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

120 lines
4.1 KiB
Python

import sys
import numpy as np
import cv2 as cv
import math
import argparse
from utils import to_board_pose_euler, cap_init
from aruco_types import ARUCO_DICT
def factory(dict_type: int, square_length: float=5.0, marker_length: float=3.0, margin_length=0):
aruco_dict = cv.aruco.getPredefinedDictionary(dict_type)
board = cv.aruco.CharucoBoard((3,3), 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_diamond_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"]])
# 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):
with np.load('results/cam_calib_charuco.npz') as X:
mtx, dist, _, _ = [X[i] for i in ('mtx', 'dist', 'rvecs', 'tvecs')]
# Open camera
cap = cv.VideoCapture(0)
if not cap.isOpened():
print("Cannot open camera")
exit()
cap_init(cap)
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
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 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
use_detect_diamonds = 0
r_vec = None
t_vec = None
gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
diamond_corners, diamond_ids, marker_corners, marker_ids = detector.detectBoard(gray)
if diamond_corners is not None:
if use_detect_diamonds:
diamond_corners1, diamond_ids1, marker_corners1, marker_ids1 = detector.detectDiamonds(gray)
diamond_corners = diamond_corners1[0]
diamond_ids = np.transpose(diamond_ids1[0])
marker_corners = marker_corners1
marker_ids = marker_ids1[0]
# Draw marker box
if draw_marker_box:
cv.aruco.drawDetectedMarkers(img, marker_corners)
# Draw marker id
if draw_marker_id:
cv.aruco.drawDetectedDiamonds(img, diamond_corners, diamond_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(diamond_ids) >= len(board.getIds()):
# Estimate diamond pose
obj_points, img_points = board.matchImagePoints(diamond_corners, diamond_ids)
offset = int(board.getMarkerLength() * board.getSquareLength())
obj_points -= [offset/2, offset/2, 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 Axis
cv.drawFrameAxes(img, mtx, dist, r_vec, t_vec, 10)
return r_vec, t_vec
if __name__ == '__main__':
main()
cv.destroyAllWindows()