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Dataset Card for COIL-100
This is a FiftyOne dataset with 7200 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
import fiftyone.utils.huggingface as fouh
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = fouh.load_from_hub("Voxel51/COIL-100")
# Launch the App
session = fo.launch_app(dataset)
Dataset Details
Dataset Description
There are 7,200 images of 100 objects. Each object was turned on a turnable through 360 degrees to vary object pose with respect to a fixed color camera. Images of the objects were taken at pose intervals of 5 degrees. This corresponds to 72 poses per object. There images were then size normalized. Objects have a wide variety of complex geometric and reflectance characteristics.
- Curated by: Center for Research on Intelligent Systems at the Department of Computer Science , Columbia University
- Language(s) (NLP): en
- License: apache-2.0
Dataset Sources [optional]
- Paper: https://www1.cs.columbia.edu/CAVE/publications/pdfs/Nene_TR96_2.pdf
- Homepage: https://www.cs.columbia.edu/CAVE/software/softlib/coil-100.php
Uses
This dataset is intended for non-commercial research purposes only.
Data Collection and Processing
COIL-100 was collected by the Center for Research on Intelligent Systems at the Department of Computer Science , Columbia University. The database contains color images of 100 objects. The objects were placed on a motorized turntable against a black background and images were taken at pose internals of 5 degrees. This dataset was used in a real-time 100 object recognition system whereby a system sensor could identify the object and display its angular pose.
Citation
BibTeX:
@article{nene1996columbia,
title={Columbia object image library (coil-100)},
author={Nene, Sameer A and Nayar, Shree K and Murase, Hiroshi},
year={1996},
publisher={Technical report CUCS-006-96}
}
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