120 lines
4.1 KiB
Python
120 lines
4.1 KiB
Python
import sys
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import numpy as np
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import cv2 as cv
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import math
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import argparse
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from utils import to_board_pose_euler, cap_init
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from aruco_types import ARUCO_DICT
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def factory(dict_type: int, square_length: float=5.0, marker_length: float=3.0, margin_length=0):
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aruco_dict = cv.aruco.getPredefinedDictionary(dict_type)
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board = cv.aruco.CharucoBoard((3,3), square_length, marker_length, aruco_dict)
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params = cv.aruco.CharucoParameters()
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detector = cv.aruco.CharucoDetector(board, params)
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image = board.generateImage((800, 600), None, margin_length, 1)
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cv.imwrite("results/charuco_diamond_board.png", image)
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return detector, board
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def main():
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# construct the argument parser and parse the arguments
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ap = argparse.ArgumentParser()
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ap.add_argument("-t", "--type", type=str,
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default="DICT_ARUCO_ORIGINAL",
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help="type of ArUCo tag to detect")
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args = vars(ap.parse_args())
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# verify that the supplied ArUCo tag exists and is supported by
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# OpenCV
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if ARUCO_DICT.get(args["type"], None) is None:
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print("[INFO] ArUCo tag of '{}' is not supported".format(
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args["type"]))
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sys.exit(0)
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# load the ArUCo dictionary, grab the ArUCo parameters, and detect
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# the markers
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print("[INFO] detecting '{}' tags...".format(args["type"]))
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detector, board = factory(ARUCO_DICT[args["type"]])
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# load the input image from disk and resize it
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print("[INFO] start processing...")
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process_video(detector, board)
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def process_video(detector: cv.aruco.CharucoDetector, board: cv.aruco.CharucoBoard):
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with np.load('results/cam_calib_charuco.npz') as X:
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mtx, dist, _, _ = [X[i] for i in ('mtx', 'dist', 'rvecs', 'tvecs')]
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# Open camera
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cap = cv.VideoCapture(0)
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if not cap.isOpened():
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print("Cannot open camera")
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exit()
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cap_init(cap)
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last_rotation = [0,0,0]
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while True:
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# Read a new frame
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ok, img = cap.read()
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if not ok:
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return
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k = cv.waitKey(1) & 0xFF
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if k == ord('q'):
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break
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else:
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r_vec, t_vec = process(detector, board, img, mtx, dist, None, None)
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if r_vec is not None and t_vec is not None:
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r_vec_obj, _ = to_board_pose_euler(r_vec, t_vec)
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rot = [round(180.0 / math.pi * v, 0) for v in r_vec_obj]
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if rot != last_rotation:
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print("\r ", end='')
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print(f"\rTilt: {rot[0]:.1f}, Roll: {rot[1]:.1f}, Azimuth: {rot[2]:.1f}", end='')
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last_rotation = rot
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cv.imshow('img', img)
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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
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use_detect_diamonds = 0
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r_vec = None
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t_vec = None
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gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
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diamond_corners, diamond_ids, marker_corners, marker_ids = detector.detectBoard(gray)
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if diamond_corners is not None:
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if use_detect_diamonds:
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diamond_corners1, diamond_ids1, marker_corners1, marker_ids1 = detector.detectDiamonds(gray)
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diamond_corners = diamond_corners1[0]
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diamond_ids = np.transpose(diamond_ids1[0])
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marker_corners = marker_corners1
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marker_ids = marker_ids1[0]
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# Draw marker box
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if draw_marker_box:
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cv.aruco.drawDetectedMarkers(img, marker_corners)
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# Draw marker id
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if draw_marker_id:
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cv.aruco.drawDetectedDiamonds(img, diamond_corners, diamond_ids)
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# Draw marker axis
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if draw_marker_axis:
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_rvecs, _tvecs, _ = cv.aruco.estimatePoseSingleMarkers(marker_corners, markerLength=0.1, cameraMatrix=mtx, distCoeffs=dist)
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for i in range(len(_rvecs)):
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cv.drawFrameAxes(img, mtx, dist, _rvecs[i], _tvecs[i], 0.05)
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if len(diamond_ids) >= len(board.getIds()):
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# Estimate diamond pose
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obj_points, img_points = board.matchImagePoints(diamond_corners, diamond_ids)
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offset = int(board.getMarkerLength() * board.getSquareLength())
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obj_points -= [offset/2, offset/2, 0]
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if mtx is not None and dist is not None:
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pose, r_vec, t_vec = cv.solvePnP(obj_points, img_points, mtx, dist, useExtrinsicGuess=False, rvec=rvecs,
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tvec=tvecs, flags=cv.SOLVEPNP_ITERATIVE)
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if pose:
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# Draw Axis
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cv.drawFrameAxes(img, mtx, dist, r_vec, t_vec, 10)
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return r_vec, t_vec
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if __name__ == '__main__':
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main()
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cv.destroyAllWindows()
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