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Merge NMS update

This commit is contained in:
Glenn Jocher 2020-03-27 13:11:24 -07:00
parent 582de735ad
commit f9d34587da
1 changed files with 3 additions and 3 deletions
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6
utils/utils.py
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@ -555,10 +555,10 @@ def non_max_suppression(prediction, conf_thres=0.1, iou_thres=0.6, multi_label=T
boxes, scores = x[:, :4].clone() + c.view(-1, 1) * max_wh, x[:, 4] # boxes (offset by class), scores boxes, scores = x[:, :4].clone() + c.view(-1, 1) * max_wh, x[:, 4] # boxes (offset by class), scores
if method == 'merge': # Merge NMS (boxes merged using weighted mean) if method == 'merge': # Merge NMS (boxes merged using weighted mean)
i = torchvision.ops.boxes.nms(boxes, scores, iou_thres) i = torchvision.ops.boxes.nms(boxes, scores, iou_thres)
iou = box_iou(boxes, boxes[i]).tril_() # lower triangular iou matrix iou = box_iou(boxes, boxes).tril_() # lower triangular iou matrix
weights = (iou > iou_thres) * scores.view(-1, 1) weights = (iou > iou_thres) * scores.view(-1, 1)
weights /= weights.sum(0) + 1E-6 weights /= weights.sum(0)
x[i, :4] = torch.mm(weights.T, x[:, :4]) # merged_boxes(n,4) = weights(n,n) * boxes(n,4) x[:, :4] = torch.mm(weights.T, x[:, :4]) # merged_boxes(n,4) = weights(n,n) * boxes(n,4)
elif method == 'vision': elif method == 'vision':
i = torchvision.ops.boxes.nms(boxes, scores, iou_thres) i = torchvision.ops.boxes.nms(boxes, scores, iou_thres)
elif method == 'fast': # FastNMS from https://github.com/dbolya/yolact elif method == 'fast': # FastNMS from https://github.com/dbolya/yolact