TACO: Trash Annotations in Context Dataset Computer Vision Project
Mohamed Traore
Updated 5 months ago
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views1.2k
downloadsClasses (59)
Aerosol
Aluminium blister pack
Aluminium foil Battery Broken glass Carded blister pack
Cigarette Clear plastic bottle
Corrugated carton Crisp packet Disposable food container
Disposable plastic cup
Drink can Drink carton Egg carton Foam cup Foam food container
Food Can Food waste Garbage bag Glass bottle Glass cup Glass jar Magazine paper Meal carton Metal bottle cap
Metal lid Normal paper Other carton Other plastic
Other plastic bottle
Other plastic container
Other plastic cup
Other plastic wrapper
Paper bag Paper cup Paper straw Pizza box Plastic bottle cap
Plastic film Plastic glooves
Plastic lid Plastic straw Plastic utensils Polypropylene bag Pop tab Rope & strings
Scrap metal Shoe Single-use carrier bag
Six pack rings
Spread tub Squeezable tube Styrofoam piece Tissues Toilet tube Tupperware Unlabeled litter
Wrapping paper Metrics
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Description
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} }
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LICENSE
CC BY 4.0 If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
taco-trash-annotations-in-context_dataset,
title = { TACO: Trash Annotations in Context Dataset Dataset },
type = { Open Source Dataset },
author = { Mohamed Traore },
howpublished = { \url{ https://universe.roboflow.com/mohamed-traore-2ekkp/taco-trash-annotations-in-context } },
url = { https://universe.roboflow.com/mohamed-traore-2ekkp/taco-trash-annotations-in-context },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2024 },
month = { aug },
note = { visited on 2024-12-21 },
}