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Domestic Trash / Garbage Dataset

Dataset for trash detection

About Dataset

This dataset is collected by DataCluster Labs, India. To download full dataset or to submit a request for your new data collection needs, please drop a mail to: sales@datacluster.ai

This dataset is an extremely challenging set of over 9000+ original Trash/Garbage images captured and crowdsourced from over 2000+ urban and rural areas, where each image is manually reviewed and verified by computer vision professionals at ****DC Labs.

Dataset Features

Dataset size : 9000+
Captured by : Over 2000+ crowdsource contributors
Resolution : 99.9% images HD and above (1920x1080 and above)
Location : Captured across 500+ cities
Diversity : Various lighting conditions like day, night, varied distances, different material view points etc.
Device used : Captured using mobile phones in 2020-2022
Usage : Trash detection, Material classification, Garbage segregation, Trash segregation, etc.

Available Annotation formats COCO, YOLO, PASCAL-VOC, Tf-Record

The images in this dataset are exclusively owned by Data Cluster Labs and were not downloaded from the internet. To access a larger portion of the training dataset for research and commercial purposes, a license can be purchased. Contact us at sales@datacluster.ai Visit www.datacluster.ai to know more.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            domestic-trash_dataset,
                            title = { Domestic Trash  Dataset },
                            type = { Open Source Dataset },
                            author = { DataCluster Labs },
                            howpublished = { \url{ https://universe.roboflow.com/datacluster-labs-agryi/domestic-trash } },
                            url = { https://universe.roboflow.com/datacluster-labs-agryi/domestic-trash },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { sep },
                            note = { visited on 2024-05-05 },
                            }