Tried to load training data with pytorch torch.datasets.ImageFolder in Colab.
transform = transforms.Compose([transforms.Resize(400),
transforms.ToTensor()])
dataset_path = 'ss/'
dataset = datasets.ImageFolder(root=dataset_path, transform=transform)
dataloader = torch.utils.data.DataLoader(dataset, batch_size=20)
I encountered the following error :
---------------------------------------------------------------------------
FileNotFoundError Traceback (most recent call last)
<ipython-input-27-7abcc1f434b1> in <module>()
2 transforms.ToTensor()])
3 dataset_path = 'ss/'
----> 4 dataset = datasets.ImageFolder(root=dataset_path, transform=transform)
5 dataloader = torch.utils.data.DataLoader(dataset, batch_size=20)
3 frames
/usr/local/lib/python3.7/dist-packages/torchvision/datasets/folder.py in make_dataset(directory, class_to_idx, extensions, is_valid_file)
100 if extensions is not None:
101 msg += f"Supported extensions are: {', '.join(extensions)}"
--> 102 raise FileNotFoundError(msg)
103
104 return instances
FileNotFoundError: Found no valid file for the classes .ipynb_checkpoints. Supported extensions are: .jpg, .jpeg, .png, .ppm, .bmp, .pgm, .tif, .tiff, .webp
My Dataset folder contains a subfolder with many training images in png format, still the ImageFolder can't access them.
I encountered the same problem when I was using IPython notebook-like tools.
First please check if there is any hidden files under your dataset_path. Use ls -a if you are under a Linux environment.
The case happen to me is I found a hidden file called .ipynb_checkpoints which is located parallelly to image class subfolders. I think that file causes confusion to PyTorch dataset. I made sure it is not useful so I simply deleted it. Then the dataset works fine.
Or if you would like to simply ignore that file, you may also try this.