Orchard Vehicle Image Classification Dataset

The current agricultural sector faces challenges of labor shortages and low production efficiency, particularly in orchard management. Intelligent transport vehicles are gradually becoming an industry trend. However, existing vehicle recognition technologies often rely on traditional methods, which cannot effectively handle diverse vehicle types and complex environments. This dataset aims to provide a rich collection of image samples to address issues of accuracy and efficiency in vehicle recognition, thus supporting the development of agricultural automation. Data collection primarily uses high-resolution cameras in various orchard environments, including different weather conditions such as sunny and cloudy days. Multiple rounds of review and expert verification are conducted during the annotation process to ensure high-quality data. Data is stored in JPG format, with a clear structure, making it easy for subsequent processing and analysis.