auto-iter 20260513-2231: GX019817 RoPE skip, 4 PLY done ready for stage06

2026-05-13 23:02:31 +00:00
parent 091ffeb2f6
commit 38dbcfd46f
14 changed files with 2083 additions and 0 deletions
--- a/scripts/dvl_optical.py
+++ b/scripts/dvl_optical.py
@@ -0,0 +1,140 @@
+#!/usr/bin/env python3
+"""Optical DVL — mean optical flow per frame → 2D ground velocity integration.
+
+Assumes downward-looking camera at constant altitude above ground.
+Convert pixel flow to metric using altitude / focal_length.
+
+Pipeline:
+  1. Dense Farneback flow between consecutive frames
+  2. Median flow vector (px) → robust against outliers
+  3. v_m = flow_px * altitude_m / focal_px  (instant velocity in cam plane)
+  4. Integrate → trajectory (cam-frame XY)
+  5. Optional: apply IMU heading rotation per frame for body-frame correction
+
+Usage:
+  python3 dvl_optical.py --frames-dir <dir> --altitude 1.5 --fps 1.0 \
+    --start-iso 2026-05-05T08:33:41 --label GX039839 \
+    --out /tmp/dvl.csv --plot /tmp/dvl.png [--ref-csv /tmp/GX039839_camera.csv]
+"""
+import argparse, csv, math, sys
+from pathlib import Path
+from datetime import datetime
+import numpy as np
+import cv2
+
+def main():
+    ap = argparse.ArgumentParser()
+    ap.add_argument('--frames-dir', required=True)
+    ap.add_argument('--altitude', type=float, default=1.5, help='Camera height above bottom (m)')
+    ap.add_argument('--fov-deg', type=float, default=122.0, help='GoPro horizontal FOV')
+    ap.add_argument('--fps', type=float, default=1.0)
+    ap.add_argument('--start-iso', default='2026-05-05T00:00:00')
+    ap.add_argument('--label', default='segment')
+    ap.add_argument('--out', required=True)
+    ap.add_argument('--plot', default=None)
+    ap.add_argument('--ref-csv', default=None)
+    ap.add_argument('--method', choices=['farneback','lk'], default='farneback')
+    args = ap.parse_args()
+    
+    frames = sorted(Path(args.frames_dir).glob('frame_*.jpg'))
+    print(f'[dvl] {len(frames)} frames', flush=True)
+    
+    W, H = 518, 294
+    f = (W/2) / math.tan(math.radians(args.fov_deg/2))
+    # scale factor : 1 px flow at altitude_m = (altitude_m / focal_px) meters
+    px_to_m = args.altitude / f
+    print(f'[dvl] focal_px={f:.1f} altitude={args.altitude}m -> px_to_m={px_to_m:.5f}', flush=True)
+    
+    t0 = datetime.fromisoformat(args.start_iso).timestamp()
+    rows = []
+    rows.append({'frame_idx': 0, 'ts_s': t0, 'flow_x_px': 0, 'flow_y_px': 0, 'speed_mps': 0, 'x_m': 0, 'y_m': 0})
+    
+    prev = cv2.imread(str(frames[0]), cv2.IMREAD_GRAYSCALE)
+    x_cum, y_cum = 0.0, 0.0
+    
+    for i in range(1, len(frames)):
+        curr = cv2.imread(str(frames[i]), cv2.IMREAD_GRAYSCALE)
+        if curr is None: continue
+        
+        if args.method == 'farneback':
+            flow = cv2.calcOpticalFlowFarneback(prev, curr, None, 0.5, 3, 21, 3, 5, 1.2, 0)
+            fx = np.median(flow[..., 0])
+            fy = np.median(flow[..., 1])
+        else:  # lk on grid
+            h, w = prev.shape
+            pts = np.array([[x, y] for y in range(20, h-20, 30) for x in range(20, w-20, 30)], dtype=np.float32).reshape(-1, 1, 2)
+            curr_pts, status, err = cv2.calcOpticalFlowPyrLK(prev, curr, pts, None, winSize=(21,21))
+            good = status.flatten() == 1
+            if good.sum() < 10:
+                fx = fy = 0
+            else:
+                d = (curr_pts - pts)[good].reshape(-1, 2)
+                fx = np.median(d[:, 0]); fy = np.median(d[:, 1])
+        
+        # Convert px/frame -> m/frame
+        dx_m = fx * px_to_m
+        dy_m = fy * px_to_m
