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@ -195,7 +195,7 @@ class YOLOLayer(nn.Module):
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ny = img_size[0] // stride # number y grid points
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create_grids(self, img_size, (nx, ny))
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def forward(self, p, img_size, var=None):
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def forward(self, p, img_size):
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if ONNX_EXPORT:
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bs = 1 # batch size
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else:
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@ -261,10 +261,9 @@ class Darknet(nn.Module):
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self.version = np.array([0, 2, 5], dtype=np.int32) # (int32) version info: major, minor, revision
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self.seen = np.array([0], dtype=np.int64) # (int64) number of images seen during training
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def forward(self, x, var=None):
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def forward(self, x, verbose=False):
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img_size = x.shape[-2:]
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yolo_out, out = [], []
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verbose = False
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if verbose:
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str = ''
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print('0', x.shape)
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