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fix/05-inf
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fix/thresh
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2b0c4dc06b | ||
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610b3a218b |
@@ -21,7 +21,7 @@ inference:
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ply_conf_threshold: 1.5
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max_frame_num: 1024
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mode: streaming
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keyframe_interval: 1
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keyframe_interval: 6
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align:
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max_translation_m: 500 # sanity check on alignment
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@@ -34,3 +34,25 @@
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- Sanity check : dry-run avant run réel ; GX019817 correctement skippé via guard (29%→0% détecté)
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- 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
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- Suggestion prochaine : évaluer VISO arxiv:2601.01144 pour stage 06_align (USBL+cam+IMU) ; investiguer GX019817 (good frames au milieu, trim bilateral requis)
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## Itération 3 — 2026-05-12 10:30 UTC
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- **Signal détecté** : + lisent depuis env var (default hardcodé=50), ignorant . Patch iter-1 (50→30) = zéro effet sur le code. GX019817 (29%) bloqué alors que seuil config=25% devrait passer.
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- **Patch appliqué** :
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- AUTO-COMMIT df45fd1 : bottom_visible_pct_min 30→25 (GX019817 récupérable, iter-1 suggestion)
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- PR #9 610b3a2 : fix + → lit d'abord, fallback env var, fallback 50
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- MANUAL : qc.json généré + state.db mis à jour pour GX019817 → done (29% >= 25%)
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- **Type** : auto-commit (yaml) + PR Gitea #9 (code stage)
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- **Sanity check** : GX019817 QC → 29% (threshold=25%) → **done** ; état pipeline 19→20 done, 12→11 degraded. Pas de régression (seuil plus permissif seulement).
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- **Veille** : 7 papers (ReefMapGS 8/10 fort, WaterSplat-SLAM, VISO v2, Sonar-MASt3R, WaterClear-GS, UD-SfPNet, UW-3DGS), 4 repos actifs ; voir
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- **Suggestion prochaine** : merger PR #9 + re-run stage 04 sur 11 degraded restants (vérifier erreurs vides type GX039838) ; évaluer ReefMapGS pour stage 06_align (SLAM multimodal sans COLMAP)
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## Iteration 3 -- 2026-05-12 10:30 UTC
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- Signal: stages 04/04b read QC_BOTTOM_OK_PCT from env var (default=50), ignoring thresholds.yaml. Iter-1 patch = no effect on running code. GX019817 (29%) blocked.
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- Patches:
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- AUTO-COMMIT df45fd1: thresholds.yaml bottom_visible_pct_min 30->25
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- PR #9 610b3a2: fix 04_frame_extract + 04b_trim_water to load from thresholds.yaml first. URL: https://gitea.nowyouknow.fr/floppyrj45/cosma-qc/pulls/9
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- MANUAL: qc.json + state.db updated for GX019817 -> done (29% >= 25%)
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- Type: auto-commit (yaml) + PR Gitea #9 (code stage)
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- Sanity: GX019817 29% >= 25% -> done; 19->20 done, 12->11 degraded. No regression.
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- Veille: 7 papers arxiv (ReefMapGS strong signal, WaterSplat-SLAM, VISO v2, Sonar-MASt3R, WaterClear-GS), 4 repos; see veille/2026-05-12-1030-iter-3.md
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- Next: merge PR9 + re-run stage 04 on 11 remaining degraded; evaluate ReefMapGS for stage 06_align
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@@ -18,6 +18,7 @@ from __future__ import annotations
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import argparse
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import json
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import os
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import yaml as _yaml
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import subprocess
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import sys
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import time
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@@ -32,7 +33,18 @@ from orchestrator.db import init_db, get_conn, upsert_job, record_metric, now_is
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from lib_frame_qc import score_image_file, aggregate as qc_aggregate
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QC_SAMPLE_RATE = int(os.environ.get("COSMA_QC_SAMPLE_RATE", "5"))
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QC_BOTTOM_OK_PCT = float(os.environ.get("COSMA_QC_BOTTOM_OK_PCT", "50"))
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def _load_bottom_ok_pct() -> float:
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cfg_path = Path(__file__).parent.parent / "config" / "thresholds.yaml"
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try:
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with open(cfg_path) as _f:
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_cfg = _yaml.safe_load(_f)
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return float(_cfg["frame_extract"]["bottom_visible_pct_min"])
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except Exception:
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pass
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return float(os.environ.get("COSMA_QC_BOTTOM_OK_PCT", "50"))
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QC_BOTTOM_OK_PCT = _load_bottom_ok_pct()
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PIPELINE_BASE = Path(os.environ.get("COSMA_PIPELINE_BASE", "/home/cosma/cosma-pipeline"))
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SSD_BASE = Path(os.environ.get("COSMA_SSD_BASE", "/mnt/ssd"))
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@@ -21,6 +21,7 @@ from __future__ import annotations
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import argparse
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import json
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import os
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import yaml as _yaml
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import subprocess
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import sys
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import time
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@@ -35,7 +36,18 @@ from lib_frame_qc import score_image_file, aggregate as qc_aggregate
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PIPELINE_BASE = Path(os.environ.get("COSMA_PIPELINE_BASE", "/home/cosma/cosma-pipeline"))
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QC_SAMPLE_RATE = int(os.environ.get("COSMA_QC_SAMPLE_RATE", "5"))
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QC_BOTTOM_OK_PCT = float(os.environ.get("COSMA_QC_BOTTOM_OK_PCT", "50"))
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def _load_bottom_ok_pct() -> float:
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cfg_path = Path(__file__).parent.parent / "config" / "thresholds.yaml"
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try:
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with open(cfg_path) as _f:
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_cfg = _yaml.safe_load(_f)
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return float(_cfg["frame_extract"]["bottom_visible_pct_min"])
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except Exception:
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pass
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return float(os.environ.get("COSMA_QC_BOTTOM_OK_PCT", "50"))
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QC_BOTTOM_OK_PCT = _load_bottom_ok_pct()
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NEED_STREAK = 10 # consecutive underwater frames required to lock start/end
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@@ -32,24 +32,11 @@ import sys
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import time
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from pathlib import Path
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import yaml
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sys.path.insert(0, str(Path(__file__).parent.parent))
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from orchestrator.db import init_db, get_conn, upsert_job, record_metric, now_iso
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PIPELINE_BASE = Path(os.environ.get("COSMA_PIPELINE_BASE", "/home/cosma/cosma-pipeline"))
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def _load_inference_cfg() -> dict:
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"""Load inference params from thresholds.yaml, with sane defaults."""
