82 lines
2.8 KiB
Python
82 lines
2.8 KiB
Python
import cv2
|
|
from cv2 import aruco
|
|
from cv2.typing import MatLike
|
|
from enum import Enum
|
|
from pathlib import Path
|
|
|
|
|
|
class ArucoDictionary(Enum):
|
|
Dict_4X4_50 = aruco.DICT_4X4_50
|
|
Dict_4X4_100 = aruco.DICT_4X4_100
|
|
Dict_4X4_250 = aruco.DICT_4X4_250
|
|
Dict_4X4_1000 = aruco.DICT_4X4_1000
|
|
Dict_5X5_50 = aruco.DICT_5X5_50
|
|
Dict_5X5_100 = aruco.DICT_5X5_100
|
|
Dict_5X5_250 = aruco.DICT_5X5_250
|
|
Dict_5X5_1000 = aruco.DICT_5X5_1000
|
|
Dict_6X6_50 = aruco.DICT_6X6_50
|
|
Dict_6X6_100 = aruco.DICT_6X6_100
|
|
Dict_6X6_250 = aruco.DICT_6X6_250
|
|
Dict_6X6_1000 = aruco.DICT_6X6_1000
|
|
Dict_7X7_50 = aruco.DICT_7X7_50
|
|
Dict_7X7_100 = aruco.DICT_7X7_100
|
|
Dict_7X7_250 = aruco.DICT_7X7_250
|
|
Dict_7X7_1000 = aruco.DICT_7X7_1000
|
|
Dict_APRILTAG_16h5 = aruco.DICT_APRILTAG_16h5
|
|
Dict_APRILTAG_25h9 = aruco.DICT_APRILTAG_25h9
|
|
Dict_APRILTAG_36h10 = aruco.DICT_APRILTAG_36h10
|
|
Dict_APRILTAG_36h11 = aruco.DICT_APRILTAG_36h11
|
|
Dict_ArUco_ORIGINAL = aruco.DICT_ARUCO_ORIGINAL
|
|
|
|
|
|
def create_charuco_board(
|
|
square_x: int,
|
|
square_y: int,
|
|
square_length: float,
|
|
marker_length: float,
|
|
dictionary: aruco.Dictionary,
|
|
) -> aruco.CharucoBoard:
|
|
return aruco.CharucoBoard( # type: ignore
|
|
(square_x, square_y), square_length, marker_length, dictionary
|
|
)
|
|
|
|
IMAGE_PATH= Path("/Users/crosstyan/Downloads/IMG_1505.jpeg")
|
|
|
|
def main():
|
|
img: MatLike
|
|
img = cv2.imread(str(IMAGE_PATH))
|
|
# 10x7
|
|
border_num_x = 10
|
|
border_num_y = 7
|
|
# 115mm square
|
|
# 90mm marker
|
|
dictionary = ArucoDictionary.Dict_4X4_50
|
|
predifined = aruco.getPredefinedDictionary(dictionary.value)
|
|
# https://docs.opencv.org/4.x/d9/d6a/group__aruco.html#ga3bc50d61fe4db7bce8d26d56b5a6428a
|
|
# https://docs.opencv.org/4.x/df/d4a/tutorial_charuco_detection.html
|
|
# https://docs.opencv.org/3.4/df/d4a/tutorial_charuco_detection.html
|
|
# https://docs.opencv.org/4.x/dc/dbb/tutorial_py_calibration.html
|
|
|
|
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
|
|
ret, chess_corners = cv2.findChessboardCorners(gray, (border_num_x, border_num_y), None)
|
|
if ret:
|
|
cv2.drawChessboardCorners(img, (border_num_x, border_num_y), chess_corners, ret)
|
|
cv2.imwrite("output.jpg", img)
|
|
else:
|
|
print("not found")
|
|
|
|
# corners, ids, rejected = aruco.detectMarkers(img, predifined)
|
|
# board = create_charuco_board(10, 7, 115, 90, predifined)
|
|
# detector = aruco.CharucoDetector(board)
|
|
# if ids is not None:
|
|
# aruco.drawDetectedMarkers(img, corners, ids)
|
|
# _, ch_corners, ch_ids = aruco.interpolateCornersCharuco(corners, ids, img, board)
|
|
# if ch_corners is not None and ch_ids is not None:
|
|
# aruco.drawDetectedCornersCharuco(img, ch_corners, ch_ids)
|
|
# cv2.imwrite("output.jpg", img)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|
|
|