""" 单文件:参考深度反投影到 ECEF → 投影到 query 相机 → 并排可视化对应点。 运行: python demo.py """ from pathlib import Path import cv2 import numpy as np import pyproj from scipy.spatial.transform import Rotation as R # 与 poses 里帧名一致(如 888.jpg) REF_STEM = "888" QUERY_STEM = "1047" NUM_SAMPLES = 100 # 内参 fx, fy, cx, cy — 需与渲染一致 FX, FY, CX, CY = 1931.7, 1931.7, 800.0, 600.0 W, H = 1600, 1200 ROOT = Path(__file__).resolve().parent ASSETS = ROOT / "assets" OUT = ROOT / "outputs" def wgs84_to_ecef(lon, lat, h): t = pyproj.Transformer.from_crs( "EPSG:4326", {"proj": "geocent", "ellps": "WGS84", "datum": "WGS84"}, always_xy=True, ) x, y, z = t.transform(lon, lat, h, radians=False) return np.array([x, y, z], np.float64) def enu_to_ecef_rot(lon, lat): lat_r, lon_r = np.radians(lat), np.radians(lon) up = np.array( [ np.cos(lon_r) * np.cos(lat_r), np.sin(lon_r) * np.cos(lat_r), np.sin(lat_r), ] ) east = np.array([-np.sin(lon_r), np.cos(lon_r), 0.0]) north = np.cross(up, east) m = np.zeros((3, 3)) m[:, 0], m[:, 1], m[:, 2] = east, north, up return m def pose_to_c2w_ecef(lon, lat, alt, roll, pitch, yaw): r_pose = R.from_euler("xyz", [pitch, roll, yaw], degrees=True).as_matrix() r_enu = enu_to_ecef_rot(lon, lat) r_c2w = r_enu @ r_pose t = wgs84_to_ecef(lon, lat, alt) T = np.eye(4, dtype=np.float64) T[:3, :3] = r_c2w T[:3, 3] = t T[:3, 1] *= -1 T[:3, 2] *= -1 return T def load_poses(path): d = {} for line in open(path, encoding="utf-8"): p = line.split() if p: d[p[0]] = list(map(float, p[1:])) return d def unproject_xy_depth(xy, z, T_c2w, fx, fy, cx, cy): """像素 (x,y) + 深度 z → ECEF。""" x, y = xy[:, 0], xy[:, 1] z = z.astype(np.float64) xc = z * (x - cx) / fx yc = z * (y - cy) / fy pc = np.stack([xc, yc, z], axis=1) Rm, t = T_c2w[:3, :3], T_c2w[:3, 3] return (Rm @ pc.T).T + t def project_ecef(pts, T_c2w, fx, fy, cx, cy): """ECEF → 像素 (x,y)。""" Rm, t = T_c2w[:3, :3], T_c2w[:3, 3] Rinv = Rm.T pc = (Rinv @ (pts - t).T).T z = pc[:, 2] u = fx * pc[:, 0] / z + cx v = fy * pc[:, 1] / z + cy return np.stack([u, v], axis=1) def vis_side_by_side(img_l, img_r, pl, pr, out_path): h1, w1 = img_l.shape[:2] h2, w2 = img_r.shape[:2] pl = np.asarray(pl, dtype=np.float64) pr = np.asarray(pr, dtype=np.float64) in_l = (pl[:, 0] >= 0) & (pl[:, 0] < w1) & (pl[:, 1] >= 0) & (pl[:, 1] < h1) in_r = (pr[:, 0] >= 0) & (pr[:, 0] < w2) & (pr[:, 1] >= 0) & (pr[:, 1] < h2) m = in_l & in_r pl, pr = pl[m], pr[m] h = max(h1, h2) w = w1 + w2 vis = np.zeros((h, w, 3), np.uint8) vis[:h1, :w1] = img_l vis[:h2, w1 : w1 + w2] = img_r for i in range(len(pl)): c = (int(37 * i % 255), int(91 * i % 255), int(17 * i % 255)) x1, y1 = int(pl[i, 0]), int(pl[i, 1]) x2, y2 = int(pr[i, 0]), int(pr[i, 1]) cv2.circle(vis, (x1, y1), 4, c, -1) cv2.circle(vis, (x2 + w1, y2), 4, c, -1) cv2.line(vis, (x1, y1), (x2 + w1, y2), c, 2) OUT.mkdir(parents=True, exist_ok=True) cv2.imwrite(str(out_path), vis) print("Wrote", out_path) def load_bgr(rgb_path, depth_path): im = cv2.imread(str(rgb_path)) if im is not None: return im d = cv2.imread(str(depth_path), cv2.IMREAD_UNCHANGED) d = np.flipud(d[:, :, 0] if d.ndim == 3 else d).astype(np.float32) v = d[d > 0] lo, hi = (np.percentile(v, [2, 98]) if v.size else (0.0, 1.0)) g = (np.clip((d - lo) / (hi - lo + 1e-6), 0, 1) * 255).astype(np.uint8) return cv2.applyColorMap(g, cv2.COLORMAP_VIRIDIS) def main(): pose_txt = ASSETS / "HongKong_seq2@500@30_60@cloudy.txt" ref_d = ASSETS / f"{REF_STEM}_1.png" q_rgb = ASSETS / f"{QUERY_STEM}_0.png" q_d = ASSETS / f"{QUERY_STEM}_1.png" poses = load_poses(pose_txt) T_ref = pose_to_c2w_ecef(*poses[f"{REF_STEM}.jpg"]) T_q = pose_to_c2w_ecef(*poses[f"{QUERY_STEM}.jpg"]) depth = cv2.imread(str(ref_d), cv2.IMREAD_UNCHANGED) depth = np.ascontiguousarray(np.flipud(depth)) rng = np.random.default_rng(0) ex = rng.integers(0, W, size=NUM_SAMPLES) ey = rng.integers(0, H, size=NUM_SAMPLES) xy = np.column_stack([ex.astype(np.float64), ey.astype(np.float64)]) z = depth[ey, ex].astype(np.float64) m = z > 0 xy, z = xy[m], z[m] pts_ecef = unproject_xy_depth(xy, z, T_ref, FX, FY, CX, CY) uv_q = project_ecef(pts_ecef, T_q, FX, FY, CX, CY) ref_img = load_bgr(ASSETS / f"{REF_STEM}_0.png", ref_d) q_img = load_bgr(q_rgb, q_d) vis_side_by_side(q_img, ref_img, uv_q, xy, OUT / "reprojection_matches.png") if __name__ == "__main__": main()