Green Pepper Fruit Segmentation Dataset

Green pepper cultivation is an important economic crop in agriculture, but during the harvesting and management process, the identification and segmentation of fruit still face many challenges. For example, traditional manual identification is slow and prone to errors, affecting production efficiency. Therefore, existing automated detection technologies often have technical limitations and lack professional datasets for green pepper characteristics. This dataset aims to provide high-quality green pepper fruit images and their semantic segmentation annotations to help researchers and developers improve the accuracy and efficiency of fruit detection. The dataset contains 2000 precisely annotated images of green pepper fruits, each accompanied by corresponding segmentation masks. During data collection, a high-resolution camera was used under natural light conditions, with special attention given to capturing images at various growth stages and in different environments. To ensure data quality, multiple rounds of annotation and consistency checks were implemented, with all annotations reviewed by experts in the agricultural field to ensure accuracy and consistency. Data is organized in JPEG format for quick access and processing.