Cattle Body Contour Segmentation Dataset

The current agricultural sector faces challenges in livestock management due to insufficient monitoring data and inefficiency, particularly in cattle condition assessment. Traditional methods often rely on manual observation, leading to insufficient data accuracy and real-time capabilities. Current solutions mainly focus on sensor-based data collection but lack sufficient image data to support the application of semantic segmentation technology. This dataset aims to help researchers and practitioners enhance the application of machine vision in agriculture by providing high-quality cattle body contour segmentation image data. Data collection is performed using high-resolution cameras under natural light and artificial lighting to ensure image clarity and detail richness. Meanwhile, all data undergo multiple rounds of annotation and consistency checks to ensure labeling accuracy. The data is stored in JPG format, accompanied by JSON format for annotation information, organized into a unified file structure to facilitate subsequent processing and model training.