TACO: Trash Annotations in Context Dataset

Instance Segmentation

TACO: Trash Annotations in Context Dataset Computer Vision Project

taco

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Classes (21)
Clear plastic bottle
Corrugated carton Crisp packet
Disposable food container
Disposable plastic cup
Egg carton Foam cup Food waste Magazine paper Meal carton
Other plastic bottle
Other plastic wrapper
Plastic bottle cap
Plastic film
Plastic glooves
Plastic lid Plastic straw Plastic utensils Polypropylene bag
Single-use carrier bag
Styrofoam piece

Metrics

mAP
57.3%
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Description

TACO: Trash Annotations in Context Dataset

From: Pedro F. Proença; Pedro Simões

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:

Gif of the model running inference

Examples images from the dataset:

Example Image #2 from the Dataset
Example Image #5 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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Cite This Project

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-bumvw_dataset, title = { TACO: Trash Annotations in Context Dataset Dataset }, type = { Open Source Dataset }, author = { taco }, howpublished = { \url{ https://universe.roboflow.com/taco-9911u/taco-trash-annotations-in-context-bumvw } }, url = { https://universe.roboflow.com/taco-9911u/taco-trash-annotations-in-context-bumvw }, journal = { Roboflow Universe }, publisher = { Roboflow }, year = { 2025 }, month = { jan }, note = { visited on 2025-02-27 }, }