How to detect multiple objects using YOLOP? about yolop HOT 10 CLOSED

按照之前的步骤操作，可以训练，但是将要训练下一轮的时候出现如下错误： Epoch: [1][1340/1342] Time 396.972s (200.944s) Speed 0.0 samples/s Data 396.692s (200.649s) Loss 0.69399 (0.75016) 0%| | 0/146 [00:00<?, ?it/s]F:\Anaconda\envs\yoloair\lib\site-packages\torch\nn\functional.py:3060: UserWarning: Default upsampling behavior when mode=bilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details. warnings.warn("Default upsampling behavior when mode={} is changed " 0%| | 0/146 [00:01<?, ?it/s] Traceback (most recent call last): File "tools/train.py", line 395, in main() File "tools/train.py", line 330, in main da_segment_results,ll_segment_results,detect_results, total_loss,maps, times = validate( File "D:\YOLOP\YOLOP-main\lib\core\function.py", line 301, in validate label_det_pred = f'{names[int(cls)]} {conf:.2f}' KeyError: 35

search for nc = 1 change them to your class number

from yolop.

hello,I'm doing the same research.
Have you ever solved the problem?
please help me.

from yolop.

hello,I'm doing the same research. Have you ever solved the problem? please help me.

Try to modify the dict parameters in convert.py file, works for me, good luck, have fun : - )

from yolop.

Hello, what do you mean by “Try to modify the dict parameters in convert.py file”？
Can you tell us more about it？Thanks！

from yolop.

I set up ：
model.nc=41 in train.py,
single_cls = False in bdd.py，
id_dict = {'xx':0, 'xx': 1,…… 'xx': 40} in convert.py
but still I got the error said:
Traceback (most recent call last):
File "tools/train.py", line 395, in
main()
File "tools/train.py", line 323, in main
epoch, num_batch, num_warmup, writer_dict, logger, device, rank)
File "F:\yoloppp\YOLOP-main\lib\core\function.py", line 77, in train
total_loss, head_losses = criterion(outputs, target, shapes,model)
File "D:\anaconda\envs\yolop\lib\site-packages\torch\nn\modules\module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "F:\yoloppp\YOLOP-main\lib\core\loss.py", line 50, in forward
total_loss, head_losses = self._forward_impl(head_fields, head_targets, shapes, model)
File "F:\yoloppp\YOLOP-main\lib\core\loss.py", line 107, in _forward_impl
t[range(n), tcls[i]] = cp
IndexError: index 26 is out of bounds for dimension 1 with size 1

from yolop.

这个是因为YOLOP.py搭建网络里面nc默认设置成了1，需要改为我们自己的nc（例如41）

from yolop.

like this!

from yolop.

按照之前的步骤操作，可以训练，但是将要训练下一轮的时候出现如下错误：
Epoch: [1][1340/1342] Time 396.972s (200.944s) Speed 0.0 samples/s Data 396.692s (200.649s) Loss 0.69399 (0.75016)
0%| | 0/146 [00:00<?, ?it/s]F:\Anaconda\envs\yoloair\lib\site-packages\torch\nn\functional.py:3060: UserWarning: Default upsampling behavior when mode=bilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
warnings.warn("Default upsampling behavior when mode={} is changed "
0%| | 0/146 [00:01<?, ?it/s]
Traceback (most recent call last):
File "tools/train.py", line 395, in
main()
File "tools/train.py", line 330, in main
da_segment_results,ll_segment_results,detect_results, total_loss,maps, times = validate(
File "D:\YOLOP\YOLOP-main\lib\core\function.py", line 301, in validate
label_det_pred = f'{names[int(cls)]} {conf:.2f}'
KeyError: 35

from yolop.

could you tell me more detail about it plz？I have no idea on where I can find nc=1 except model.nc in train.py...

from yolop.

I created a fork and updated the code for BDD's 13 classes. Check it out here.

from yolop.