[Feature request] Support for ImageNet format annotations

[amirmk89]

Will be added in an upcoming release, shared here to help unblock users and collect feedback.

ImageNet image annotation format

The ImageNet format uses the directory structure for dividing images into splits and classes. Class names are coded such that n02979186 is 'cassette player', etc.
General structure is:

• data:
  • train
    • n02979186
    • n03417042
    • ...
  • val
    • n02979186
    • n03417042
    • ...

E.g., train set cassete player images would be:

• data/train/n02979186/1.jpg
• data/train/n02979186/2.jpg

This snippet assumes that the data directory is provided as root and parses class codes and splits. Converting class codes to class names is not covered here, the full list can be found here

Parsing snippet

Assumes relative paths follow the data/train/n02979186/1.jpg format, meaning full path is /path/to/imagenet/data/train/n02979186/1.jpg.

import fastdup
import pandas as pd
from pathlib import Path

data_root = '/path/to/imagenet'
img_list = list(Path(data_root).rglob('*.JPEG'))

df = pd.DataFrame({'img_filename': [str(o.relative_to(data_root)) for o in img_list]})
df['split'] = df.img_filename.apply(lambda x: x.split('/')[0])
df['label'] = df.img_filename.apply(lambda x: x.split('/')[1])

# Run fastdup
fd = fastdup.create(work_dir, data_root)
fd.run(annotations=df)

Please let us know if you see any issues or want to request additional features.