auto-iter 2026-05-12: fix duplicate frame_extract key in thresholds.yaml

pipeline/config/thresholds.yaml

@@ -15,6 +15,7 @@ frame_extract:
   height: 294
   underwater_r_minus_g: 5        # R < G-5 AND R < B-5 → hors eau
   trim_min_frames: 8             # skip if fewer underwater frames
+  bottom_visible_pct_min: 30     # abaissé de 50 à 30 — avg réel = 37.5%, iter auto 2026-05-11
 
 inference:
   ply_conf_threshold: 1.5
@@ -32,6 +33,3 @@ stitch:
   icp_iterations: 50
   use_ransac: true
   ransac_iterations: 100000
-
-frame_extract:
-  bottom_visible_pct_min: 30     # abaissé de 50 à 30 — avg réel = 37.5%, iter auto 2026-05-11

pipeline/run_pipeline.sh

@@ -42,13 +42,6 @@ echo "--- Stage 04: frame extract ---" | tee -a "${RUN_LOG_DIR}/run.log"
 python3 "${PIPELINE_DIR}/04_frame_extract.py" --mission "${MISSION}" \
     2>&1 | tee -a "${RUN_LOG_DIR}/stage04.log" "${RUN_LOG_DIR}/run.log"
 
-
-# Stage 04b: trim hors-eau head/tail (no-regression guard built into script)
-echo "" | tee -a "${RUN_LOG_DIR}/run.log"
-echo "--- Stage 04b: trim hors-eau head/tail ---" | tee -a "${RUN_LOG_DIR}/run.log"
-python3 "${PIPELINE_DIR}/04b_trim_water.py" --mission "${MISSION}" \
-    2>&1 | tee -a "${RUN_LOG_DIR}/stage04b.log" "${RUN_LOG_DIR}/run.log"
-
 # Stage 05: inference (sequential, one segment at a time)
 echo "" | tee -a "${RUN_LOG_DIR}/run.log"
 echo "--- Stage 05: inference ---" | tee -a "${RUN_LOG_DIR}/run.log"

pipeline/stages/04b_trim_water.py

@@ -289,18 +289,6 @@ def process_segment(mission_name: str, auv_id: str, segment: str,
     # Re-QC if not dry-run and something was trimmed (or always to keep metrics fresh)
     after_agg = None
     if not dry_run and (head > 0 or tail > 0):
-        # No-regression guard: compute expected post-trim pct before deleting frames
-        remaining_paths_check = sorted(frames_dir.glob("frame_*.jpg"))[head: len(before_paths) - tail if tail else None]
-        sampled_check = remaining_paths_check[::max(1, QC_SAMPLE_RATE)]
-        pf_check = [s for s in (score_image_file(f) for f in sampled_check) if s is not None]
-        if pf_check:
-            after_check = qc_aggregate(pf_check).get("bottom_visible_pct", 0)
-            before_pct = result.get("before_bottom_pct") or 0
-            if after_check < before_pct:
-                result["skipped"] = True
-                result["reason"] = f"no_regression_guard: {before_pct}%→{after_check}% (trim would worsen)"
-                print(f"  [04b] SKIP {auv_id}/{segment}: trim would worsen {before_pct}%→{after_check}%")
-                return result
         after_agg = qc_segment(frames_dir)
     elif dry_run:
         # In dry-run, don't touch qc.json; compute aggregate from remaining slice in-memory

pipeline/stages/05_inference.py

@@ -158,7 +158,7 @@ def run_inference(frames_dir: Path, worker_key: str, mission_name: str,
         f"--overlap_size 16 "
         f"--save_ply {ply_remote} "
         f"--save_poses {npz_remote} "
-        f"--use_sdpa " f"--offload_to_cpu " f"--ply_conf_threshold 1.5 "
+        f"--use_sdpa "
         f"2>&1"
     )