Smart Speaker Appearance Classification Dataset

The retail e-commerce industry is facing significant challenges in effectively classifying and categorizing smart speakers due to the variety of shapes and designs available. Existing solutions often struggle with accuracy and consistency, leading to difficulties in inventory management and product recommendations. This dataset aims to specifically tackle the classification of various smart speaker appearances, addressing the need for high-quality labeled data to enhance machine learning models. The dataset includes images collected from various online retail platforms under controlled lighting conditions to ensure consistency. Quality control measures such as multi-round annotations and expert reviews were implemented to maintain high precision. The data is stored in JPEG format, organized by category, ensuring easy access and usability for training models.