Initial public release

scripts/run_detection_quality_matrix.sh

@@ -0,0 +1,442 @@
+#!/usr/bin/env bash
+set -euo pipefail
+
+usage() {
+  cat >&2 <<'EOF'
+Usage:
+  REAL_RASTER_PATH=/path/to/orthophoto.tif \
+  REAL_REFERENCE_VECTOR_PATH=/path/to/reference-buildings.geojson \
+  QUALITY_MODEL_ASSET_IDS="yolov8n-building-segmentation-pt yolov8n-pt" \
+  QUALITY_TILE_SIZES="512 640" \
+  QUALITY_TILE_OVERLAPS="64" \
+  QUALITY_THRESHOLDS="0.50 0.25 0.15" \
+  QUALITY_SAMPLE_SLUG="mol" \
+  bash scripts/run_detection_quality_matrix.sh [base_url]
+
+or:
+  bash scripts/run_detection_quality_matrix.sh [base_url] /path/to/orthophoto.tif /path/to/reference-buildings.geojson
+
+Required inputs:
+  REAL_RASTER_PATH             Georeferenced .tif/.tiff/.geotiff raster.
+  REAL_REFERENCE_VECTOR_PATH   EPSG-aware .geojson/.json reference vector with building polygons.
+
+Optional environment:
+  QUALITY_MODEL_ASSET_IDS      Space/comma separated local model asset IDs. Default: active configured model asset.
+  QUALITY_TILE_SIZES           Space/comma separated raster tile sizes, default: 640.
+  QUALITY_TILE_OVERLAPS        Space/comma separated raster tile overlaps, default: 64.
+  QUALITY_THRESHOLDS           Space/comma separated confidence thresholds, default: 0.50 0.25 0.15.
+  QUALITY_OUTPUT_DIR           Output directory, default: artifacts/detection-quality-matrix/<timestamp>.
+  QUALITY_SAMPLE_SLUG          Optional AOI slug included in persisted project names.
+  REAL_PROJECT_REGION          Persisted project region forwarded to the workflow.
+  REAL_AREA_NAME               Persisted AOI name when REAL_AREA_BBOX is set.
+  REAL_AREA_BBOX               Optional EPSG:4326 minx,miny,maxx,maxy AOI bounds.
+  REAL_IOU_THRESHOLD           QA IoU threshold, default inherited by the underlying workflow.
+
+This script never downloads models and never uses fixture detections. It repeats
+the existing real-data upload/tile/detection/QA workflow for each matrix row.
+EOF
+}
+
+ROOT="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)"
+cd "$ROOT"
+
+BASE_URL="${1:-${GE_INTEL_BASE_URL:-http://localhost:1202}}"
+REAL_RASTER_PATH="${2:-${REAL_RASTER_PATH:-}}"
+REAL_REFERENCE_VECTOR_PATH="${3:-${REAL_REFERENCE_VECTOR_PATH:-}}"
+QUALITY_MODEL_ASSET_IDS="${QUALITY_MODEL_ASSET_IDS:-${REAL_MODEL_ASSET_ID:-__active__}}"
+QUALITY_TILE_SIZES="${QUALITY_TILE_SIZES:-640}"
+QUALITY_TILE_OVERLAPS="${QUALITY_TILE_OVERLAPS:-64}"
+QUALITY_THRESHOLDS="${QUALITY_THRESHOLDS:-0.50 0.25 0.15}"
+QUALITY_SAMPLE_SLUG="${QUALITY_SAMPLE_SLUG:-}"
+REAL_PROJECT_REGION="${REAL_PROJECT_REGION:-Kempen}"
+REAL_AREA_NAME="${REAL_AREA_NAME:-${QUALITY_SAMPLE_SLUG:-Detection quality} AOI}"
+REAL_AREA_BBOX="${REAL_AREA_BBOX:-}"
+QUALITY_OUTPUT_DIR="${QUALITY_OUTPUT_DIR:-artifacts/detection-quality-matrix/$(date -u +%Y%m%dT%H%M%SZ)}"
+
+if [ "${BASE_URL}" = "-h" ] || [ "${BASE_URL}" = "--help" ]; then
+  usage
+  exit 0
+fi
+
+if [ -z "${REAL_RASTER_PATH}" ] || [ -z "${REAL_REFERENCE_VECTOR_PATH}" ]; then
+  usage
+  exit 2
+fi
+
+if ! command -v curl >/dev/null 2>&1; then
+  echo "curl is required for detection quality matrix verification" >&2
+  exit 1
+fi
+
+if [ -n "${PYTHON_BIN:-}" ]; then
+  PYTHON_BIN="${PYTHON_BIN}"
+else
+  PYTHON_BIN=""
+  for candidate in python3 python.exe python; do
+    if command -v "${candidate}" >/dev/null 2>&1 && "${candidate}" -c "import json, sys" >/dev/null 2>&1; then
+      PYTHON_BIN="${candidate}"
+      break
+    fi
+  done
+fi
+
+if [ -z "${PYTHON_BIN}" ]; then
+  echo "A Python interpreter is required for JSON parsing" >&2
+  exit 1
+fi
+
+mkdir -p "${QUALITY_OUTPUT_DIR}"
+
+model_requests_normalized="$(printf '%s' "${QUALITY_MODEL_ASSET_IDS}" | tr ',' ' ')"
+tile_sizes_normalized="$(printf '%s' "${QUALITY_TILE_SIZES}" | tr ',' ' ')"
