mattak · July 15, 2025 11:00 · Jul 15, 2025
diff --git a/calibrate_fisheye.py b/calibrate_fisheye.py
@@ -0,0 +1,101 @@
+import cv2
+import numpy as np
+import glob
+import os
+import argparse
+
+def calibrate_fisheye(folder_path, pattern_size=(9, 6), square_size=1.0, save_path='fisheye_camera_params.npz'):
+    # 3D座標の準備（Z=0平面）
+    objp = np.zeros((1, pattern_size[0] * pattern_size[1], 3), np.float32)
+    objp[0, :, :2] = np.mgrid[0:pattern_size[0], 0:pattern_size[1]].T.reshape(-1, 2)
+    objp *= square_size
+
+    objpoints = []  # 3D点
+    imgpoints = []  # 2D点
+
+    # 画像取得（再帰的に）
+    image_paths = glob.glob(os.path.join(folder_path, '**', '*.jpg'), recursive=True)
+    image_paths += glob.glob(os.path.join(folder_path, '**', '*.png'), recursive=True)
+
+    print(f"{len(image_paths)} 枚の画像が見つかりました")
+    if not image_paths:
+        print("画像が見つかりませんでした")
+        return
+
+    for path in image_paths:
+        img = cv2.imread(path)
+        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+
+        ret, corners = cv2.findChessboardCorners(
+            gray, pattern_size,
+            cv2.CALIB_CB_ADAPTIVE_THRESH + cv2.CALIB_CB_FAST_CHECK + cv2.CALIB_CB_NORMALIZE_IMAGE
+        )
+
+        if ret:
+            corners2 = cv2.cornerSubPix(
+                gray, corners, (3, 3), (-1, -1),
+                (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.01)
+            )
+            imgpoints.append(corners2)
+            objpoints.append(objp)
+            print(f"OK: {path}")
+        else:
+            print(f"NG: {path}")
+
+    if len(objpoints) < 3:
+        print("十分な有効な画像がありません。最低3枚以上必要です。")
+        return
+
+    N_OK = len(objpoints)
+    img_shape = gray.shape[::-1]
+
+    K = np.zeros((3, 3))
+    D = np.zeros((4, 1))
+    rvecs = [np.zeros((1, 1, 3)) for _ in range(N_OK)]
+    tvecs = [np.zeros((1, 1, 3)) for _ in range(N_OK)]
+
+    flags = (
+        cv2.fisheye.CALIB_RECOMPUTE_EXTRINSIC +
+        cv2.fisheye.CALIB_CHECK_COND +
+        cv2.fisheye.CALIB_FIX_SKEW
+    )
+
+    rms, K, D, rvecs, tvecs = cv2.fisheye.calibrate(
+        objpoints,
+        imgpoints,
+        img_shape,
+        K,
+        D,
+        rvecs,
+        tvecs,
+        flags,
+        (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 100, 1e-6)
+    )
+
+    print("\n=== FishEye キャリブレーション結果 ===")
+    print("RMS 誤差:", rms)
+    print("Camera Matrix (K):\n", K)
+    print("Distortion Coefficients (D):\n", D.ravel())
+
+    # 保存
+    np.savez(save_path, K=K, D=D)
+    print(f"\n保存しました: {save_path}")
+
+
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser(description='OpenCV FishEye カメラキャリブレーションスクリプト')
+    parser.add_argument('--folder', type=str, required=True, help='チェスボード画像のフォルダパス')
+    parser.add_argument('--cols', type=int, default=9, help='チェスボードの列数（交点数）')
+    parser.add_argument('--rows', type=int, default=6, help='チェスボードの行数（交点数）')
+    parser.add_argument('--square-size', type=float, default=1.0, help='1マスのサイズ（mm）')
+    parser.add_argument('--output', type=str, default='fisheye_camera_params.npz', help='出力ファイル名')
+
+    args = parser.parse_args()
+    pattern_size = (args.cols, args.rows)
+
+    calibrate_fisheye(
+        folder_path=args.folder,
+        pattern_size=pattern_size,
+        square_size=args.square_size,
+        save_path=args.output
+    )