Mall_Surveillance_Object_Detection is a dataset for training YOLOv8 models. It contains annotated images for detecting four object classes: bag, busket, people, and product. The dataset was sourced from Kaggle, but its author, size, and update history are unknown.
Use Cases
- Train object detection models for retail security based on the four specified classes (bag, busket, people, product)
- Benchmark YOLOv8 model performance on surveillance footage
- Develop applications for counting people or products in a mall environment
Strengths
- Dataset is specifically designed for training the YOLOv8 object detection model
- Focuses on a defined set of four classes relevant to retail surveillance
Limitations
- Row count and dataset size are unknown, which may limit suitability assessment
- Column-level documentation is absent; field semantics must be inferred after download
- Last update date is unknown; freshness unverified