Annotated Object Detection Dataset of Five Herbivorous Animal Classes
Published: 9 May 2025| Version 1 | DOI: 10.17632/fwm6z9tv3f.1
Contributors:
Muhammad Juman Jhatial, Riaz Ahmed Shaikh, Rafaqat Hussain ArainDescription
This dataset contains 10,000 high-resolution images of herbivorous animals, annotated for object identification and detection tasks. It is intended for use in training and evaluating deep learning models for animal detection in natural or farm environments. Each image contains a single instance of one of the following five animal classes: Buffalo Camel Cow Goat Sheep The annotations include bounding box coordinates and class labels, formatted for compatibility with modern object detection frameworks such as YOLO, Pascal VOC, or COCO, depending on the export version.
Files
Institutions
- Shah Abdul Latif University
Categories
Computer Vision, Applied Computer Science, Deep Learning