refatored into class

This commit is contained in:
2025-11-28 14:37:57 +01:00
parent f79fdde5e3
commit 3ac10cf0aa
2 changed files with 213 additions and 0 deletions
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import abc
import math
import cv2 as cv
import numpy as np
from utils import to_board_pose_euler
class ArTagPose(abc.ABC):
detector: cv.aruco.ArucoDetector | cv.aruco.CharucoDetector = None
board: cv.aruco.GridBoard | cv.aruco.CharucoBoard = None
mtx = None
dist = None
r_vecs = None
t_vecs = None
img_size = None
obj_points_list = []
img_points_list = []
@staticmethod
def cap_init(cap: cv.VideoCapture):
cap.set(cv.CAP_PROP_SETTINGS, 1)
cap.set(cv.CAP_PROP_FOURCC, cv.VideoWriter.fourcc('M', 'J', 'P', 'G'))
cap.set(cv.CAP_PROP_FPS, 60.0)
cap.set(cv.CAP_PROP_FRAME_WIDTH, 1280)
cap.set(cv.CAP_PROP_FRAME_HEIGHT, 1024)
cap.set(cv.CAP_PROP_EXPOSURE, 30)
cap.set(cv.CAP_PROP_AUTO_EXPOSURE, 1)
def is_calibrated(self):
return self.mtx is not None and self.dist is not None
def calibrate_camera(self, cal_img_size: tuple[int,int], r_vecs=None, t_vecs=None, flags=0):
success = False
if len(self.obj_points_list) > 0 and len(self.img_points_list) > 0:
ret, mtx, dist, r_vecs, t_vecs = cv.calibrateCamera(self.obj_points_list, self.img_points_list, cal_img_size, self.mtx, self.dist,
rvecs=r_vecs, tvecs=t_vecs, flags=flags)
print(f"Camera calibration finished: ", end='')
if ret < 2:
print(f"Success ({ret})!")
success = True
self.mtx = mtx
self.dist = dist
self.r_vecs = r_vecs
self.t_vecs = t_vecs
else:
print(f"Failed ({ret})!")
return success
@abc.abstractmethod
def calibrate_points(self, image: cv.typing.MatLike):
pass
@abc.abstractmethod
def calibrate_save(self):
pass
@abc.abstractmethod
def calibrate_load(self):
pass
def process(self):
# Open camera
cap = cv.VideoCapture(0)
ArTagPose.cap_init(cap)
if not cap.isOpened():
print("Cannot open camera")
exit()
self.calibrate_load()
cal_img_size = None
last_rotation = [0, 0, 0]
while True:
# Read a new frame
ok, img = cap.read()
if not ok:
return
k = cv.waitKey(1) & 0xFF
if k == ord('q'):
break
elif k == ord('s'):
success, cal_img_size, obj_points, img_points = self.calibrate_points(img)
if success:
print("Frame captured")
self.obj_points_list.append(obj_points)
self.img_points_list.append(img_points)
else:
print("Point matching failed, try again")
elif k == ord('c'):
if self.calibrate_camera(cal_img_size):
self.calibrate_save()
elif k == ord('x'):
self.mtx = None
self.dist = None
self.obj_points_list = []
self.img_points_list = []
else:
success, r_vec, t_vec = self._process(img)
if success:
r_vec_obj, _ = to_board_pose_euler(r_vec, t_vec)
rot = [round(180.0 / math.pi * v, 0) for v in r_vec_obj]
if rot != last_rotation:
print("\r ",
end='')
print(f"\rTilt: {rot[0]:.1f}, Roll: {rot[1]:.1f}, Azimuth: {rot[2]:.1f}", end='')
last_rotation = rot
cv.imshow('img', img)
cv.destroyAllWindows()
@abc.abstractmethod
def _process(self, image, draw_marker_box=True, draw_marker_id=False, draw_marker_axis=True) -> (bool, np.ndarray, np.ndarray):
pass
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from PIL.ImageOps import posterize
from ar_tag_pose import ArTagPose
import numpy as np
import cv2 as cv
