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Simplify Darknet() class: forward pass yolo case #48

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Simplify Darknet() class: forward pass yolo case #48

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16 changes: 2 additions & 14 deletions darknet.py
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Original file line number Diff line number Diff line change
Expand Up @@ -305,12 +305,10 @@ def get_module_list(self):


def forward(self, x, CUDA):
detections = []
modules = self.blocks[1:]
outputs = {} #We cache the outputs for the route layer
detections = torch.empty(0) # concatenate all bbox predictions to this initially empty tensor


write = 0
for i in range(len(modules)):

module_type = (modules[i]["type"])
Expand Down Expand Up @@ -364,17 +362,7 @@ def forward(self, x, CUDA):
if type(x) == int:
continue


if not write:
detections = x
write = 1

else:
detections = torch.cat((detections, x), 1)

outputs[i] = outputs[i-1]


detections = torch.cat((detections, x), dim=1)

try:
return detections
Expand Down