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ocv_cam_pose/legacy/cam_pose_charuco_board.py
2025-11-28 18:49:48 +01:00

166 lines
5.6 KiB
Python

import sys
import numpy as np
import cv2 as cv
import argparse
from aruco_types import ARUCO_DICT
import math
from utils import to_board_pose_euler, cap_init
CAM_CALIB_FILE = "results/cam_calib_charuco.npz"
def factory(dict_type: int, board_size: cv.typing.Size, square_length: float=5.0, marker_length: float=3.0, margin_length=0):
aruco_dict = cv.aruco.getPredefinedDictionary(dict_type)
board = cv.aruco.CharucoBoard(board_size, square_length, marker_length, aruco_dict)
params = cv.aruco.CharucoParameters()
detector = cv.aruco.CharucoDetector(board, params)
image = board.generateImage((800, 600), None, margin_length, 1)
cv.imwrite("results/charuco_board.png", image)
return detector, board
def main():
# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-t", "--type", type=str,
default="DICT_ARUCO_ORIGINAL",
help="type of ArUCo tag to detect")
args = vars(ap.parse_args())
# verify that the supplied ArUCo tag exists and is supported by
# OpenCV
if ARUCO_DICT.get(args["type"], None) is None:
print("[INFO] ArUCo tag of '{}' is not supported".format(
args["type"]))
sys.exit(0)
# load the ArUCo dictionary, grab the ArUCo parameters, and detect
# the markers
print("[INFO] detecting '{}' tags...".format(args["type"]))
detector, board = factory(ARUCO_DICT[args["type"]], (6,7))
# load the input image from disk and resize it
print("[INFO] start processing...")
process_video(detector, board)
def process_video(detector: cv.aruco.CharucoDetector, board: cv.aruco.CharucoBoard):
mtx = None
dist = None
obj_points_list = []
img_points_list = []
try:
with np.load(CAM_CALIB_FILE) as X:
mtx, dist, _, _ = [X[i] for i in ('mtx', 'dist', 'rvecs', 'tvecs')]
except FileNotFoundError:
pass
except KeyError:
pass
# Open camera
cap = cv.VideoCapture(0)
if not cap.isOpened():
print("Cannot open camera")
exit()
cap_init(cap)
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'):
img_size, obj_points, img_points = store_frame(detector, board, img)
if img_size is not None:
obj_points_list.append(obj_points)
img_points_list.append(img_points)
elif k == ord('c'):
mtx, dist, rvecs, tvecs = calibrate_camera(img_size, obj_points_list, img_points_list, mtx, dist, None, None)
np.savez(f"{CAM_CALIB_FILE}", mtx=mtx, dist=dist, rvecs=rvecs, tvecs=tvecs)
elif k == ord('x'):
mtx = None
dist = None
obj_points_list = []
img_points_list = []
else:
r_vec, t_vec = process(detector, board, img, mtx, dist, None, None)
if r_vec is not None and t_vec is not None:
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)
def store_frame(detector: cv.aruco.CharucoDetector, board: cv.aruco.Board, img):
img_size = None
obj_points = None
img_points = None
gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
charuco_corners, charuco_ids, _, _ = detector.detectBoard(gray)
if charuco_corners is not None:
if len(charuco_ids) >= len(board.getIds()):
obj_points, img_points = board.matchImagePoints(charuco_corners, charuco_ids)
if len(obj_points) > 0 and len(img_points) > 0:
img_size = gray.shape
print("Frame captured")
else:
print("Point matching failed, try again")
else:
print("Point matching failed, try again")
else:
print("Point matching failed, try again")
return img_size, obj_points, img_points
def calibrate_camera(img_size, obj_points_list, img_points_list, mtx, dist, rvecs=None, tvecs=None, flags=0):
if len(obj_points_list) > 0 and len(img_points_list) > 0:
ret, mtx, dist, rvecs, tvecs = cv.calibrateCamera(obj_points_list, img_points_list, img_size, mtx, dist, rvecs=rvecs, tvecs=tvecs, flags=flags)
print(f"Camera calibration finished. Result = {ret}")
return mtx, dist, rvecs, tvecs
def process(detector: cv.aruco.CharucoDetector, board: cv.aruco.CharucoBoard, img, mtx, dist, rvecs=None, tvecs=None, draw_marker_box=True, draw_marker_id=False, draw_marker_axis=False): # Load previously saved data
r_vec = None
t_vec = None
gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
charuco_corners, charuco_ids, marker_corners, marker_ids = detector.detectBoard(gray)
if charuco_corners is not None:
# Draw marker box
if draw_marker_box:
cv.aruco.drawDetectedMarkers(img, marker_corners)
# Draw marker id
if draw_marker_id:
cv.aruco.drawDetectedCornersCharuco(img, charuco_corners, charuco_ids)
# Draw marker axis
if draw_marker_axis:
_rvecs, _tvecs, _ = cv.aruco.estimatePoseSingleMarkers(marker_corners, markerLength=0.1, cameraMatrix=mtx, distCoeffs=dist)
for i in range(len(_rvecs)):
cv.drawFrameAxes(img, mtx, dist, _rvecs[i], _tvecs[i], 0.05)
if len(charuco_ids) >= len(board.getIds()):
obj_points, img_points = board.matchImagePoints(charuco_corners, charuco_ids)
offset = int(board.getMarkerLength() * board.getSquareLength())
obj_points -= [offset, offset, 0]
if mtx is not None and dist is not None:
pose, r_vec, t_vec = cv.solvePnP(obj_points, img_points, mtx, dist, useExtrinsicGuess=False, rvec=rvecs, tvec=tvecs, flags=cv.SOLVEPNP_ITERATIVE)
if pose:
# Draw
cv.drawFrameAxes(img, mtx, dist, r_vec, t_vec, 10)
return r_vec, t_vec
if __name__ == '__main__':
main()
cv.destroyAllWindows()