def factory(dict_type: int, board_size: cv.typing.Size, marker_length: float=100.0, marker_sep=10, margins=10):
aruco_dict = cv.aruco.getPredefinedDictionary(dict_type)
params = cv.aruco.DetectorParameters()
detector = cv.aruco.ArucoDetector(aruco_dict, params)
board = cv.aruco.GridBoard(board_size, markerLength=marker_length, markerSeparation=marker_sep, dictionary=aruco_dict)
im_w = int(board_size[0] * (marker_length + marker_sep) - marker_sep + 2 * margins)
im_h = int(board_size[1] * (marker_length + marker_sep) - marker_sep + 2 * margins)
image = board.generateImage((im_w, im_h), None, margins, 1)
cv.imwrite("results/aruco_board.png", image)
return detector, board
class ArTagPoseArucoBoard(ArTagPose):
def __init__(self, dict_type: int, board_size: tuple[int, int]):
self.board_size = board_size
self.calib_filename = f"results/cam_calib_aruco_board_w{board_size[0]}_h{board_size[1]}.npz"
self.detector, self.board = factory(dict_type, board_size)
def calibrate_save(self):
np.savez(f"{self.calib_filename}", mtx=self.mtx, dist=self.dist, rvecs=self.r_vecs, tvecs=self.t_vecs)
def calibrate_load(self):
try:
with np.load(self.calib_filename) as X:
self.mtx, self.dist, _, _ = [X[i] for i in ('mtx', 'dist', 'rvecs', 'tvecs')]
except FileNotFoundError:
pass
except KeyError:
pass
def calibrate_points(self, image: cv.typing.MatLike):
success = False
img_size = (0,0)
obj_points = None
img_points = None
gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
corners, ids, _ = self.detector.detectMarkers(gray)
if corners is not None:
if len(ids) >= len(self.board.getIds()):
_obj_points, _img_points = self.board.matchImagePoints(corners, ids)
if len(_obj_points) > 0 and len(_img_points) > 0:
success =True
img_size = gray.shape
obj_points = _obj_points
img_points = _img_points
return success, img_size, obj_points, img_points
def _process(self, image, r_vecs: np.ndarray=None, t_vecs: np.ndarray=None, draw_marker_box=True, draw_marker_id=False, draw_marker_axis=True):
pose = False
r_vec = None
t_vec = None
if not self.is_calibrated():
return pose, None, None
gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
(corners, ids, rejected) = self.detector.detectMarkers(gray)
# Draw a square around the markers
if draw_marker_box:
cv.aruco.drawDetectedMarkers(image, corners)
# Draw marker id
if draw_marker_id:
cv.aruco.drawDetectedMarkers(image, corners, ids)
# Draw marker axis
if draw_marker_axis:
_r_vecs, _t_vecs, _ = cv.aruco.estimatePoseSingleMarkers(corners, markerLength=0.1, cameraMatrix=self.mtx, distCoeffs=self.dist)
if _r_vecs is not None:
for i in range(len(_r_vecs)):
cv.drawFrameAxes(image, self.mtx, self.dist, _r_vecs[i], _t_vecs[i], 0.05)
if len(corners) > 0:
# Estimate pose of each marker and return the values r_vec and t_vec---(different from those of camera coefficients)
obj_points, img_points = self.board.matchImagePoints(corners, ids)
pose, r_vec, t_vec = cv.solvePnP(obj_points, img_points, self.mtx, self.dist, rvec=r_vecs, tvec=t_vecs)
if pose:
# Draw Axis
cv.drawFrameAxes(image, self.mtx, self.dist, r_vec, t_vec, self.board.getMarkerLength()*1.5)
return pose, r_vec, t_vec
def main():
pose = ArTagPoseArucoBoard(10, (5,5))
pose.calibrate_load()
pose.process()
if __name__ == '__main__':
main()