+tile_overlaps_normalized="$(printf '%s' "${QUALITY_TILE_OVERLAPS}" | tr ',' ' ')"
+thresholds_normalized="$(printf '%s' "${QUALITY_THRESHOLDS}" | tr ',' ' ')"
+matrix_manifest="${QUALITY_OUTPUT_DIR}/quality_matrix_requests.tsv"
+
+"${PYTHON_BIN}" - \
+  "${model_requests_normalized}" \
+  "${tile_sizes_normalized}" \
+  "${tile_overlaps_normalized}" \
+  "${thresholds_normalized}" \
+  "${matrix_manifest}" <<'PY'
+import re
+import sys
+
+models, tile_sizes, tile_overlaps, thresholds, output_path = sys.argv[1:6]
+
+
+def split_values(raw: str, name: str) -> list[str]:
+    values = [value.strip() for value in raw.split() if value.strip()]
+    if not values:
+        raise SystemExit(f"{name} must contain at least one value")
+    return values
+
+
+def safe_label(value: str) -> str:
+    label = re.sub(r"[^A-Za-z0-9_.-]+", "_", value.strip())
+    return label.replace(".", "p").replace("-", "_") or "active"
+
+
+model_values = split_values(models, "QUALITY_MODEL_ASSET_IDS")
+tile_size_values = split_values(tile_sizes, "QUALITY_TILE_SIZES")
+tile_overlap_values = split_values(tile_overlaps, "QUALITY_TILE_OVERLAPS")
+threshold_values = split_values(thresholds, "QUALITY_THRESHOLDS")
+
+for value in tile_size_values:
+    try:
+        tile_size = int(value)
+    except ValueError as exc:
+        raise SystemExit(f"Invalid tile size: {value}") from exc
+    if tile_size < 64:
+        raise SystemExit(f"Tile size must be at least 64: {value}")
+
+for value in tile_overlap_values:
+    try:
+        tile_overlap = int(value)
+    except ValueError as exc:
+        raise SystemExit(f"Invalid tile overlap: {value}") from exc
+    if tile_overlap < 0:
+        raise SystemExit(f"Tile overlap cannot be negative: {value}")
+
+for value in threshold_values:
+    try:
+        threshold = float(value)
+    except ValueError as exc:
+        raise SystemExit(f"Invalid confidence threshold: {value}") from exc
+    if threshold < 0.0 or threshold > 1.0:
+        raise SystemExit(f"Confidence threshold must be between 0 and 1: {value}")
+
+with open(output_path, "w", encoding="utf-8") as handle:
+    for model in model_values:
+        for tile_size in tile_size_values:
+            for overlap in tile_overlap_values:
+                for threshold in threshold_values:
+                    label = "_".join(
+                        [
+                            f"model_{safe_label(model)}",
+                            f"tile_{safe_label(tile_size)}",
+                            f"overlap_{safe_label(overlap)}",
+                            f"threshold_{safe_label(threshold)}",
+                        ]
+                    )
+                    handle.write(f"{model}\t{tile_size}\t{overlap}\t{threshold}\t{label}\n")
+PY
+
+echo "== GeoIntel detection quality matrix =="
+echo "Base URL: ${BASE_URL}"
+echo "Raster: ${REAL_RASTER_PATH}"
+echo "Reference vector: ${REAL_REFERENCE_VECTOR_PATH}"
+echo "Models: ${model_requests_normalized}"
+echo "Tile sizes: ${tile_sizes_normalized}"
+echo "Tile overlaps: ${tile_overlaps_normalized}"
+echo "Thresholds: ${thresholds_normalized}"
+echo "Output: ${QUALITY_OUTPUT_DIR}"
+
+run_index=0
+while IFS=$'\t' read -r model_request tile_size tile_overlap threshold run_label; do
+  run_index=$((run_index + 1))
+  run_log="${QUALITY_OUTPUT_DIR}/${run_label}.log"
+  quality_response="${QUALITY_OUTPUT_DIR}/${run_label}_quality_checks.json"
+  detection_run_response="${QUALITY_OUTPUT_DIR}/${run_label}_detection_run.json"
+  run_summary="${QUALITY_OUTPUT_DIR}/${run_label}_summary.json"
+  model_env="${model_request}"
+  if [ "${model_request}" = "__active__" ]; then
+    model_env=""
+  fi
+  project_sample_label=""
+  if [ -n "${QUALITY_SAMPLE_SLUG}" ]; then
