From 207c6fcff9a40c55773b382b3f8f51a656082bff Mon Sep 17 00:00:00 2001 From: Glenn Jocher Date: Thu, 2 Apr 2020 18:53:40 -0700 Subject: [PATCH] merge NMS full matrix --- utils/utils.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/utils/utils.py b/utils/utils.py index d434ccf4..e5a4c526 100755 --- a/utils/utils.py +++ b/utils/utils.py @@ -555,12 +555,12 @@ 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 if method == 'merge': # Merge NMS (boxes merged using weighted mean) i = torchvision.ops.boxes.nms(boxes, scores, iou_thres) - if n < 1E4: # update boxes + if n < 1E4: # update boxes as boxes(i,4) = weights(i,n) * boxes(n,4) # weights = (box_iou(boxes, boxes).tril_() > iou_thres) * scores.view(-1, 1) # box weights # weights /= weights.sum(0) # normalize # x[:, :4] = torch.mm(weights.T, x[:, :4]) weights = (box_iou(boxes[i], boxes) > iou_thres) * scores[None] # box weights - x[i, :4] = torch.mm(weights / weights.sum(1, keepdim=True), x[:, :4]) # boxes(i,4) = w(i,n) * boxes(n,4) + x[i, :4] = torch.mm(weights / weights.sum(1, keepdim=True), x[:, :4]).float() # merged boxes elif method == 'vision': i = torchvision.ops.boxes.nms(boxes, scores, iou_thres) elif method == 'fast': # FastNMS from https://github.com/dbolya/yolact