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Should we control the pwh range for bbox regression from (0, 4) to (1/4, 4) ? #8265

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daikankan wants to merge 3 commits into from
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Should we control the pwh range for bbox regression from (0, 4) to (1/4, 4) ? #8265

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6050fd4
change pwh distribution.
Jun 20, 2022
ef703b9
Merge branch 'master' into master
glenn-jocher Jul 7, 2022
4666708
Merge branch 'master' into master
glenn-jocher Jul 12, 2022
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4 changes: 2 additions & 2 deletions models/yolo.py
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Original file line number Diff line number Diff line change
Expand Up @@ -65,11 +65,11 @@ def forward(self, x):
y = x[i].sigmoid()
if self.inplace:
y[..., 0:2] = (y[..., 0:2] * 2 + self.grid[i]) * self.stride[i] # xy
y[..., 2:4] = (y[..., 2:4] * 2) ** 2 * self.anchor_grid[i] # wh
y[..., 2:4] = torch.exp(y[..., 2:4] * 2.7724 - 1.3862) * self.anchor_grid[i] # wh
else: # for YOLOv5 on AWS Inferentia https://github.com/ultralytics/yolov5/pull/2953
xy, wh, conf = y.split((2, 2, self.nc + 1), 4) # y.tensor_split((2, 4, 5), 4) # torch 1.8.0
xy = (xy * 2 + self.grid[i]) * self.stride[i] # xy
wh = (wh * 2) ** 2 * self.anchor_grid[i] # wh
wh = torch.exp(wh * 2.7724 - 1.3862) * self.anchor_grid[i] # wh
y = torch.cat((xy, wh, conf), 4)
z.append(y.view(bs, -1, self.no))

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2 changes: 1 addition & 1 deletion utils/loss.py
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Expand Up @@ -136,7 +136,7 @@ def __call__(self, p, targets): # predictions, targets

# Regression
pxy = pxy.sigmoid() * 2 - 0.5
pwh = (pwh.sigmoid() * 2) ** 2 * anchors[i]
pwh = torch.exp(pwh.sigmoid() * 2.7724 - 1.3862) * anchors[i]
pbox = torch.cat((pxy, pwh), 1) # predicted box
iou = bbox_iou(pbox, tbox[i], CIoU=True).squeeze() # iou(prediction, target)
lbox += (1.0 - iou).mean() # iou loss
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