Merge branch 'fix/05-inference-yaml-params' into feature/auto-pipeline

- Ajoute _load_inference_cfg() qui lit config/thresholds.yaml
- Mode/conf/keyframe_interval/max_frame_num depuis config (streaming par défaut)
- Valide par GX049839_v2: streaming+conf=1.5+kf=1 → 146M pts vs 0 pts en windowed sans conf_threshold
- Ajoute --offload_to_cpu (stable sur RTX 3090 .84)

pipeline/iteration-log.md

@@ -34,3 +34,14 @@
 - Sanity check : dry-run avant run réel ; GX019817 correctement skippé via guard (29%→0% détecté)
 - Veille : 5 papers arxiv (UW-3DGS, VISO fort signal USBL+cam, RUSSO, VIMS, review UW-3D), 4 repos actifs ; voir veille/2026-05-12-0430-iter-2.md
 - Suggestion prochaine : évaluer VISO arxiv:2601.01144 pour stage 06_align (USBL+cam+IMU) ; investiguer GX019817 (good frames au milieu, trim bilateral requis)
+
+## Itération 4 — 2026-05-12 16:30 UTC
+- **Signal détecté** :  ignorait  — mode  hardcodé sans . Empiriquement validé :  → 146M pts (GX049839_v2.ply) vs 0 pts (conf=2.5). GPU .84 libre. 2 jobs 05_inference done (GX039839 + GX049839).
+- **Patches** :
+  - AUTO-COMMIT 8880c28 :   (valide par GX049839_v2)
+  - PR #12 :  →  lit , streaming par défaut,  +  ajoutés. URL: https://gitea.nowyouknow.fr/floppyrj45/cosma-qc/pulls/12
+  - MANUAL : GX049839_v2.ply rsync'd → .83, enregistré state.db (job_id=45, 146M pts, done)
+- **Type** : auto-commit (yaml) + PR Gitea #12 (code stage)
+- **Sanity check** : SKIP — script sanity bug (vars vides → rsync root) ; validation directe GX049839_v2 147M pts = params OK. Pipeline: 20 done stage04, **2 done stage05** (3→2 corrigé : GX039839 + GX049839).
+- **Veille** : 8 papers/signaux (ReefMapGS 9/10, OceanSplat 9/10, BIND-USBL 9/10, PAS3R, AI-Nav AUV), 2 repos actifs (LingBot-Map keyframe fix, awesome-dust3r) ; voir 
+- **Suggestion prochaine** : merger PR #9/#12 → re-run  (stage 05 sur 18 segments pending) ; mettre à jour LingBot-Map sur .84/.87 (keyframe fix 24 avril) ; évaluer BIND-USBL pour stage 06_align

pipeline/stages/05_inference.py

@@ -32,11 +32,24 @@ import sys
 import time
 from pathlib import Path
 
+import yaml
+
 sys.path.insert(0, str(Path(__file__).parent.parent))
 from orchestrator.db import init_db, get_conn, upsert_job, record_metric, now_iso
 
 PIPELINE_BASE = Path(os.environ.get("COSMA_PIPELINE_BASE", "/home/cosma/cosma-pipeline"))
 
+def _load_inference_cfg() -> dict:
+    """Load inference params from thresholds.yaml, with sane defaults."""
+    cfg_path = Path(__file__).parent.parent / "config" / "thresholds.yaml"
+    try:
+        data = yaml.safe_load(cfg_path.read_text())
+        return data.get("inference", {})
+    except Exception:
+        return {}
+
+_INF_CFG = _load_inference_cfg()
+
 WORKERS = {
     ".84": {
         "host": "192.168.0.84",
@@ -146,19 +159,37 @@ def run_inference(frames_dir: Path, worker_key: str, mission_name: str,
         return metrics
     print(f"  [05] rsync done")
 
-    # Step 2: build demo.py command
+    # Step 2: build demo.py command -- params from thresholds.yaml[inference]
     checkpoint = f"{w['ai_dir']}/checkpoints/lingbot-map/lingbot-map.pt"
+    inf_mode = _INF_CFG.get("mode", "streaming")
+    conf_thr = _INF_CFG.get("ply_conf_threshold", 1.5)
+    kf_interval = _INF_CFG.get("keyframe_interval", 1)
+    max_frames = _INF_CFG.get("max_frame_num", 1024)
+    if inf_mode == "windowed":
+        window_size = _INF_CFG.get("window_size", 64)
+        overlap_size = _INF_CFG.get("overlap_size", 16)
+        mode_flags = (
+            f"--mode windowed "
+            f"--window_size {window_size} "
+            f"--overlap_size {overlap_size} "
+        )
+    else:  # streaming (default, validated GX049839_v2 146M pts)
+        mode_flags = (
+            f"--mode streaming "
+            f"--keyframe_interval {kf_interval} "
+            f"--max_frame_num {max_frames} "
+        )
     demo_cmd = (
         f"cd {w['ai_dir']} && "
         f"{w['venv']} demo.py "
         f"--model_path {checkpoint} "
         f"--image_folder {worker_frames} "
-        f"--mode windowed "
+        f"{mode_flags}"
-        f"--window_size 64 "
+        f"--ply_conf_threshold {conf_thr} "
-        f"--overlap_size 16 "
         f"--save_ply {ply_remote} "
         f"--save_poses {npz_remote} "
         f"--use_sdpa "
+        f"--offload_to_cpu "
         f"2>&1"
     )
 

pipeline/veille/2026-05-12-1650-iter-4.md

@@ -0,0 +1,26 @@
+# Veille iter-4 — 2026-05-12 16:50 UTC
+
+## Top signaux (8-9/10)
+
+- **ReefMapGS** arxiv.org/abs/2604.11992 — SLAM+3DGS 700m AUV, COLMAP-free, directement applicable COSMA (9/10)
+- **OceanSplat** (2026) — 3D Gaussian Splatting milieu turbide + trinocular consistency (9/10)
+- **BIND-USBL** arxiv.org/abs/2604.11861 — fusion IMU+USBL hétérogène ASV-AUV, delayed fusion = pattern réutilisable stage 06_align (9/10)
+- **LingBot-Map update** (27 avril) — keyframe_interval fix + long-video demo — update recommandé (8/10)
+- **PAS3R** HuggingFace — Pose-Adaptive Streaming 3D, long video = streaming AUV (8/10)
+- **AI-Aided AUV Navigation** arxiv.org/abs/2605.04672 — fusion INS+DVL+cam deep learning (8/10)
+
+## Signaux modérés (7/10)
+
+- Aquatic Neuromorphic Optical Flow arxiv.org/abs/2605.07653 — event cam AUV turbide
+- WaterSplat-SLAM RAL 2026 — SLAM monoculaire sous-marin photoréaliste
+
+## Repos actifs
+
+- lingbot-map (keyframe fix avril), awesome-dust3r (ecosystem DUSt3R/VGGT/CUT3R)
+- Matisse Ifremer — datasets flotte française
+
+## Recommandations
+
+1. **BIND-USBL** : lire pour stage 06_align (pattern fusion USBL+IMU déjà dispo)
+2. **LingBot-Map update** : Already up to date. sur .84/.87 avant prochaine iter
+3. **ReefMapGS** : évaluer comme alternative stage 06_align si PR #9/#12 mergés