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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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