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Add https://youtu.be/isc06_9qnM0 to docs (#14525)

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Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Muhammad Rizwan Munawar 2024-07-18 18:11:43 +05:00 committed by GitHub
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docs/en/datasets/classify/caltech256.md
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@ -8,6 +8,17 @@ keywords: Caltech-256 dataset, object classification, image dataset, machine lea
The [Caltech-256](https://data.caltech.edu/records/nyy15-4j048) dataset is an extensive collection of images used for object classification tasks. It contains around 30,000 images divided into 257 categories (256 object categories and 1 background category). The images are carefully curated and annotated to provide a challenging and diverse benchmark for object recognition algorithms.
<p align="center">
<br>
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/isc06_9qnM0"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>
</iframe>
<br>
<strong>Watch:</strong> How to Train Image Classification Model using Caltech-256 Dataset with Ultralytics HUB
</p>
## Key Features
- The Caltech-256 dataset comprises around 30,000 color images divided into 257 categories.