Electric Wheelchair Model Classification Image Dataset

In the current medical industry, the use of electric wheelchairs is increasingly popular, especially in elderly care and rehabilitation. However, existing methods for classifying electric wheelchairs often rely on manual labeling, which is inefficient and prone to errors. Current solutions often cannot provide efficient, accurate classification support, leading to resource waste and poor patient experience. This dataset aims to provide high-quality electric wheelchair image data to support automated image classification tasks, thereby improving classification accuracy and efficiency. Data collection uses professional photography equipment to capture different models of electric wheelchairs in a natural light environment, ensuring image quality. For quality control, multiple rounds of labeling and consistency checks are employed to ensure accurate labeling of each image. The data is stored in JPG format, organized by category for easy retrieval and use.