Object detection is all about bounding boxes. The IAdet tool enables users to teach the computer how to draw bounding boxes around a particular class of objects present in some images. As you annotate, a model is trained on the background and is used to provide predictions.
- Clone the repo
- With Python 3.10 run:
python -m venv env_iadet
source env_iadet/bin/activate
bash install.sh # installing mmcv might take a long time
bash launch.sh DATA_DIR
If you find this project useful, cite our work:
@inproceedings{marchesoni2022iadet,
title={IAdet: Human in the loop object detection},
author={Marchesoni-Acland, Facciolo},
booktitle={NeurIPS 2022 Workshop on Human in the Loop Learning},
year={2022}
}
or check out the paper's code here: https://github.com/franchesoni/iadet_paper
- Include semi-supervised learning https://mmdetection.readthedocs.io/en/v3.0.0rc0/user_guides/semi_det.html#configure-meanteacherhook
- Make GUI show the images in the center of the region (resize accroding to max width max depth)