Weed Detection Dataset

Currently, the agricultural field faces a serious threat to crop growth due to weeds, resulting in reduced crop yield and resource waste. Existing weed detection methods often rely on manual observation, which is not only inefficient but also prone to subjective influence. To improve the accuracy and efficiency of weed detection, this dataset aims to provide high-quality weed image data to support the development of automated object detection technology. The data collection is conducted using drones during different crop growth stages, ensuring data diversity. Each image undergoes multiple rounds of annotation and consistency checks to ensure annotation accuracy and reliability. The data is stored in JPG format, with a clear organizational structure for easy subsequent processing and analysis.