# FreeLabel: A Publicly Available Annotation Tool based on Freehand Traces

## TL;DR

FreeLabel is an open-source annotation tool that enables quick, high-quality image segmentation using minimal freehand scribbles, significantly reducing annotation time and effort for large datasets.

## Contribution

It introduces a user-friendly web interface for efficient segmentation annotation with minimal input, adaptable to various datasets and annotation needs.

## Key findings

- Demonstrated high-quality segmentation results on PASCAL dataset
- Validated effectiveness on agricultural domain dataset
- Reduced annotation time with minimal user input

## Abstract

Large-scale annotation of image segmentation datasets is often prohibitively expensive, as it usually requires a huge number of worker hours to obtain high-quality results. Abundant and reliable data has been, however, crucial for the advances on image understanding tasks achieved by deep learning models. In this paper, we introduce FreeLabel, an intuitive open-source web interface that allows users to obtain high-quality segmentation masks with just a few freehand scribbles, in a matter of seconds. The efficacy of FreeLabel is quantitatively demonstrated by experimental results on the PASCAL dataset as well as on a dataset from the agricultural domain. Designed to benefit the computer vision community, FreeLabel can be used for both crowdsourced or private annotation and has a modular structure that can be easily adapted for any image dataset.