpr > bpr: # replace anchors
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anchors = torch.tensor(anchors, device=m.anchors.device).type_as(m.anchors)
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anchors = torch.tensor(anchors, device=m.anchors.device).type_as(m.anchors)
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m.anchors[:] = anchors.clone().view_as(m.anchors) / m.stride.to(m.anchors.device).view(-1, 1, 1) # loss
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m.anchors[:] = anchors.clone().view_as(m.anchors)
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check_anchor_order(m)
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check_anchor_order(m) # must be in pixel-space (not grid-space)
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m.anchors /= stride
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s = f'{PREFIX}Done ✅ (optional: update model *.yaml to use these anchors in the future)'
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s = f'{PREFIX}Done ✅ (optional: update model *.yaml to use these anchors in the future)'
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else:
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else:
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s = f'{PREFIX}Done ⚠️ (original anchors better than new anchors, proceeding with original anchors)'
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s = f'{PREFIX}Done ⚠️ (original anchors better than new anchors, proceeding with original anchors)'
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