def calculate(self):
self.calculated = True
self.count = 10
img_shape = self.g_pool.capture.frame_size
# Compute calibration
try:
if self.dist_mode == "Fisheye":
calibration_flags = cv2.fisheye.CALIB_RECOMPUTE_EXTRINSIC + cv2.fisheye.CALIB_CHECK_COND + cv2.fisheye.CALIB_FIX_SKEW
max_iter=30
eps=1e-6
camera_matrix = np.zeros((3, 3))
dist_coefs = np.zeros((4, 1))
rvecs = [np.zeros((1, 1, 3), dtype=np.float64) for i in range(self.count)]
tvecs = [np.zeros((1, 1, 3), dtype=np.float64) for i in range(self.count)]
objPoints = [x.reshape(1,-1,3) for x in self.obj_points]
imgPoints = self.img_points
rms, _, _, _, _ = \
cv2.fisheye.calibrate(
objPoints,
imgPoints,
img_shape,
camera_matrix,
dist_coefs,
rvecs,
tvecs,
calibration_flags,
(cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, max_iter, eps)
)
camera_model = Fisheye_Dist_Camera(camera_matrix, dist_coefs, img_shape, self.g_pool.capture.name)
elif self.dist_mode == "Radial":
rms, camera_matrix, dist_coefs, rvecs, tvecs = cv2.calibrateCamera(np.array(self.obj_points),
np.array(self.img_points),
self.g_pool.capture.frame_size, None,
None)
camera_model = Radial_Dist_Camera(camera_matrix, dist_coefs, img_shape, self.g_pool.capture.name)
else:
raise ValueError("Unkown distortion model: {}".format(self.dist_mode))
except ValueError as e:
raise e
except Exception as e:
logger.warning("Camera calibration failed to converge!")
logger.warning("Please try again with a better coverage of the cameras FOV!")
return
logger.info("Calibrated Camera, RMS:{}".format(rms))
camera_model.save(self.g_pool.user_dir)
self.g_pool.capture.intrinsics = camera_model
# self.camera_intrinsics = camera_matrix.tolist(),dist_coefs.tolist(),self.g_pool.capture.frame_size TODO delete this, used anywhere?
self.show_undistortion_switch.read_only=False
def calculate(self):
self.calculated = True
self.count = 10
img_shape = self.g_pool.capture.frame_size
# Compute calibration
try:
if self.dist_mode == "Fisheye":
calibration_flags = (
cv2.fisheye.CALIB_RECOMPUTE_EXTRINSIC
+ cv2.fisheye.CALIB_CHECK_COND
+ cv2.fisheye.CALIB_FIX_SKEW
)
max_iter = 30
eps = 1e-6
camera_matrix = np.zeros((3, 3))
dist_coefs = np.zeros((4, 1))
rvecs = [
np.zeros((1, 1, 3), dtype=np.float64) for i in range(self.count)
]
tvecs = [
np.zeros((1, 1, 3), dtype=np.float64) for i in range(self.count)
]
objPoints = [x.reshape(1, -1, 3) for x in self.obj_points]
imgPoints = self.img_points
rms, _, _, _, _ = cv2.fisheye.calibrate(
objPoints,
imgPoints,
img_shape,
camera_matrix,
dist_coefs,
rvecs,
tvecs,
calibration_flags,
(cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, max_iter, eps),
)
camera_model = Fisheye_Dist_Camera(
camera_matrix, dist_coefs, img_shape, self.g_pool.capture.name
)
elif self.dist_mode == "Radial":
rms, camera_matrix, dist_coefs, rvecs, tvecs = cv2.calibrateCamera(
np.array(self.obj_points),
np.array(self.img_points),
self.g_pool.capture.frame_size,
None,
None,
)
camera_model = Radial_Dist_Camera(
camera_matrix, dist_coefs, img_shape, self.g_pool.capture.name
)
else:
raise ValueError("Unkown distortion model: {}".format(self.dist_mode))
except ValueError as e:
raise e
except Exception as e:
logger.warning("Camera calibration failed to converge!")
logger.warning(
"Please try again with a better coverage of the cameras FOV!"
)
return
logger.info("Calibrated Camera, RMS:{}".format(rms))
camera_model.save(self.g_pool.user_dir)
self.g_pool.capture.intrinsics = camera_model
self.show_undistortion_switch.read_only = False