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# Cattle Body Parts Image Dataset for Object Detection
## Intro
This dataset is a curated collection of images featuring various cattle body parts aimed at facilitating object detection tasks. The dataset contains a total of 428 high-quality photos, meticulously annotated with three distinct classes: "Back," "Head," and "Leg."
The dataset can be downloaded using [this link](https://www.kaggle.com/datasets/alikhalilit98/cattle-body-parts-dataset-for-object-detection). The dataset is also available at Roboflow Universe.
<p align="center">
<a href="https://universe.roboflow.com/ali-khalili/cattle-body-parts-dataset-for-object-detection">
<img src="https://app.roboflow.com/images/download-dataset-badge.svg"></img>
</a>
</p>
### Acquisition
The dataset creation involved the following steps:
- **Initial Data:** Images were collected and annotated to create a base dataset for training.
- **Model Training:** A [YOLOv7](https://github.com/WongKinYiu/yolov7) model was trained to recognize target objects in the annotated images.
- **Data Acquisition Script:** An automated script fetched videos from the internet.
- **Conversion and Filtering:** Videos were turned into frames; similar frames were filtered out using Cosine Similarity.
- **Object Detection:** The trained model identified objects in the new images.
- **Quality Check:** A comprehensive review ensured dataset accuracy and consistency.
## Motivation
Accurate and reliable identification of different cattle body parts is crucial for various agricultural and veterinary applications. This dataset aims to provide a valuable resource for researchers, developers, and enthusiasts working on object detection tasks involving cattle, ultimately contributing to advancements in livestock management, health monitoring, and related fields.
## Data
### Overview
- Total Images: 428
- Classes: Back, Head, Leg
- Annotations: Bounding boxes for each class
Below is an example image from the dataset.
<div align="center">
<img src="readme_assets/sample.png"/>
</div>
### Contents
```
π¦ Cattle_Body_Parts_OD.zip
β£ π images
β β£ π image1.jpg
β β£ π image2.jpg
β β ...
β π annotations
β£ π image1.json
β£ π image2.json
β ...
```
### Annotation Format
Each annotation file corresponds to an image in the dataset and is formatted as per the [LabelMe](https://github.com/wkentaro/labelme) [JSON](https://www.json.org/json-en.html) standard. These annotations define the bounding box coordinates for each labeled body part, enabling straightforward integration into object detection pipelines.
## License
<a rel="license" href="http://creativecommons.org/licenses/by/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International License</a>.
## Contact
For any questions, concerns, or collaboration opportunities, please don't hesitate to contact me on my [LinkedIn](https://www.linkedin.com/in/ali-khalili-790b10146/) account.
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