6 Commits

Include renames

Author	SHA1	Message	Date
JensandClaude Opus 5	c4d873149b	page the analysis run listings ... Detection and segmentation run listings returned every run a project had ever produced. Runs accumulate with every analysis while the panel only ever draws the recent ones, so the response grew without bound for no benefit. Both take limit and offset now and report total, limit, offset and truncated, matching the result listings. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>	2026-08-22 22:18:08 +02:00
JensandClaude Opus 5	1a1a9af6e7	give segmentation QA the same threshold-independent view as detection ... Detection QA reports a precision/recall curve, average precision and a calibration sweep; segmentation QA reported a single operating point. Both rank their outputs by confidence, so the same view applies, and the asymmetry meant the two panels answered different questions about comparable runs — an inconsistency introduced when detection gained the curve. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>	2026-08-22 20:47:30 +02:00
JensandClaude Opus 5	5b3839dc89	page detection and segmentation results instead of returning all of them ... /detection/runs/{id}/detections and its GeoJSON sibling returned every persisted detection, as did the segmentation equivalents. A regional run holds tens of thousands, and these are the endpoints the results table and the map overlay call after every run. They now take limit and offset, default to 2.000, and report total, limit, offset and truncated so the complete population stays visible while what is transferred does not. The GeoJSON responses carry the same window in a geointel_result_window foreign member. Rows are ordered by confidence, so a capped overlay draws the strongest detections rather than an arbitrary slice, and the lab says how many of how many are being shown rather than silently presenting a page as the whole run. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>	2026-08-22 15:24:46 +02:00
JensandClaude Opus 5	08188005bd	correct the tiled inference chain and move runs off the request thread ... Tile handling produced results that were wrong before any model quality question arose: - orthophoto tiles reached the model through PIL convert("RGB"), which truncates the high byte of a 16-bit product and treats a 4-band RGB+NIR tile's infrared channel as colour. Tiles are now read with rasterio, the visible bands are chosen explicitly, and values are percentile-stretched across all three bands together so hue is preserved; - an object wider than the tile overlap was truncated by both tiles into two boxes that barely intersect, so IoU suppression kept both: two false positives and one missed footprint per seam building. Suppression now also compares overlap against the smaller box, and boxes cut by an interior tile edge are dropped in favour of the neighbouring tile's complete view; - georeferencing fell back to an assumed EPSG:4326 when a manifest carried no CRS, producing geometry that renders plausibly in the wrong place. QA already refused such a tile; inference now fails closed too. Segmentation QA scored candidates against every reference feature in the dataset, so every building outside the inferred tiles counted as a false negative. It now applies the same persisted tile coverage that detection QA has always used, including the indexed ST_Intersects prefilter. Duplicate suppression uses an STRtree instead of the O(n^2) scan, tiles are predicted in batches of YOLO_BATCH_SIZE (a setting that existed but was never read), and detection/segmentation runs can be queued through /run-async for a polling background worker rather than holding an HTTP worker thread for minutes of GPU work. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>	2026-08-22 14:32:44 +02:00
Codex	0fae53a7de	Harden RC7 API response contracts	2026-07-18 05:07:35 +02:00
Codex	6ea3586a3e	Initial GeoIntel V1 foundation	2026-06-16 23:36:32 +02:00