merge_batch NMS method
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@ -561,7 +561,7 @@ def non_max_suppression(prediction, conf_thres=0.1, iou_thres=0.6, multi_label=T
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elif method == 'merge_batch': # Merge NMS
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elif method == 'merge_batch': # Merge NMS
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i = torchvision.ops.boxes.nms(boxes, scores, iou_thres)
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i = torchvision.ops.boxes.nms(boxes, scores, iou_thres)
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iou = box_iou(boxes, boxes[i]).tril_() # upper triangular iou matrix
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iou = box_iou(boxes, boxes[i]).tril_() # upper triangular iou matrix
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weights = (iou > conf_thres) * scores.view(-1, 1)
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weights = (iou > iou_thres) * scores.view(-1, 1)
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weights /= weights.sum(0)
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weights /= weights.sum(0)
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pred[i, :4] = torch.matmul(weights.T, pred[:, :4]) # merged_boxes(n,4) = weights(n,n) * boxes(n,4)
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pred[i, :4] = torch.matmul(weights.T, pred[:, :4]) # merged_boxes(n,4) = weights(n,n) * boxes(n,4)
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elif method == 'fast_batch': # FastNMS from https://github.com/dbolya/yolact
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elif method == 'fast_batch': # FastNMS from https://github.com/dbolya/yolact
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