I use Ade20K dataset to train model. This error occurred.
Original Traceback (most recent call last):
File "/home/docker/.local/lib/python2.7/site-packages/torch/utils/data/_utils/worker.py", line 178, in _worker_loop
data = fetcher.fetch(index)
File "/home/docker/.local/lib/python2.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/docker/catkin_ws/src/semantic_slam/semantic_cloud/include/ptsemseg/loader/ade20k_loader.py", line 43, in getitem
img, lbl = self.augmentations(img, lbl)
File "/home/docker/catkin_ws/src/semantic_slam/semantic_cloud/include/ptsemseg/augmentations.py", line 16, in call
img, mask = Image.fromarray(img, mode='RGB'), Image.fromarray(mask, mode='L')
File "/home/docker/.local/lib/python2.7/site-packages/PIL/Image.py", line 2657, in fromarray
raise ValueError("Too many dimensions: %d > %d." % (ndim, ndmax))
ValueError: Too many dimensions: 3 > 2.
Dylanhj
commented
3 years ago
I use Ade20K dataset to train model. This error occurred. Original Traceback (most recent call last): File "/home/docker/.local/lib/python2.7/site-packages/torch/utils/data/_utils/worker.py", line 178, in _worker_loop data = fetcher.fetch(index) File "/home/docker/.local/lib/python2.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch data = [self.dataset[idx] for idx in possibly_batched_index] File "/home/docker/catkin_ws/src/semantic_slam/semantic_cloud/include/ptsemseg/loader/ade20k_loader.py", line 43, in getitem img, lbl = self.augmentations(img, lbl) File "/home/docker/catkin_ws/src/semantic_slam/semantic_cloud/include/ptsemseg/augmentations.py", line 16, in call img, mask = Image.fromarray(img, mode='RGB'), Image.fromarray(mask, mode='L') File "/home/docker/.local/lib/python2.7/site-packages/PIL/Image.py", line 2657, in fromarray raise ValueError("Too many dimensions: %d > %d." % (ndim, ndmax)) ValueError: Too many dimensions: 3 > 2.