| # 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 | |
| ``` | |
| 📦 Cattle_Body_Parts_OD.zip | |
| ┣ 📂 images | |
| ┃ ┣ 📜 image1.jpg | |
| ┃ ┣ 📜 image2.jpg | |
| ┃ ┗ ... | |
| ┗ 📂 annotations | |
| ┣ 📜 image1.json | |
| ┣ 📜 image2.json | |
| ┗ ... | |
| ``` | |
| ### 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. | |