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I am training for only 1 class and got this error.
Epoch gpu_mem box obj cls total targets img_size 0% 0/11 [00:08<?, ?it/s] Traceback (most recent call last): File "/content/drive/MyDrive/PhD-OBJ-1/PyTorch_YOLOv4-master/train.py", line 537, in train(hyp, opt, device, tb_writer, wandb) File "/content/drive/MyDrive/PhD-OBJ-1/PyTorch_YOLOv4-master/train.py", line 287, in train pred = model(imgs) # forward File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1501, in _call_impl return forward_call(*args, **kwargs) File "/content/drive/MyDrive/PhD-OBJ-1/PyTorch_YOLOv4-master/models/models.py", line 465, in forward return self.forward_once(x) File "/content/drive/MyDrive/PhD-OBJ-1/PyTorch_YOLOv4-master/models/models.py", line 518, in forward_once yolo_out.append(module(x, out)) File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1501, in _call_impl return forward_call(*args, **kwargs) File "/content/drive/MyDrive/PhD-OBJ-1/PyTorch_YOLOv4-master/models/models.py", line 321, in forward p = p.view(bs, self.na, self.no, self.ny, self.nx).permute(0, 1, 3, 4, 2).contiguous() # prediction RuntimeError: shape '[2, 3, 9, 80, 80]' is invalid for input of size 230400
The text was updated successfully, but these errors were encountered:
check your .cfg & change filters [convolutional] size=1 stride=1 pad=1 filters=21 # (5+classes)*3 activation=linear
[yolo] mask = 6,7,8 anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401 classes=2 num=9 jitter=.3 ignore_thresh = .7 truth_thresh = 1 random=1 scale_x_y = 1.05 iou_thresh=0.213 cls_normalizer=1.0 iou_normalizer=0.07 iou_loss=ciou nms_kind=greedynms beta_nms=0.6
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I am training for only 1 class and got this error.
Epoch gpu_mem box obj cls total targets img_size
0% 0/11 [00:08<?, ?it/s]
Traceback (most recent call last):
File "/content/drive/MyDrive/PhD-OBJ-1/PyTorch_YOLOv4-master/train.py", line 537, in
train(hyp, opt, device, tb_writer, wandb)
File "/content/drive/MyDrive/PhD-OBJ-1/PyTorch_YOLOv4-master/train.py", line 287, in train
pred = model(imgs) # forward
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/content/drive/MyDrive/PhD-OBJ-1/PyTorch_YOLOv4-master/models/models.py", line 465, in forward
return self.forward_once(x)
File "/content/drive/MyDrive/PhD-OBJ-1/PyTorch_YOLOv4-master/models/models.py", line 518, in forward_once
yolo_out.append(module(x, out))
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/content/drive/MyDrive/PhD-OBJ-1/PyTorch_YOLOv4-master/models/models.py", line 321, in forward
p = p.view(bs, self.na, self.no, self.ny, self.nx).permute(0, 1, 3, 4, 2).contiguous() # prediction
RuntimeError: shape '[2, 3, 9, 80, 80]' is invalid for input of size 230400
The text was updated successfully, but these errors were encountered: