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… See the full description on the dataset page: https://huggingface.co/datasets/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:
44PNG files - Dataset file:
sam3_eval_pack.jsonl - Image layout:
images/<source_case_id>/current.pngandimages/<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.