Vineyard Scene Recognition Data

The current agricultural industry faces multifaceted challenges such as climate change, pests, and diseases. Farmers need efficient information to make planting decisions. Existing solutions often rely on manual experience and lack systematic data support, leading to insufficient decision accuracy. This dataset aims to assist AI models in better recognizing orchard planting patterns and environmental features by providing images of vineyard scenes under different seasons and lighting conditions, thus enhancing the intelligence level of agricultural production. Data collection is mainly accomplished using high-resolution cameras to capture diverse environmental variables across various seasons and lighting conditions. To ensure data quality, multiple rounds of annotation, consistency checks, and expert reviews were conducted to ensure the accuracy of the labeling information for each image. The data is stored in JPG format and is organized by season and lighting conditions.