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TACO: Trash Annotations in Context Dataset Computer Vision Project
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TACO: Trash Annotations in Context Dataset
From: Pedro F. Proença; Pedro Simões
- For more information, go to: http://tacodataset.org
- https://github.com/pedropro/TACO
TACO is a growing image dataset of trash in the wild. It contains segmented images of litter taken under diverse environments: woods, roads and beaches. These images are manually labeled according to an hierarchical taxonomy to train and evaluate object detection algorithms. Annotations are provided in a similar format to COCO dataset.
The model in action:
Examples images from the dataset:
For more details and to cite the authors:
- Paper: https://arxiv.org/abs/2003.06975
- Paper Citation: @article{taco2020, title={TACO: Trash Annotations in Context for Litter Detection}, author={Pedro F Proença and Pedro Simões}, journal={arXiv preprint arXiv:2003.06975}, year={2020} }
Trained Model API
This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.
Find utilities and guides to help you start using the TACO: Trash Annotations in Context Dataset project in your project.
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