Grass Seed Recognition Classification Dataset

The current agricultural sector faces challenges in grass seed recognition. Traditional methods rely on manual observation, which is inefficient and prone to error. Existing solutions often lack large-scale data support, resulting in low recognition accuracy. This dataset aims to provide a rich library of grass seed images to support the training of machine learning algorithms in grass seed recognition, improving overall identification efficiency and accuracy. The dataset is composed of high-resolution images collected from various farmland using high-performance cameras, ensuring data quality. Quality control involves multiple rounds of labeling and expert review to ensure accurate annotations for each image. The data storage format is JPG, organized by grass seed category for easy subsequent processing and analysis.