Smart Camera Image Classification Dataset

The current smart device industry faces challenges in intelligently classifying surveillance images, especially regarding accurate recognition in complex environments. Existing solutions often rely on traditional image processing techniques, which struggle to adapt to variable scenarios and real-time requirements. This dataset aims to assist researchers and developers in overcoming issues of low image recognition accuracy and long response times by providing high-quality indoor and outdoor surveillance camera images. The dataset includes diverse image samples suitable for training and testing deep learning models. Data collection was conducted using various brands and models of surveillance cameras, covering scenarios under different lighting and weather conditions. To ensure data quality, we implemented multiple rounds of annotation and consistency checks, with all annotations reviewed by professionals. Data storage is in JPEG format, organized by category and timestamp for easy retrieval and use.