def intrinsics(self):
if self._intrinsics is None or self._intrinsics.resolution != self.frame_size:
if self.projection_matrix is None:
distortion = [[0.0, 0.0, 0.0, 0.0, 0.0]]
self._intrinsics = Radial_Dist_Camera(
self.projection_matrix, distortion, self.frame_size, self.name
)
else:
self._intrinsics = Dummy_Camera(self.frame_size, self.name)
return self._intrinsics
def intrinsics(self):
if self._intrinsics is None or self._intrinsics.resolution != self.frame_size:
lens_params = roypycy.get_lens_parameters(self.camera)
c_x, c_y = lens_params["principalPoint"]
f_x, f_y = lens_params["focalLength"]
p_1, p_2 = lens_params["distortionTangential"]
k_1, k_2, *k_other = lens_params["distortionRadial"]
K = [[f_x, 0.0, c_x], [0.0, f_y, c_y], [0.0, 0.0, 1.0]]
D = k_1, k_2, p_1, p_2, *k_other
self._intrinsics = Radial_Dist_Camera(K, D, self.frame_size, self.name)
return self._intrinsics
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 intrinsics(self):
if not self.online:
return self._intrinsics or Dummy_Camera(self.frame_size, self.name)
if self._intrinsics is None or self._intrinsics.resolution != self.frame_size:
lens_params = self.camera.get_lens_parameters()
c_x, c_y = lens_params.principal_point
f_x, f_y = lens_params.focal_length
p_1, p_2 = lens_params.distortion_tangential
k_1, k_2, *k_other = lens_params.distortion_radial
K = [[f_x, 0.0, c_x], [0.0, f_y, c_y], [0.0, 0.0, 1.0]]
D = k_1, k_2, p_1, p_2, *k_other
self._intrinsics = Radial_Dist_Camera(K, D, self.frame_size, self.name)
with open(os.path.join(self.g_pool.user_dir, "picoflexx_intrinsics"), "wb") as f:
pickle.dump([
K, D, self.frame_size, self.name
], f)
return self._intrinsics
def intrinsics(self):
if self._intrinsics is None or self._intrinsics.resolution != self.frame_size:
self._intrinsics = load_intrinsics(self.g_pool.user_dir, self.name,
self.frame_size)
if type(self._intrinsics) is Dummy_Camera:
logger.info("Was dummy camera")
saved_fp = os.path.join(self.g_pool.user_dir,
"picoflexx_intrinsics")
if os.path.exists(saved_fp):
with open(saved_fp, "rb") as f:
K, D, self.frame_size, self.name = pickle.load(f)
self._intrinsics = Radial_Dist_Camera(
K, D, self.frame_size, self.name)
logger.info("Loaded from saved")
else:
logger.info("No saved intrinsics?")
return self._intrinsics