Pharmaceutical Classification and Detection Dataset

In the current medical industry, there are significant challenges in the classification and detection of pharmaceuticals, particularly given the wide variety of drugs and inconsistent image quality. Existing automated detection systems struggle to ensure accuracy. Traditional manual annotation methods are inefficient and prone to errors, resulting in low accuracy in drug identification. To address this issue, this dataset aims to provide high-quality image data for pharmaceutical classification and detection, helping to improve the performance of machine learning models in drug recognition tasks. Data collection is done using high-resolution cameras in a standardized environment to ensure image clarity. Quality control measures, including multiple rounds of annotation and expert review, ensure data annotation accuracy and consistency. Data is stored in JPEG format and organized by category in folders for ease of subsequent use.