+        # AUV motion is OPPOSITE to optical flow direction (camera moves opposite to apparent ground motion)
+        # If ground appears to move +x in image, AUV moves -x in world
+        x_cum -= dx_m
+        y_cum -= dy_m
+        speed_mps = math.sqrt(dx_m**2 + dy_m**2) * args.fps
+        
+        rows.append({'frame_idx': i, 'ts_s': t0 + i/args.fps, 'flow_x_px': float(fx), 'flow_y_px': float(fy),
+                     'speed_mps': speed_mps, 'x_m': x_cum, 'y_m': y_cum})
+        prev = curr
+        
+        if i % 100 == 0:
+            print(f'[dvl] {i}/{len(frames)} flow=({fx:.2f},{fy:.2f}) speed={speed_mps:.3f}m/s pos=({x_cum:.2f},{y_cum:.2f})', flush=True)
+    
+    print(f'[dvl] done. Final position: ({x_cum:.2f}, {y_cum:.2f}) m', flush=True)
+    
+    with open(args.out, 'w', newline='') as f:
+        w = csv.DictWriter(f, fieldnames=list(rows[0].keys()))
+        w.writeheader(); w.writerows(rows)
+    print(f'[out] {args.out}', flush=True)
+    
+    if args.plot:
+        import matplotlib
+        matplotlib.use('Agg')
+        import matplotlib.pyplot as plt
+        fig, axes = plt.subplots(2, 2, figsize=(14, 12))
+        ax_xy, ax_speed, ax_flow, ax_cmp = axes[0,0], axes[0,1], axes[1,0], axes[1,1]
+        x = [r['x_m'] for r in rows]; y = [r['y_m'] for r in rows]
+        ax_xy.plot(x, y, '-b', linewidth=1.2)
+        ax_xy.plot(x[0], y[0], 'go', markersize=10, label='start')
+        ax_xy.plot(x[-1], y[-1], 'r^', markersize=10, label='end')
+        ax_xy.set_xlabel('X (m)'); ax_xy.set_ylabel('Y (m)'); ax_xy.set_title(f'DVL trajectory (altitude={args.altitude}m)')
+        ax_xy.set_aspect('equal'); ax_xy.legend(); ax_xy.grid(True, alpha=0.3)
+        
+        speeds = [r['speed_mps'] for r in rows]
+        ax_speed.plot(range(len(rows)), speeds, '-r', linewidth=0.8)
+        ax_speed.set_xlabel('Frame'); ax_speed.set_ylabel('Speed (m/s)'); ax_speed.set_title('Speed over time'); ax_speed.grid(True, alpha=0.3)
+        
+        fx_arr = [r['flow_x_px'] for r in rows]; fy_arr = [r['flow_y_px'] for r in rows]
+        ax_flow.plot(fx_arr, label='flow_x px', alpha=0.6)
+        ax_flow.plot(fy_arr, label='flow_y px', alpha=0.6)
+        ax_flow.set_xlabel('Frame'); ax_flow.set_ylabel('Median flow (px)'); ax_flow.set_title('Median optical flow'); ax_flow.legend(); ax_flow.grid(True, alpha=0.3)
+        
+        # comparison with reference
+        if args.ref_csv:
+            try:
+                with open(args.ref_csv) as ff:
+                    refrows = [r for r in csv.DictReader(ff) if r.get('segment','')==args.label or r.get('label','')==args.label]
+                rx = [float(r['x']) for r in refrows]
+                ry = [float(r['y']) for r in refrows]
+                ax_cmp.plot(x, y, '-b', linewidth=1.2, label='DVL optical', alpha=0.7)
+                ax_cmp.plot(rx, ry, '-r', linewidth=1.2, label='lingbot', alpha=0.7)
+                ax_cmp.plot(x[0], y[0], 'go', markersize=8)
+                ax_cmp.set_xlabel('X (m)'); ax_cmp.set_ylabel('Y (m)'); ax_cmp.set_title('DVL vs Lingbot (same scale, x/y)'); ax_cmp.set_aspect('equal')
+                ax_cmp.legend(); ax_cmp.grid(True, alpha=0.3)
+            except Exception as e:
+                print(f'[plot] ref fail: {e}', flush=True)
+        else:
+            ax_cmp.set_title('(no reference)')
+        
+        plt.suptitle(f'Optical DVL — {args.label} ({args.method.upper()} flow, altitude {args.altitude}m)')
+        plt.tight_layout()
+        plt.savefig(args.plot, dpi=130, bbox_inches='tight')
+
+if __name__ == '__main__': main()