Description
Describe the bug
When running inference.py --data-dir data --class-map class_map.txt --model efficientnet_b7 --num-classes 8 --checkpoint output/model_best.pth.tar where data is a directory that contains images and no subfolders, the script crashes with the following output:
Traceback (most recent call last):
File "/home/josua/redacted/pytorch-image-models/inference.py", line 369, in <module>
main()
File "/home/josua/redacted/pytorch-image-models/inference.py", line 224, in main
dataset = create_dataset(
^^^^^^^^^^^^^^^
File "/home/josua/redacted/pytorch-image-models/timm/data/dataset_factory.py", line 216, in create_dataset
ds = ImageDataset(
^^^^^^^^^^^^^
File "/home/josua/redacted/pytorch-image-models/timm/data/dataset.py", line 36, in __init__
reader = create_reader(
^^^^^^^^^^^^^^
File "/home/josua/redacted/pytorch-image-models/timm/data/readers/reader_factory.py", line 44, in create_reader
reader = ReaderImageFolder(root, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/josua/redacted/pytorch-image-models/timm/data/readers/reader_image_folder.py", line 82, in __init__
raise RuntimeError(
RuntimeError: Found 0 images in subfolders of /home/josua/redacted/data/unlabeled. Supported image extensions are .png, .jpg, .jpeg
Expected behavior
Instead of raising an error, I expect it to perform the inference on the (recursive) contents of data irrespective of the existence of labeled subfolders because labels are not necessary for inference.
Desktop (please complete the following information):
- OS: x86_64 Linux 6.11.5-arch1-1
- This repository version: d4dde48
- PyTorch version w/ CUDA/cuDNN: python-pytorch-cuda 2.3.1-8, cuda 12.6.2-2
Additional context
Workaround: It works when, instead of placing the images in data/ directly, one places them in data/random_label/ where random_label is a random label, i.e. a random line from class_map.txt