VoTT JSON#

Format specification#

VoTT (Visual Object Tagging Tool) is an open source annotation tool released by Microsoft. VoTT JSON is the format used by VoTT when the user exports a project and selects “VoTT JSON” as the export format.

Supported annotation types:

  • Bbox

Import VoTT dataset#

A Datumaro project with a VoTT JSON source can be created in the following way:

datum project create
datum project import --format vott_json <path/to/dataset>

It is also possible to import the dataset using Python API:

import datumaro as dm

vott_json_dataset = dm.Dataset.import_from('<path/to/dataset>', 'vott_json')

VoTT JSON dataset directory should have the following structure:

dataset/
├── dataset_meta.json # a list of custom labels (optional)
├── img0001.jpg
├── img0002.jpg
├── img0003.jpg
├── img0004.jpg
├── ...
├── test-export.json
├── train-export.json
└── ...

To add custom classes, you can use dataset_meta.json.

Export to other formats#

Datumaro can convert a VoTT JSON dataset into any other format Datumaro supports. To get the expected result, convert the dataset to a format that supports bounding boxes.

There are several ways to convert a VoTT JSON dataset to other dataset formats using CLI:

datum project create
datum project import -f vott_json <path/to/dataset>
datum project export -f voc -o ./save_dir -- --save-media

or

datum convert -if vott_json -i <path/to/dataset> \
    -f voc -o <output/dir> -- --save-media

Or, using Python API:

import datumaro as dm

dataset = dm.Dataset.import_from('<path/to/dataset>', 'vott_json')
dataset.export('save_dir', 'voc')

Examples#

Examples of using this format from the code can be found in VoTT JSON tests.