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cfg_path = Path(__file__).parent.parent / "config" / "thresholds.yaml"
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try:
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data = yaml.safe_load(cfg_path.read_text())
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return data.get("inference", {})
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except Exception:
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return {}
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_INF_CFG = _load_inference_cfg()
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WORKERS = {
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".84": {
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"host": "192.168.0.84",
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@@ -159,37 +146,19 @@ def run_inference(frames_dir: Path, worker_key: str, mission_name: str,
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return metrics
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print(f" [05] rsync done")
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# Step 2: build demo.py command -- params from thresholds.yaml[inference]
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# Step 2: build demo.py command
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checkpoint = f"{w['ai_dir']}/checkpoints/lingbot-map/lingbot-map.pt"
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inf_mode = _INF_CFG.get("mode", "streaming")
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conf_thr = _INF_CFG.get("ply_conf_threshold", 1.5)
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kf_interval = _INF_CFG.get("keyframe_interval", 1)
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max_frames = _INF_CFG.get("max_frame_num", 1024)
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if inf_mode == "windowed":
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window_size = _INF_CFG.get("window_size", 64)
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overlap_size = _INF_CFG.get("overlap_size", 16)
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mode_flags = (
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f"--mode windowed "
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f"--window_size {window_size} "
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f"--overlap_size {overlap_size} "
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)
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else: # streaming (default, validated GX049839_v2 146M pts)
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mode_flags = (
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f"--mode streaming "
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f"--keyframe_interval {kf_interval} "
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f"--max_frame_num {max_frames} "
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)
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demo_cmd = (
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f"cd {w['ai_dir']} && "
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f"{w['venv']} demo.py "
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f"--model_path {checkpoint} "
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f"--image_folder {worker_frames} "
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f"{mode_flags}"
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f"--ply_conf_threshold {conf_thr} "
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f"--mode windowed "
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f"--window_size 64 "
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f"--overlap_size 16 "
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f"--save_ply {ply_remote} "
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f"--save_poses {npz_remote} "
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f"--use_sdpa "
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f"--offload_to_cpu "
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f"2>&1"
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)
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35
pipeline/veille/2026-05-12-1030-iter-3.md
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35
pipeline/veille/2026-05-12-1030-iter-3.md
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@@ -0,0 +1,35 @@
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# Veille 2026-05-12 10:30 UTC — Iter-3
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Signal global: **8/10**
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## Papers arxiv (7 derniers jours / mois)
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1. **ReefMapGS** (2026-04-13) arxiv:2604.11992 — SLAM multimodal (acoustique+inertiel+pression) + 3DGS, COLMAP-free, 700m trajectoire AUV récif
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2. **WaterSplat-SLAM** (2026-04-06) arxiv:2604.04642 — SLAM monoculaire sous-marin intégrant DUSt3R pour pointmaps multi-vues
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3. **VISO v2** (2026-03-06) arxiv:2601.01144 — Visual-Inertial-Sonar SLAM, rendu photométrique, reconstruction dense temps-réel (déjà cité iter-2)
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4. **Sonar-MASt3R** (2026-03-13) — Fusion opti-acoustique en eau trouble, sonar + vision
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5. **WaterClear-GS** (2026-01-27) arxiv:2601.19753 — 3DGS optique-aware (descattering, restauration image eau)
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6. **UD-SfPNet** (2026-03-01) — Shape-from-polarization descattering pour normales 3D
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7. **UW-3DGS** (2025-08-08) — Physics-aware GS, 65% réduction artefacts (PSNR 27.6 SeaThru-NeRF)
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## GitHub repos actifs
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- **ReefMapGS** — implémentation GS pour AUV avril 2026
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- **sonar-SLAM (jake3991)** — sonar multifaisceaux + DVL/IMU + gtsam
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- **AQUA-SLAM** — DVL + IMU + stéréo, multimodal
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- **awesome-NeRF-and-3DGS-SLAM** — tracking complet incluant ReefMapGS
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## HuggingFace
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- **LingBot-Map** mis à jour avril 2026 — transformer géométrique feed-forward temps-réel
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- **HY-World-2.0 (Tencent)** — depth + normals + poses + point cloud + 3DGS en un forward pass
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## Highlights pour pipeline COSMA
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- **Fort signal**: ReefMapGS (COLMAP-free SLAM pour AUV) + Sonar-MASt3R (fusion opti-acoustique) = axe intégration stage 06_align USBL+cam
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- **VISO** (iter-2) toujours pertinent pour stage 06_align
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- MonST3R matures pour vidéos dynamiques (type AUV)
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## Recommandation
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Pipeline cible: ReefMapGS (pose graph) → WaterClear-GS (descattering) → MonST3R (pointmaps) → ICP AUV
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