The Labeled Faces in the Wild (LFW) format is primarily used for face verification and face recognition tasks. The LFW format is designed to be straightforward and is compatible with a variety of machine learning and deep learning frameworks.

For more information, see:

Export LFW annotation

For export of images:

  • Supported annotations: Tags, Skeletons.

  • Attributes:

    • negative_pairs (should be defined for labels as text): list of image names with mismatched persons.
    • positive_pairs (should be defined for labels as text): list of image names with matched persons.
  • Tracks: Not supported.

The downloaded file is a .zip archive with the following structure:

    └── images/ # if the option save images was selected
    │    ├── name1/
    │    │   ├── name1_0001.jpg
    │    │   ├── name1_0002.jpg
    │    │   ├── ...
    │    ├── name2/
    │    │   ├── name2_0001.jpg
    │    │   ├── name2_0002.jpg
    │    │   ├── ...
    │    ├── ...
    ├── landmarks.txt
    ├── pairs.txt
    └── people.txt

Import LFW annotation

The uploaded annotations file should be a zip file with the following structure:

    └── annotations/
        ├── landmarks.txt # list with landmark points for each image
        ├── pairs.txt # list of matched and mismatched pairs of person
        └── people.txt # optional file with a list of persons name

Full information about the content of annotation files is available here

Example: create task with images and upload LFW annotations into it

This is one of the possible ways to create a task and add LFW annotations for it.

  • On the task creation page:
    • Add labels that correspond to the names of the persons.
    • For each label define text attributes with names positive_pairs and negative_pairs
    • Add images using zip archive from local repository:
    ├── name1_0001.jpg
    ├── name1_0002.jpg
    ├── ...
    ├── name1_<N>.jpg
    ├── name2_0001.jpg
    ├── ...
  • On the annotation page: Upload annotation -> LFW 1.0 -> choose archive with structure that described in the import section.