+    project_sample_label=" sample ${QUALITY_SAMPLE_SLUG}"
+  fi
+
+  echo "-- Matrix run ${run_index}: model=${model_request} tile=${tile_size} overlap=${tile_overlap} threshold=${threshold} --"
+  if ! REAL_PROJECT_NAME="GeoIntel Detection Quality Matrix${project_sample_label} ${model_request} tile ${tile_size} overlap ${tile_overlap} threshold ${threshold}" \
+      REAL_PROJECT_REGION="${REAL_PROJECT_REGION}" \
+      REAL_AREA_NAME="${REAL_AREA_NAME}" \
+      REAL_AREA_BBOX="${REAL_AREA_BBOX}" \
+      REAL_MODEL_ASSET_ID="${model_env}" \
+      REAL_TILE_SIZE="${tile_size}" \
+      REAL_TILE_OVERLAP="${tile_overlap}" \
+      REAL_CONFIDENCE_THRESHOLD="${threshold}" \
+      bash scripts/verify_real_data_detection_qa_workflow.sh "${BASE_URL}" "${REAL_RASTER_PATH}" "${REAL_REFERENCE_VECTOR_PATH}" \
+      >"${run_log}" 2>&1; then
+    echo "Detection quality matrix run failed. Log: ${run_log}" >&2
+    tail -n 80 "${run_log}" >&2 || true
+    exit 1
+  fi
+
+  project_id="$(sed -n 's/^Project: //p' "${run_log}" | tail -n 1)"
+  area_id="$(sed -n 's/^Area: //p' "${run_log}" | tail -n 1)"
+  raster_dataset_id="$(sed -n 's/^Raster dataset: //p' "${run_log}" | tail -n 1)"
+  reference_dataset_id="$(sed -n 's/^Reference dataset: //p' "${run_log}" | tail -n 1)"
+  selected_model_asset_id="$(sed -n 's/^Model asset: //p' "${run_log}" | tail -n 1)"
+  manifest_path="$(sed -n 's/^Manifest: //p' "${run_log}" | tail -n 1)"
+  analysis_run_id="$(sed -n 's/^Analysis run: //p' "${run_log}" | tail -n 1)"
+  quality_check_id="$(sed -n 's/^Quality check: //p' "${run_log}" | tail -n 1)"
+  detection_count="$(sed -n 's/^Detections: //p' "${run_log}" | tail -n 1)"
+  export_id="$(sed -n 's/^Detection export: //p' "${run_log}" | tail -n 1)"
+
+  if [ -z "${project_id}" ] || [ -z "${analysis_run_id}" ] || [ -z "${quality_check_id}" ]; then
+    echo "Matrix run did not print project/run/quality ids. Log: ${run_log}" >&2
+    exit 1
+  fi
+
+  curl -fsS "${BASE_URL%/}/api/v1/projects/${project_id}/quality-checks?limit=200" > "${quality_response}"
+  curl -fsS "${BASE_URL%/}/api/v1/detection/runs/${analysis_run_id}" > "${detection_run_response}"
+
+  "${PYTHON_BIN}" - \
+    "${quality_response}" \
+    "${detection_run_response}" \
+    "${run_summary}" \
+    "${model_request}" \
+    "${selected_model_asset_id}" \
+    "${tile_size}" \
+    "${tile_overlap}" \
+    "${threshold}" \
+    "${project_id}" \
+    "${area_id}" \
+    "${raster_dataset_id}" \
+    "${reference_dataset_id}" \
+    "${manifest_path}" \
+    "${analysis_run_id}" \
+    "${quality_check_id}" \
+    "${detection_count}" \
+    "${export_id}" \
+    "${run_log}" <<'PY'
+import json
+import sys
+
+(
+    quality_path,
+    detection_run_path,
+    output_path,
+    model_request,
+    selected_model_asset_id,
+    tile_size,
+    tile_overlap,
+    threshold,
+    project_id,
+    area_id,
+    raster_dataset_id,
+    reference_dataset_id,
+    manifest_path,
+    analysis_run_id,
+    quality_check_id,
+    detection_count,
+    export_id,
+    run_log,
+) = sys.argv[1:19]
+
+with open(quality_path, "r", encoding="utf-8") as handle:
+    payload = json.load(handle)
+if "data" not in payload:
+    raise SystemExit("Quality-check list is not a canonical GeoIntel data envelope")
+with open(detection_run_path, "r", encoding="utf-8") as handle:
+    detection_run_payload = json.load(handle)
+if "data" not in detection_run_payload:
+    raise SystemExit("Detection run detail is not a canonical GeoIntel data envelope")
+detection_run = detection_run_payload["data"]
+run_result = detection_run.get("result_json") or {}
+items = payload["data"].get("items") or []
+quality_check = next((item for item in items if str(item.get("id")) == quality_check_id), None)
+if quality_check is None:
