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ICLR bundle: RWTD, RWTD-COCO, TextureADE, CSTD (verified 256)
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{
"name": "CAP",
"path": "/home/aviad/datasets/CAP",
"texture_type": "category-independent appearance partitioning (two-region transition crops)",
"k_nominal": "2",
"source": "RWTD_Coco CAP_balanced_256: 212 manually curated anchors plus 44 CAP-supervised additions, all from the COCO-Stuff 164K stuffthingmaps tiers; NOT derived from ADE20K",
"built_utc": "2026-09-02T08:45:51.767195+00:00",
"selection": {
"method": "manual review",
"selection_dir": "(local manual selection)",
"n_selected": 256,
"by_source_pool": {
"CAP_500": 152,
"CAP_500/candidate": 13,
"CAP_FC/candidate": 8,
"raw/tier1": 49,
"raw/tier2": 34
},
"by_tier": {
"tier1": 201,
"tier2": 55
},
"n_cap500": 248,
"n_cap_cf": 8,
"by_curation": {
"CAP_supervised_extension": 44,
"manual anchor": 212
},
"anchor_note": "The manually curated anchors are identified per entry by provenance.curation.is_cap_anchor=true; the rest were added by the CAP-supervised ranker. No separate anchor directory is kept -- filter on that flag instead.",
"note": "Entries with cap_selection.cap_cf=true come from the CAP-CF pool and were chosen because their two regions look alike. They are counterfactual probes, not typical samples; keep them separable when computing set-level statistics."
},
"directories": {
"images": 256,
"masks": 256,
"overlays": 256,
"textures_mask": 512
},
"metadata_files": {
"metadata.json": {
"num_entries": 256,
"total_texture_instances": 512,
"non_empty_descriptions": 0
}
},
"k_distribution": {
"2": 256
},
"description_policy": "blank (annotation_status=pending_human)",
"provenance_audit": {
"ade20k_derived_entries": 0,
"clean": true,
"image_bytes_verified_against_source": 256
},
"mirrors": {
"repo_copy": "RWTD_Coco/output/CAP_balanced_256",
"note": "same 256 samples and the same region masks. This copy follows the Detecture dataset layout: masks/<id>_annotation.png is the RGB annotation the sibling datasets use. The repo copy follows the RWTD_Coco tier layout instead -- the same regions live there as label_masks/<id>.png (tri-value) and masks/<id>.png (binary, region A) -- and it adds manifest.jsonl/.csv, source_label_crops/ and contact_sheets/ for the statistics pipeline."
},
"image_sizes": {
"sampled": 50,
"unique_sizes_in_sample": 4,
"width": {
"min": 192,
"max": 256
},
"height": {
"min": 192,
"max": 256
},
"constant": false,
"example_size": [
192,
192
]
}
}