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Open Source Computer Vision Library
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115 lines
5.3 KiB
115 lines
5.3 KiB
#!/usr/bin/env python |
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"""aruco_detect_board_charuco.py |
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Usage example: |
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python aruco_detect_board_charuco.py -w=5 -h=7 -sl=0.04 -ml=0.02 -d=10 -c=../data/aruco/tutorial_camera_charuco.yml |
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-i=../data/aruco/choriginal.jpg |
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""" |
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import argparse |
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import numpy as np |
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import cv2 as cv |
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import sys |
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def read_camera_parameters(filename): |
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fs = cv.FileStorage(cv.samples.findFile(filename, False), cv.FileStorage_READ) |
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if fs.isOpened(): |
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cam_matrix = fs.getNode("camera_matrix").mat() |
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dist_coefficients = fs.getNode("distortion_coefficients").mat() |
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return True, cam_matrix, dist_coefficients |
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return False, [], [] |
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def main(): |
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# parse command line options |
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parser = argparse.ArgumentParser(description="detect markers and corners of charuco board, estimate pose of charuco" |
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"board", add_help=False) |
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parser.add_argument("-H", "--help", help="show help", action="store_true", dest="show_help") |
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parser.add_argument("-v", "--video", help="Input from video or image file, if omitted, input comes from camera", |
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default="", action="store", dest="v") |
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parser.add_argument("-i", "--image", help="Input from image file", default="", action="store", dest="img_path") |
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parser.add_argument("-w", help="Number of squares in X direction", default="3", action="store", dest="w", type=int) |
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parser.add_argument("-h", help="Number of squares in Y direction", default="3", action="store", dest="h", type=int) |
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parser.add_argument("-sl", help="Square side length", default="1.", action="store", dest="sl", type=float) |
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parser.add_argument("-ml", help="Marker side length", default="0.5", action="store", dest="ml", type=float) |
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parser.add_argument("-d", help="dictionary: DICT_4X4_50=0, DICT_4X4_100=1, DICT_4X4_250=2, DICT_4X4_1000=3," |
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"DICT_5X5_50=4, DICT_5X5_100=5, DICT_5X5_250=6, DICT_5X5_1000=7, DICT_6X6_50=8," |
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"DICT_6X6_100=9, DICT_6X6_250=10, DICT_6X6_1000=11, DICT_7X7_50=12, DICT_7X7_100=13," |
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"DICT_7X7_250=14, DICT_7X7_1000=15, DICT_ARUCO_ORIGINAL = 16}", |
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default="0", action="store", dest="d", type=int) |
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parser.add_argument("-ci", help="Camera id if input doesnt come from video (-v)", default="0", action="store", |
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dest="ci", type=int) |
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parser.add_argument("-c", help="Input file with calibrated camera parameters", default="", action="store", |
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dest="cam_param") |
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args = parser.parse_args() |
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show_help = args.show_help |
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if show_help: |
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parser.print_help() |
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sys.exit() |
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width = args.w |
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height = args.h |
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square_len = args.sl |
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marker_len = args.ml |
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dict = args.d |
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video = args.v |
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camera_id = args.ci |
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img_path = args.img_path |
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cam_param = args.cam_param |
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cam_matrix = [] |
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dist_coefficients = [] |
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if cam_param != "": |
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_, cam_matrix, dist_coefficients = read_camera_parameters(cam_param) |
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aruco_dict = cv.aruco.getPredefinedDictionary(dict) |
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board_size = (width, height) |
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board = cv.aruco.CharucoBoard(board_size, square_len, marker_len, aruco_dict) |
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charuco_detector = cv.aruco.CharucoDetector(board) |
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image = None |
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input_video = None |
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wait_time = 10 |
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if video != "": |
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input_video = cv.VideoCapture(cv.samples.findFileOrKeep(video, False)) |
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image = input_video.retrieve()[1] if input_video.grab() else None |
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elif img_path == "": |
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input_video = cv.VideoCapture(camera_id) |
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image = input_video.retrieve()[1] if input_video.grab() else None |
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elif img_path != "": |
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wait_time = 0 |
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image = cv.imread(cv.samples.findFile(img_path, False)) |
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if image is None: |
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print("Error: unable to open video/image source") |
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sys.exit(0) |
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while image is not None: |
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image_copy = np.copy(image) |
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charuco_corners, charuco_ids, marker_corners, marker_ids = charuco_detector.detectBoard(image) |
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if not (marker_ids is None) and len(marker_ids) > 0: |
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cv.aruco.drawDetectedMarkers(image_copy, marker_corners) |
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if not (charuco_ids is None) and len(charuco_ids) > 0: |
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cv.aruco.drawDetectedCornersCharuco(image_copy, charuco_corners, charuco_ids) |
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if len(cam_matrix) > 0 and len(charuco_ids) >= 4: |
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try: |
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obj_points, img_points = board.matchImagePoints(charuco_corners, charuco_ids) |
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flag, rvec, tvec = cv.solvePnP(obj_points, img_points, cam_matrix, dist_coefficients) |
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if flag: |
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cv.drawFrameAxes(image_copy, cam_matrix, dist_coefficients, rvec, tvec, .2) |
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except cv.error as error_inst: |
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print("SolvePnP recognize calibration pattern as non-planar pattern. To process this need to use " |
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"minimum 6 points. The planar pattern may be mistaken for non-planar if the pattern is " |
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"deformed or incorrect camera parameters are used.") |
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print(error_inst.err) |
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cv.imshow("out", image_copy) |
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key = cv.waitKey(wait_time) |
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if key == 27: |
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break |
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image = input_video.retrieve()[1] if input_video is not None and input_video.grab() else None |
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if __name__ == "__main__": |
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main()
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