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geointel/artifacts/evidence/accuracy/model-training/20260809-reviewedexp6-minpx4-derived-corpus.json
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derive cleaner min-4px YOLO corpus
2026-08-09 19:51:17 +02:00

64 lines
3.1 KiB
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{
"schema_version": 1,
"evidence_id": "reviewedexp6-minpx4-derived-corpus-r1",
"created_at": "2026-08-09T19:45:41+02:00",
"status": "complete_experimental_only",
"claim_boundary": "Deterministic derived-corpus improvement and AI-assisted visual triage only; no human-review, governed training, evaluation, promotion or production claim.",
"source": {
"dataset_dir": "/app/storage/operator-data/yolo-building-aoi1024-reviewedexp6-minpx3vis035",
"summary_sha256": "7c917e31216d1df2174c0f9c736f88a81f3835aa991971f8fb8665e17ddf5c9c",
"tile_size": 512,
"stride": 256,
"min_label_px": 3.0,
"min_visible_ratio": 0.35,
"tile_count": 252,
"label_count": 79192
},
"derived": {
"dataset_dir": "/app/storage/operator-data/yolo-building-aoi1024-reviewedexp6-minpx4-derived-r1",
"manifest_sha256": "8a80d0e9d5ac2d32556e2f1ea0c6009045d48a3e56d931b3161622dca4173a67",
"summary_sha256": "391b0302cc8a46d15fef426d8971a4a8e594fb6d63ed1c7ce16feeee9f1406",
"quality_audit_sha256": "0fc9391ce09a399f51f1e0ed30c677f482c7c1b49b187926da01ecdfd9f1067e",
"outlier_audit_sha256": "c2453abb83aaff8aebd84f63efb14da131225192cf0434d5d1df7cf06be240ca",
"relationship_audit_sha256": "61660d0c448ff579272bc585de8140e82d1577c0b017e1c078b66dc093f14c2e",
"cross_tile_repetition_audit_sha256": "9ca22d83271707713f7f96d5409af598f834787ad5a48be14f8752a704de0da0",
"min_label_px": 4.0,
"tile_count": 252,
"positive_tile_count": 234,
"negative_tile_count": 18,
"label_count": 77380,
"removed_label_count": 1812,
"excluded_tile_count": 0,
"invalid_label_count": 0,
"missing_label_file_count": 0,
"sub_4_pixel_label_count": 0,
"extreme_aspect_label_count": 10,
"tile_edge_label_count": 4840,
"possible_nested_pair_count": 41,
"exact_duplicate_pair_count": 0,
"near_duplicate_pair_count": 0,
"cross_split_repetition_group_count": 0,
"training_release_eligible": false
},
"visual_review": {
"reviewer_type": "ai_assistant",
"human": false,
"rendered_tile_count": 252,
"rendered_label_count": 77380,
"contact_sheet_sha256s": [
"f197769ca68da08745277ff93331f3ea93738f6b63eb383a3b6168a9e438ee12",
"e9ecde3f38b4f580adb7523f647460af5d5933e2e1efe1f11f98c1656ca1cd13",
"497bf5878560113fcc59f21aeba09b1de167cb3eff4d0327c7584ba8caeebf70",
"4a8262291ed29699ae59517e1a542e513a50081a225ea1e84268afa37f99d6df"
],
"extreme_aspect_contact_sheet_sha256": "6c08c42eb6478d1fa06745135dd588ce6522b5cec4adf0bdcd177d77cd6c78a7",
"conclusion": "All 252 tiles remain visually coherent; pure-background tiles remain empty, sparse contexts remain distinct, and the ten remaining extreme-aspect labels predominantly correspond to plausible elongated structures."
},
"decision": {
"preferred_experimental_corpus": true,
"replaces_source_in_place": false,
"reason": "It deterministically removes all 1,812 visually marginal sub-4-pixel labels while preserving every tile and all larger labels with exact lineage.",
"remaining_gate": "Requires independent human review and the governed release-contract inputs before training eligibility."
}
}