Project summary
Campus-Objects is a multi-class object detection project built around annotated campus imagery and LW-DETR.
Object detection project using LW-DETR and PyTorch on 3,000+ annotated campus images, achieving 0.71 mAP@0.5.
Campus-Objects is a multi-class object detection project built around annotated campus imagery and LW-DETR.
The project uses 3,000+ annotated campus images prepared for object detection workflows.
The pipeline uses PyTorch and LW-DETR for object detection, with dataset preparation aligned to COCO-style training workflows.
The model achieved 0.71 mAP@0.5 on the available evaluation setup.
The repository content does not provide enough detail to state deployment status, production usage, or per-class performance.
Open to AI/ML internships, research collaborations, fellowships, and December 2026 full-time opportunities.