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@@ -1448,11 +1448,23 @@ class RoIHeads(nn.Module):
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if feature_logits is not None:
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circles_probs, circles_scores = circle_inference(feature_logits, circle_proposals)
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- for keypoint_prob, kps, r,f in zip(circles_probs, circles_scores, result,feature_logits):
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+ # print(f'circles_probs:{circles_probs.shape}, circles_scores:{circles_scores.shape}')
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+ proposals_per_image = [box.size(0) for box in circle_proposals]
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+ print(f'circle_proposals_per_image:{proposals_per_image}')
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+ feature_logits_props=[]
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+ start_idx = 0
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+ for num_p in proposals_per_image:
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+ current_features = feature_logits[start_idx:start_idx + num_p]
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+ merged_feature = torch.sum(current_features, dim=0, keepdim=True)
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+ feature_logits_props.append(merged_feature)
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+
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+
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+
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+ for keypoint_prob, kps, r,f in zip(circles_probs, circles_scores, result,feature_logits_props):
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r["circles"] = keypoint_prob
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r["circles_scores"] = kps
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print(f'circles feature map:{f.shape}')
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- r["features"] = f
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+ r["features"] = f.squeeze(0)
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print(f'loss_circle:{loss_circle}')
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print(f'loss_circle_extra:{loss_circle_extra}')
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