+    raise SystemExit(f"Quality check not found in project list: {quality_check_id}")
+metrics = {
+    metric.get("metric_key"): metric.get("metric_value")
+    for metric in quality_check.get("metrics", [])
+    if metric.get("metric_key")
+}
+findings = quality_check.get("findings_json") or {}
+coverage = findings.get("coverage") or {}
+diagnostics = findings.get("box_to_footprint_diagnostics") or {}
+reference_raw_count = coverage.get("reference_raw_count")
+reference_evaluated_count = coverage.get("reference_evaluated_count")
+reference_coverage_ratio = None
+if isinstance(reference_raw_count, int) and reference_raw_count > 0 and isinstance(reference_evaluated_count, int):
+    reference_coverage_ratio = reference_evaluated_count / reference_raw_count
+summary = {
+    "model_request": model_request,
+    "model_asset_id": selected_model_asset_id,
+    "tile_size": int(tile_size),
+    "tile_overlap": int(tile_overlap),
+    "threshold": float(threshold),
+    "project_id": project_id,
+    "area_id": area_id or None,
+    "raster_dataset_id": raster_dataset_id,
+    "reference_dataset_id": reference_dataset_id,
+    "manifest_path": manifest_path,
+    "analysis_run_id": analysis_run_id,
+    "quality_check_id": quality_check_id,
+    "detection_count": int(detection_count),
+    "raw_detection_count": run_result.get("raw_detection_count", int(detection_count)),
+    "suppressed_detection_count": run_result.get("suppressed_detection_count", 0),
+    "duplicate_iou_threshold": run_result.get("duplicate_iou_threshold"),
+    "quality_status": quality_check.get("status"),
+    "quality_score": quality_check.get("score"),
+    "precision": metrics.get("precision"),
+    "recall": metrics.get("recall"),
+    "f1_score": metrics.get("f1_score", metrics.get("f1")),
+    "mean_iou": metrics.get("mean_iou"),
+    "matches": findings.get("matches"),
+    "false_positives": findings.get("false_positives"),
+    "false_negatives": findings.get("false_negatives"),
+    "coverage_applied": coverage.get("applied", False),
+    "coverage_mode": coverage.get("mode"),
+    "coverage_tile_count": coverage.get("tile_count", 0),
+    "coverage_source_crs_values": coverage.get("source_crs_values") or [],
+    "candidate_raw_count": coverage.get("candidate_raw_count"),
+    "candidate_evaluated_count": coverage.get("candidate_evaluated_count"),
+    "candidate_excluded_outside_count": coverage.get("candidate_excluded_outside_count"),
+    "candidate_clipped_boundary_count": coverage.get("candidate_clipped_boundary_count"),
+    "reference_raw_count": reference_raw_count,
+    "reference_evaluated_count": reference_evaluated_count,
+    "reference_excluded_outside_count": coverage.get("reference_excluded_outside_count"),
+    "reference_clipped_boundary_count": coverage.get("reference_clipped_boundary_count"),
+    "reference_coverage_ratio": reference_coverage_ratio,
+    "diagnostic_only": diagnostics.get("diagnostic_only"),
+    "diagnostic_method": diagnostics.get("diagnostic_method"),
+    "strict_matches": diagnostics.get("strict_matches"),
+    "envelope_matches": diagnostics.get("envelope_matches"),
+    "possible_box_to_footprint_mismatch_count": diagnostics.get("possible_box_to_footprint_mismatch_count"),
+    "envelope_precision": diagnostics.get("envelope_precision"),
+    "envelope_recall": diagnostics.get("envelope_recall"),
+    "envelope_f1_score": diagnostics.get("envelope_f1_score"),
+    "export_id": export_id,
+    "run_log": run_log,
+}
+with open(output_path, "w", encoding="utf-8") as handle:
+    json.dump(summary, handle, indent=2, sort_keys=True)
+print(
+    "model={model} tile={tile} overlap={overlap} threshold={threshold} detections={detections} raw={raw} suppressed={suppressed} "
