Merge NMS update
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@ -555,10 +555,10 @@ def non_max_suppression(prediction, conf_thres=0.1, iou_thres=0.6, multi_label=T
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boxes, scores = x[:, :4].clone() + c.view(-1, 1) * max_wh, x[:, 4] # boxes (offset by class), scores
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if method == 'merge': # Merge NMS (boxes merged using weighted mean)
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i = torchvision.ops.boxes.nms(boxes, scores, iou_thres)
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iou = box_iou(boxes, boxes[i]).tril_() # lower triangular iou matrix
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iou = box_iou(boxes, boxes).tril_() # lower triangular iou matrix
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weights = (iou > iou_thres) * scores.view(-1, 1)
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weights /= weights.sum(0) + 1E-6
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x[i, :4] = torch.mm(weights.T, x[:, :4]) # merged_boxes(n,4) = weights(n,n) * boxes(n,4)
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weights /= weights.sum(0)
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x[:, :4] = torch.mm(weights.T, x[:, :4]) # merged_boxes(n,4) = weights(n,n) * boxes(n,4)
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elif method == 'vision':
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i = torchvision.ops.boxes.nms(boxes, scores, iou_thres)
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elif method == 'fast': # FastNMS from https://github.com/dbolya/yolact
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