Weed Species Classification Dataset

The current agricultural sector faces the challenge of weed management, as the variety of weeds has a severe impact on crops. Traditional methods of weed identification are inefficient and fail to meet the needs of precision agriculture. Therefore, it is necessary to develop an efficient weed species classification dataset. This dataset aims to provide high-quality training data for deep learning models in weed identification. Data collection was conducted using high-resolution cameras in various farmland environments, ensuring diversity and representativeness of the data. Each image has undergone multiple rounds of annotation and consistency checks, reviewed by professionals to ensure annotation accuracy. Data is stored in JPG format and organized by weed species for easy retrieval and usage.