refactored

legacy/cam_pose_aruco_board.py

@@ -0,0 +1,95 @@
+import sys
+import numpy as np
+import cv2 as cv
+import argparse
+from aruco_types import ARUCO_DICT
+
+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
+
+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"]], (5, 5))
+
+	# load the input image from disk and resize it
+	print("[INFO] start processing...")
+	process_video(detector, board)
+
+def process_video(detector: cv.aruco.ArucoDetector, board):
+	with np.load('results/cam_calib_charuco.npz') as X:
+		mtx, dist, _, _ = [X[i] for i in ('mtx', 'dist', 'rvecs', 'tvecs')]
+
+	# Open camera
+	video = cv.VideoCapture(0)
+	if not video.isOpened():
+		print("Cannot open camera")
+		exit()
+
+	while True:
+		# Read a new frame
+		ok, img = video.read()
+		if not ok:
+			return
+		process(detector, board, img, mtx, dist)
+		k = cv.waitKey(1) & 0xFF
+		if k == ord('q'):
+			break
+
+def process(detector: cv.aruco.ArucoDetector, board: cv.aruco.GridBoard, img, mtx, dist, r_vecs=None, t_vecs=None, draw_marker_box=True, draw_marker_id=False, draw_marker_axis=True):
+	gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
+	(corners, ids, rejected) = detector.detectMarkers(gray)
+
+	# Draw a square around the markers
+	if draw_marker_box:
+		cv.aruco.drawDetectedMarkers(img, corners)
+
+	# Draw marker id
+	if draw_marker_id:
+		cv.aruco.drawDetectedMarkers(img, corners, ids)
+
+	# Draw marker axis
+	if draw_marker_axis:
+		_r_vecs, _t_vecs, _ = cv.aruco.estimatePoseSingleMarkers(corners, markerLength=0.1, cameraMatrix=mtx, distCoeffs=dist)
+		if _r_vecs is not None:
+			for i in range(len(_r_vecs)):
+				cv.drawFrameAxes(img, mtx, 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 = board.matchImagePoints(corners, ids)
+		pose, r_vec, t_vec = cv.solvePnP(obj_points, img_points, mtx, dist, r_vecs, t_vecs)
+		if pose:
+			# Draw Axis
+			cv.drawFrameAxes(img, mtx, dist, r_vec, t_vec, board.getMarkerLength()*1.5)
+
+
+	cv.imshow('img', img)
+
+
+if __name__ == '__main__':
+	main()
+	cv.destroyAllWindows()