ChrisRPL/blackline-atlas-sam3-real-eval-v2

Blackline Atlas SAM3 Real-Image Eval Pack

This dataset packages the Blackline Atlas SAM3/SAM3.1 selected-site evidence eval pack with real SimSat Sentinel image pairs.

It is an evaluation and integration dataset, not a training benchmark. The cases are exact civilian lifeline sites with current/baseline satellite frames, text prompts, expected visual evidence tags, expected triage action, and optional normalized bboxes.

Contents

• Cases: 22
• Images: 44 PNG files
• Dataset file: sam3_eval_pack.jsonl
• Image layout: images/<source_case_id>/current.png and images/<source_case_id>/baseline.png

Intended Use

Use this dataset to run SAM3/SAM3.1 zero-shot promptable segmentation against selected civilian disruption sites before deciding whether any segmentation fine-tuning is justified.

Important Limitations

• This is not a tactical targeting dataset.
• Labels are Blackline operational eval labels, not expert pixel masks.
• Fine-tuning SAM3/SAM3.1 still requires real binary mask supervision; these rows are for inference/eval gating.
• Sentinel resolution limits small-object and fine-grained damage claims.