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I want to train the data, but when I run python train.py cfg/ape.data cfg/yolo-pose.cfg backup/ape/init.weights, it get wrong as follows:
Dose anyone got the same errors?
layer filters size input output
0 conv 32 3 x 3 / 1 416 x 416 x 3 -> 416 x 416 x 32
1 max 2 x 2 / 2 416 x 416 x 32 -> 208 x 208 x 32
2 conv 64 3 x 3 / 1 208 x 208 x 32 -> 208 x 208 x 64
3 max 2 x 2 / 2 208 x 208 x 64 -> 104 x 104 x 64
4 conv 128 3 x 3 / 1 104 x 104 x 64 -> 104 x 104 x 128
5 conv 64 1 x 1 / 1 104 x 104 x 128 -> 104 x 104 x 64
6 conv 128 3 x 3 / 1 104 x 104 x 64 -> 104 x 104 x 128
7 max 2 x 2 / 2 104 x 104 x 128 -> 52 x 52 x 128
8 conv 256 3 x 3 / 1 52 x 52 x 128 -> 52 x 52 x 256
9 conv 128 1 x 1 / 1 52 x 52 x 256 -> 52 x 52 x 128
10 conv 256 3 x 3 / 1 52 x 52 x 128 -> 52 x 52 x 256
11 max 2 x 2 / 2 52 x 52 x 256 -> 26 x 26 x 256
12 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512
13 conv 256 1 x 1 / 1 26 x 26 x 512 -> 26 x 26 x 256
14 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512
15 conv 256 1 x 1 / 1 26 x 26 x 512 -> 26 x 26 x 256
16 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512
17 max 2 x 2 / 2 26 x 26 x 512 -> 13 x 13 x 512
18 conv 1024 3 x 3 / 1 13 x 13 x 512 -> 13 x 13 x1024
19 conv 512 1 x 1 / 1 13 x 13 x1024 -> 13 x 13 x 512
20 conv 1024 3 x 3 / 1 13 x 13 x 512 -> 13 x 13 x1024
21 conv 512 1 x 1 / 1 13 x 13 x1024 -> 13 x 13 x 512
22 conv 1024 3 x 3 / 1 13 x 13 x 512 -> 13 x 13 x1024
23 conv 1024 3 x 3 / 1 13 x 13 x1024 -> 13 x 13 x1024
24 conv 1024 3 x 3 / 1 13 x 13 x1024 -> 13 x 13 x1024
25 route 16
26 conv 64 1 x 1 / 1 26 x 26 x 512 -> 26 x 26 x 64
27 reorg / 2 26 x 26 x 64 -> 13 x 13 x 256
28 route 27 24
29 conv 1024 3 x 3 / 1 13 x 13 x1280 -> 13 x 13 x1024
30 conv 20 1 x 1 / 1 13 x 13 x1024 -> 13 x 13 x 20
31 detection
2018-09-11 13:56:55 epoch 0, processed 0 samples, lr 0.000100
/home/yong/anaconda2/lib/python2.7/site-packages/torch/nn/functional.py:1006: UserWarning: nn.functional.sigmoid is deprecated. Use torch.sigmoid instead.
warnings.warn("nn.functional.sigmoid is deprecated. Use torch.sigmoid instead.")
Traceback (most recent call last):
File "train.py", line 401, in
niter = train(epoch)
File "train.py", line 96, in train
loss = region_loss(output, target)
File "/home/yong/anaconda2/lib/python2.7/site-packages/torch/nn/modules/module.py", line 477, in call
result = self.forward(*input, **kwargs)
File "/home/yong/paperWorkspace/01.singleshotpose/singleshotpose-master/region_loss.py", line 205, in forward
pred_corners[0] = (x0.data + grid_x) / nW
RuntimeError: The size of tensor a (13) must match the size of tensor b (5070) at non-singleton dimension 3
I want to train the data, but when I run
python train.py cfg/ape.data cfg/yolo-pose.cfg backup/ape/init.weights, it get wrong as follows:Dose anyone got the same errors?
layer filters size input output
0 conv 32 3 x 3 / 1 416 x 416 x 3 -> 416 x 416 x 32
1 max 2 x 2 / 2 416 x 416 x 32 -> 208 x 208 x 32
2 conv 64 3 x 3 / 1 208 x 208 x 32 -> 208 x 208 x 64
3 max 2 x 2 / 2 208 x 208 x 64 -> 104 x 104 x 64
4 conv 128 3 x 3 / 1 104 x 104 x 64 -> 104 x 104 x 128
5 conv 64 1 x 1 / 1 104 x 104 x 128 -> 104 x 104 x 64
6 conv 128 3 x 3 / 1 104 x 104 x 64 -> 104 x 104 x 128
7 max 2 x 2 / 2 104 x 104 x 128 -> 52 x 52 x 128
8 conv 256 3 x 3 / 1 52 x 52 x 128 -> 52 x 52 x 256
9 conv 128 1 x 1 / 1 52 x 52 x 256 -> 52 x 52 x 128
10 conv 256 3 x 3 / 1 52 x 52 x 128 -> 52 x 52 x 256
11 max 2 x 2 / 2 52 x 52 x 256 -> 26 x 26 x 256
12 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512
13 conv 256 1 x 1 / 1 26 x 26 x 512 -> 26 x 26 x 256
14 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512
15 conv 256 1 x 1 / 1 26 x 26 x 512 -> 26 x 26 x 256
16 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512
17 max 2 x 2 / 2 26 x 26 x 512 -> 13 x 13 x 512
18 conv 1024 3 x 3 / 1 13 x 13 x 512 -> 13 x 13 x1024
19 conv 512 1 x 1 / 1 13 x 13 x1024 -> 13 x 13 x 512
20 conv 1024 3 x 3 / 1 13 x 13 x 512 -> 13 x 13 x1024
21 conv 512 1 x 1 / 1 13 x 13 x1024 -> 13 x 13 x 512
22 conv 1024 3 x 3 / 1 13 x 13 x 512 -> 13 x 13 x1024
23 conv 1024 3 x 3 / 1 13 x 13 x1024 -> 13 x 13 x1024
24 conv 1024 3 x 3 / 1 13 x 13 x1024 -> 13 x 13 x1024
25 route 16
26 conv 64 1 x 1 / 1 26 x 26 x 512 -> 26 x 26 x 64
27 reorg / 2 26 x 26 x 64 -> 13 x 13 x 256
28 route 27 24
29 conv 1024 3 x 3 / 1 13 x 13 x1280 -> 13 x 13 x1024
30 conv 20 1 x 1 / 1 13 x 13 x1024 -> 13 x 13 x 20
31 detection
2018-09-11 13:56:55 epoch 0, processed 0 samples, lr 0.000100
/home/yong/anaconda2/lib/python2.7/site-packages/torch/nn/functional.py:1006: UserWarning: nn.functional.sigmoid is deprecated. Use torch.sigmoid instead.
warnings.warn("nn.functional.sigmoid is deprecated. Use torch.sigmoid instead.")
Traceback (most recent call last):
File "train.py", line 401, in
niter = train(epoch)
File "train.py", line 96, in train
loss = region_loss(output, target)
File "/home/yong/anaconda2/lib/python2.7/site-packages/torch/nn/modules/module.py", line 477, in call
result = self.forward(*input, **kwargs)
File "/home/yong/paperWorkspace/01.singleshotpose/singleshotpose-master/region_loss.py", line 205, in forward
pred_corners[0] = (x0.data + grid_x) / nW
RuntimeError: The size of tensor a (13) must match the size of tensor b (5070) at non-singleton dimension 3