Image Classification Annotation Task

I have a sizeable batch of raw photographs that must be turned into a clean, AI-ready image-classification dataset. Every file simply needs a single or multi-label tag that tells my model whether it contains Vehicles, People, or both. No bounding boxes or pixel-perfect masks are required—just accurate whole-image labels.

You’ll work in the annotation tool of your choice (LabelImg, CVAT, VoTT, Roboflow, etc.) as long as the final export is compatible with standard machine-learning pipelines. A comma-separated CSV or JSON with filename-to-label mapping is perfect.

Selected classes
• Vehicles
• People

Deliverables
• Completed project file or export (CSV/JSON) listing each image and its assigned class(es)
• The original images left unaltered in their folder structure
• A brief log describing any ambiguous cases or edge decisions you encountered

I’ll share the image set and exact label taxonomy once we start; you then upload the finished annotation package for review. Clean, consistent work and clear communication will get this wrapped up quickly.

Image sets:
Labelling and Annotation- 8745