+    "score={score} precision={precision} recall={recall} f1={f1} matches={matches} fp={fp} fn={fn} "
+    "coverage={coverage} diagnostic_gap={diagnostic_gap}".format(
+        model=summary["model_asset_id"],
+        tile=summary["tile_size"],
+        overlap=summary["tile_overlap"],
+        threshold=summary["threshold"],
+        detections=summary["detection_count"],
+        raw=summary["raw_detection_count"],
+        suppressed=summary["suppressed_detection_count"],
+        score=summary["quality_score"],
+        precision=summary["precision"],
+        recall=summary["recall"],
+        f1=summary["f1_score"],
+        matches=summary["matches"],
+        fp=summary["false_positives"],
+        fn=summary["false_negatives"],
+        coverage=summary["reference_coverage_ratio"],
+        diagnostic_gap=summary["possible_box_to_footprint_mismatch_count"],
+    )
+)
+PY
+done < "${matrix_manifest}"
+
+"${PYTHON_BIN}" - "${QUALITY_OUTPUT_DIR}" "${BASE_URL}" "${matrix_manifest}" <<'PY'
+import glob
+import json
+import os
+import sys
+from datetime import datetime, timezone
+
+output_dir, base_url, manifest_path = sys.argv[1:4]
+items = []
+for path in sorted(glob.glob(os.path.join(output_dir, "*_summary.json"))):
+    if path.endswith("quality_matrix_summary.json"):
+        continue
+    with open(path, "r", encoding="utf-8") as handle:
+        items.append(json.load(handle))
+
+if not items:
+    raise SystemExit("No detection quality matrix summaries were produced")
+
+
+def ranked_with(metric: str):
+    return [item for item in items if item.get(metric) is not None]
+
+
+best_by_score = max(ranked_with("quality_score"), key=lambda item: item["quality_score"], default=None)
+best_by_recall = max(ranked_with("recall"), key=lambda item: item["recall"], default=None)
+best_by_precision = max(ranked_with("precision"), key=lambda item: item["precision"], default=None)
+summary = {
+    "generated_at": datetime.now(timezone.utc).isoformat(),
+    "base_url": base_url,
+    "request_manifest_path": manifest_path,
+    "run_count": len(items),
+    "best_by_score": best_by_score,
+    "best_by_recall": best_by_recall,
+    "best_by_precision": best_by_precision,
+    "items": items,
+}
+summary_path = os.path.join(output_dir, "quality_matrix_summary.json")
+with open(summary_path, "w", encoding="utf-8") as handle:
+    json.dump(summary, handle, indent=2, sort_keys=True)
+
+print("")
+print("Detection quality matrix summary")
+print("model\ttile\toverlap\tthreshold\tdetections\traw\tsuppressed\tscore\tprecision\trecall\tf1\tmatches\tfp\tfn\tcoverage\tdiagnostic_gap")
+for item in items:
+    print(
+        "{model_asset_id}\t{tile_size}\t{tile_overlap}\t{threshold:.2f}\t{detection_count}\t{raw_detection_count}\t{suppressed_detection_count}\t{quality_score}\t{precision}\t{recall}\t{f1_score}\t{matches}\t{false_positives}\t{false_negatives}\t{reference_coverage_ratio}\t{possible_box_to_footprint_mismatch_count}".format(
+            **item
+        )
+    )
+print("")
+print(f"Summary: {summary_path}")
+if best_by_score:
+    print(
+        "best_by_score model={model_asset_id} tile={tile_size} overlap={tile_overlap} threshold={threshold:.2f} score={quality_score} f1={f1_score}".format(
+            **best_by_score
+        )
+    )
+if best_by_recall:
+    print(
+        "best_by_recall model={model_asset_id} tile={tile_size} overlap={tile_overlap} threshold={threshold:.2f} recall={recall} detections={detection_count}".format(
+            **best_by_recall
+        )
+    )
+if best_by_precision:
+    print(
+        "best_by_precision model={model_asset_id} tile={tile_size} overlap={tile_overlap} threshold={threshold:.2f} precision={precision} detections={detection_count}".format(
+            **best_by_precision
+        )
+    )
+PY