VoTT CSV

Format specification

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

Supported annotation types:

• Bbox

Import VoTT dataset

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

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

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

import datumaro as dm

vott_csv_dataset = dm.Dataset.import_from('<path/to/dataset>', 'vott_csv')

VoTT CSV 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.csv
├── train-export.csv
└── ...

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

Export to other formats

Datumaro can convert a VoTT CSV 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 CSV dataset to other dataset formats using CLI:

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

or

datum convert -if vott_csv -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_csv')
dataset.export('save_dir', 'voc')

Examples

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