meetps/pytorch-semseg

The following problem occurs when loading the sunrgbd dataset

18022443868 opened this issue · 0 comments

INFO:ptsemseg:Iter [260/300000] Loss: 2.5116 Time/Image: 0.2828 lr=0.000020
[ 0 4 5 7 9 10 12]
[ 0 4 5 7 9 10 12]
[ 0 5 7 10 12]
[ 0 5 7 10 12]
[ 0 4 5 7 12 13]
[ 0 4 5 7 12 13]
[ 0 4 5 7 8 12 13]
[ 0 4 5 8 12 13]
[ 0 4 5 7 10 12]
[ 0 4 5 7 10 12]
Traceback (most recent call last):
File "C:\Program Files\JetBrains\PyCharm 2019.1.2\helpers\pydev\pydevd.py", line 1758, in
main()
File "C:\Program Files\JetBrains\PyCharm 2019.1.2\helpers\pydev\pydevd.py", line 1752, in main
globals = debugger.run(setup['file'], None, None, is_module)
File "C:\Program Files\JetBrains\PyCharm 2019.1.2\helpers\pydev\pydevd.py", line 1147, in run
pydev_imports.execfile(file, globals, locals) # execute the script
File "C:\Program Files\JetBrains\PyCharm 2019.1.2\helpers\pydev_pydev_imps_pydev_execfile.py", line 18, in execfile
exec(compile(contents+"\n", file, 'exec'), glob, loc)
File "E:/vSLAM/FCHarDNet-master/train.py", line 292, in
train(cfg, writer, logger)
File "E:/vSLAM/FCHarDNet-master/train.py", line 141, in train
for (images, labels) in trainloader:
File "D:\Anancaonda4\envs\pytorch\lib\site-packages\torch\utils\data\dataloader.py", line 637, in next
return self._process_next_batch(batch)
File "D:\Anancaonda4\envs\pytorch\lib\site-packages\torch\utils\data\dataloader.py", line 658, in _process_next_batch
raise batch.exc_type(batch.exc_msg)
AssertionError: Traceback (most recent call last):
File "D:\Anancaonda4\envs\pytorch\lib\site-packages\torch\utils\data\dataloader.py", line 138, in _worker_loop
samples = collate_fn([dataset[i] for i in batch_indices])
File "D:\Anancaonda4\envs\pytorch\lib\site-packages\torch\utils\data\dataloader.py", line 138, in
samples = collate_fn([dataset[i] for i in batch_indices])
File "E:\vSLAM\FCHarDNet-master\ptsemseg\loader\sunrgbd_loader.py", line 82, in getitem
img1, lbl1 = self.transform(img, lbl)
File "E:\vSLAM\FCHarDNet-master\ptsemseg\loader\sunrgbd_loader.py", line 109, in transform
assert np.all(classes == np.unique(lbl))
AssertionError

The above opencv scaling results in reduced categories