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update https://github.com/WongKinYiu/yolov7/issues/272
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Kin-Yiu, Wong 2022-08-04 20:20:51 +08:00 committed by GitHub
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commit 72a9c9628a
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1 changed files with 5 additions and 5 deletions
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10
models/yolo.py
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@ -522,16 +522,16 @@ class Model(nn.Module):
if isinstance(m, Detect): if isinstance(m, Detect):
s = 256 # 2x min stride s = 256 # 2x min stride
m.stride = torch.tensor([s / x.shape[-2] for x in self.forward(torch.zeros(1, ch, s, s))]) # forward m.stride = torch.tensor([s / x.shape[-2] for x in self.forward(torch.zeros(1, ch, s, s))]) # forward
m.anchors /= m.stride.view(-1, 1, 1)
check_anchor_order(m) check_anchor_order(m)
m.anchors /= m.stride.view(-1, 1, 1)
self.stride = m.stride self.stride = m.stride
self._initialize_biases() # only run once self._initialize_biases() # only run once
# print('Strides: %s' % m.stride.tolist()) # print('Strides: %s' % m.stride.tolist())
if isinstance(m, IDetect): if isinstance(m, IDetect):
s = 256 # 2x min stride s = 256 # 2x min stride
m.stride = torch.tensor([s / x.shape[-2] for x in self.forward(torch.zeros(1, ch, s, s))]) # forward m.stride = torch.tensor([s / x.shape[-2] for x in self.forward(torch.zeros(1, ch, s, s))]) # forward
m.anchors /= m.stride.view(-1, 1, 1)
check_anchor_order(m) check_anchor_order(m)
m.anchors /= m.stride.view(-1, 1, 1)
self.stride = m.stride self.stride = m.stride
self._initialize_biases() # only run once self._initialize_biases() # only run once
# print('Strides: %s' % m.stride.tolist()) # print('Strides: %s' % m.stride.tolist())
@ -539,24 +539,24 @@ class Model(nn.Module):
s = 256 # 2x min stride s = 256 # 2x min stride
m.stride = torch.tensor([s / x.shape[-2] for x in self.forward(torch.zeros(1, ch, s, s))[:4]]) # forward m.stride = torch.tensor([s / x.shape[-2] for x in self.forward(torch.zeros(1, ch, s, s))[:4]]) # forward
#print(m.stride) #print(m.stride)
m.anchors /= m.stride.view(-1, 1, 1)
check_anchor_order(m) check_anchor_order(m)
m.anchors /= m.stride.view(-1, 1, 1)
self.stride = m.stride self.stride = m.stride
self._initialize_aux_biases() # only run once self._initialize_aux_biases() # only run once
# print('Strides: %s' % m.stride.tolist()) # print('Strides: %s' % m.stride.tolist())
if isinstance(m, IBin): if isinstance(m, IBin):
s = 256 # 2x min stride s = 256 # 2x min stride
m.stride = torch.tensor([s / x.shape[-2] for x in self.forward(torch.zeros(1, ch, s, s))]) # forward m.stride = torch.tensor([s / x.shape[-2] for x in self.forward(torch.zeros(1, ch, s, s))]) # forward
m.anchors /= m.stride.view(-1, 1, 1)
check_anchor_order(m) check_anchor_order(m)
m.anchors /= m.stride.view(-1, 1, 1)
self.stride = m.stride self.stride = m.stride
self._initialize_biases_bin() # only run once self._initialize_biases_bin() # only run once
# print('Strides: %s' % m.stride.tolist()) # print('Strides: %s' % m.stride.tolist())
if isinstance(m, IKeypoint): if isinstance(m, IKeypoint):
s = 256 # 2x min stride s = 256 # 2x min stride
m.stride = torch.tensor([s / x.shape[-2] for x in self.forward(torch.zeros(1, ch, s, s))]) # forward m.stride = torch.tensor([s / x.shape[-2] for x in self.forward(torch.zeros(1, ch, s, s))]) # forward
m.anchors /= m.stride.view(-1, 1, 1)
check_anchor_order(m) check_anchor_order(m)
m.anchors /= m.stride.view(-1, 1, 1)
self.stride = m.stride self.stride = m.stride
self._initialize_biases_kpt() # only run once self._initialize_biases_kpt() # only run once
# print('Strides: %s' % m.stride.tolist()) # print('Strides: %s' % m.stride.tolist())