Python cv2.CALIB_CB_NORMALIZE_IMAGE属性代码示例

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import CALIB_CB_NORMALIZE_IMAGE [as 别名]
def find_chessboard(frame):
    chessboard_flags = cv2.CALIB_CB_ADAPTIVE_THRESH + cv2.CALIB_CB_FAST_CHECK + cv2.CALIB_CB_NORMALIZE_IMAGE
    small_frame = cv2.resize(frame, (0, 0), fx=0.3, fy=0.3)
    return cv2.findChessboardCorners(small_frame, (9, 6), chessboard_flags)[0] and \
           cv2.findChessboardCorners(frame, (9, 6), chessboard_flags)[0] 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import CALIB_CB_NORMALIZE_IMAGE [as 别名]
def process_images(self, filepath):
        """Read images, detect corners, refine corners, and save data."""
        # Arrays to store object points and image points from all the images.
        self.objpoints = []  # 3d point in real world space
        self.imgpoints_l = []  # 2d points in image plane.
        self.imgpoints_r = []  # 2d points in image plane.
        self.calib_successes = [] # polygon ids of left/right image sets with checkerboard corners.

        images_left = glob.glob(filepath + "/left/*")
        images_right = glob.glob(filepath + "/right/*")
        images_left.sort()
        images_right.sort()

        print("\nAttempting to read images for left camera from dir: " +
              filepath + "/left/")
        print("Attempting to read images for right camera from dir: " +
              filepath + "/right/")

        assert len(images_left) != 0, "ERROR: Images not read correctly, check directory"
        assert len(images_right) != 0, "ERROR: Images not read correctly, check directory"

        for image_left, image_right in zip(images_left, images_right):
            img_l = cv2.imread(image_left, 0)
            img_r = cv2.imread(image_right, 0)

            assert img_l is not None, "ERROR: Images not read correctly"
            assert img_r is not None, "ERROR: Images not read correctly"

            print("Finding chessboard corners for %s and %s..." % (os.path.basename(image_left), os.path.basename(image_right)))
            start_time = time.time()

            # Find the chess board corners
            flags = 0
            flags |= cv2.CALIB_CB_ADAPTIVE_THRESH
            flags |= cv2.CALIB_CB_NORMALIZE_IMAGE
            ret_l, corners_l = cv2.findChessboardCorners(img_l, (9, 6), flags)
            ret_r, corners_r = cv2.findChessboardCorners(img_r, (9, 6), flags)

            # termination criteria
            self.criteria = (cv2.TERM_CRITERIA_MAX_ITER +
                             cv2.TERM_CRITERIA_EPS, 30, 0.001)

            # if corners are found in both images, refine and add data
            if ret_l and ret_r:
                self.objpoints.append(self.objp)
                rt = cv2.cornerSubPix(img_l, corners_l, (5, 5),
                                      (-1, -1), self.criteria)
                self.imgpoints_l.append(corners_l)
                rt = cv2.cornerSubPix(img_r, corners_r, (5, 5),
                                      (-1, -1), self.criteria)
                self.imgpoints_r.append(corners_r)
                self.calib_successes.append(polygon_from_image_name(image_left))
                print("\t[OK]. Took %i seconds." % (round(time.time() - start_time, 2)))
            else:
                print("\t[ERROR] - Corners not detected. Took %i seconds." % (round(time.time() - start_time, 2)))

            self.img_shape = img_r.shape[::-1]
        print(str(len(self.objpoints)) + " of " + str(len(images_left)) +
              " images being used for calibration")
        self.ensure_valid_images() 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import CALIB_CB_NORMALIZE_IMAGE [as 别名]
def get_K_and_D(checkerboard, imgsPath):

    CHECKERBOARD = checkerboard
    subpix_criteria = (cv2.TERM_CRITERIA_EPS+cv2.TERM_CRITERIA_MAX_ITER, 30, 0.1)
    calibration_flags = cv2.fisheye.CALIB_RECOMPUTE_EXTRINSIC+cv2.fisheye.CALIB_CHECK_COND+cv2.fisheye.CALIB_FIX_SKEW
    objp = np.zeros((1, CHECKERBOARD[0]*CHECKERBOARD[1], 3), np.float32)
    objp[0,:,:2] = np.mgrid[0:CHECKERBOARD[0], 0:CHECKERBOARD[1]].T.reshape(-1, 2)
    _img_shape = None
    objpoints = []
    imgpoints = []
    images = glob.glob(imgsPath + '/*.png')
    for fname in images:
        img = cv2.imread(fname)
        if _img_shape == None:
            _img_shape = img.shape[:2]
        else:
            assert _img_shape == img.shape[:2], "All images must share the same size."

        gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
        ret, corners = cv2.findChessboardCorners(gray, CHECKERBOARD,cv2.CALIB_CB_ADAPTIVE_THRESH+cv2.CALIB_CB_FAST_CHECK+cv2.CALIB_CB_NORMALIZE_IMAGE)
        if ret == True:
            objpoints.append(objp)
            cv2.cornerSubPix(gray,corners,(3,3),(-1,-1),subpix_criteria)
            imgpoints.append(corners)
    N_OK = len(objpoints)
    K = np.zeros((3, 3))
    D = np.zeros((4, 1))
    rvecs = [np.zeros((1, 1, 3), dtype=np.float64) for i in range(N_OK)]
    tvecs = [np.zeros((1, 1, 3), dtype=np.float64) for i in range(N_OK)]
    rms, _, _, _, _ = cv2.fisheye.calibrate(
        objpoints,
        imgpoints,
        gray.shape[::-1],
        K,
        D,
        rvecs,
        tvecs,
        calibration_flags,
        (cv2.TERM_CRITERIA_EPS+cv2.TERM_CRITERIA_MAX_ITER, 30, 1e-6)
    )
    DIM = _img_shape[::-1]
    print("Found " + str(N_OK) + " valid images for calibration")
    print("DIM=" + str(_img_shape[::-1]))
    print("K=np.array(" + str(K.tolist()) + ")")
    print("D=np.array(" + str(D.tolist()) + ")")
    return DIM, K, D