Project Overview
Objective
Prepared EV socket segmentation and tracking assets for temporal computer-vision experiments.
Stack
Computer Vision DatasetSegmentation MasksVideo Test AssetsTracking
Delivery highlights
- Organized media and segmentation/tracking artifacts for studying EV charger sockets across consecutive video frames, including the relationship between pixel-level masks and persistent object identities.
- The audited snapshot contains dataset and test assets without runnable source code. It therefore supports experimentation and visual validation, but does not by itself confirm the claimed RF-DETR-Seg, YOLO, or ByteTrack integration as a reproducible software pipeline.
- Reuse should begin with licence and privacy review, followed by dataset documentation and a reproducible training or inference implementation.