Poultry Health Status Recognition Dataset

The current agricultural industry faces the challenge of frequent poultry diseases. Traditional health monitoring methods often rely on manual inspection, which is inefficient and prone to errors. Existing solutions have some effectiveness, but due to the lack of high-quality data support, the model's generalization ability is insufficient to accurately identify the health status of poultry. This dataset aims to provide rich image data of poultry health statuses, supporting the development of object detection technology to achieve efficient and accurate health monitoring. Data collection is conducted using high-resolution cameras in a standard breeding environment to ensure image quality. To ensure data accuracy, multi-round labeling and expert review are employed for quality control. The data is stored in JPEG format, organized so that each image folder contains corresponding annotation information for easy subsequent processing and analysis.