Electronics Object Image Dataset | Computer Parts Computer Vision Project
Updated a month ago
Electronics Object Image Dataset | Computer Parts
Daily electronic items images like Earphones, Chargers, Mouse, etc.
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 5000+ original Electronic Items images captured and crowdsourced from over 1000+ urban and rural areas, where each image is manually reviewed and verified by computer vision professionals at Datacluster Labs.
Dataset Features
- Dataset size : 5000+
- Captured by : Over 1000+ crowdsource contributors
- Resolution : 99% images HD and above (1920x1080 and above)
- Location : Captured with 800+ cities accross India
- Diversity : Various lighting conditions like day, night, varied distances, view points etc.
- Device used : Captured using mobile phones in 2020-2021
- Applications : Electronics Detection, Daily item detection, Home Automation, 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.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
electronics-object-image-dataset-computer-parts-n9725_dataset,
title = { Electronics Object Image Dataset | Computer Parts Dataset },
type = { Open Source Dataset },
author = { ferds2 },
howpublished = { \url{ https://universe.roboflow.com/ferds2/electronics-object-image-dataset-computer-parts-n9725 } },
url = { https://universe.roboflow.com/ferds2/electronics-object-image-dataset-computer-parts-n9725 },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2024 },
month = { oct },
note = { visited on 2024-11-25 },
}