Garden Anthracnose Disease Identification Image Dataset

With the intensification and large-scale application of agricultural production, crop diseases, especially anthracnose, have become a major challenge affecting economic efficiency. Currently, disease detection relies on manual experience and small-scale field observations, making it difficult to identify and respond to disease changes in real-time effectively. This dataset provides high-quality anthracnose images to assist in the development of intelligent disease detection systems, improving agricultural production efficiency and crop health. Data collection is conducted using professional agricultural drones and high-resolution cameras, covering various plant species and disease severities, with detailed delineation of disease spots. Data quality is ensured through multiple rounds of expert annotation, cross-verification by multiple teams, and consistency checks. The annotation team consists of pathology experts and PhD botanists, with a team size of over 20 people. The image data is standardized and enhanced, stored in high-quality JPG format, making it suitable for model training.