101 lines
3.7 KiB
Python
101 lines
3.7 KiB
Python
import cv2
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from cv2 import aruco
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from cv2.typing import MatLike
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from enum import Enum
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from pathlib import Path
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from loguru import logger
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from itertools import chain
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class ArucoDictionary(Enum):
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Dict_4X4_50 = aruco.DICT_4X4_50
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Dict_4X4_100 = aruco.DICT_4X4_100
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Dict_4X4_250 = aruco.DICT_4X4_250
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Dict_4X4_1000 = aruco.DICT_4X4_1000
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Dict_5X5_50 = aruco.DICT_5X5_50
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Dict_5X5_100 = aruco.DICT_5X5_100
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Dict_5X5_250 = aruco.DICT_5X5_250
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Dict_5X5_1000 = aruco.DICT_5X5_1000
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Dict_6X6_50 = aruco.DICT_6X6_50
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Dict_6X6_100 = aruco.DICT_6X6_100
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Dict_6X6_250 = aruco.DICT_6X6_250
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Dict_6X6_1000 = aruco.DICT_6X6_1000
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Dict_7X7_50 = aruco.DICT_7X7_50
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Dict_7X7_100 = aruco.DICT_7X7_100
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Dict_7X7_250 = aruco.DICT_7X7_250
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Dict_7X7_1000 = aruco.DICT_7X7_1000
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Dict_APRILTAG_16h5 = aruco.DICT_APRILTAG_16h5
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Dict_APRILTAG_25h9 = aruco.DICT_APRILTAG_25h9
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Dict_APRILTAG_36h10 = aruco.DICT_APRILTAG_36h10
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Dict_APRILTAG_36h11 = aruco.DICT_APRILTAG_36h11
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Dict_ArUco_ORIGINAL = aruco.DICT_ARUCO_ORIGINAL
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def create_charuco_board(
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square_x: int,
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square_y: int,
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square_length: float,
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marker_length: float,
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dictionary: aruco.Dictionary,
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) -> aruco.CharucoBoard:
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return aruco.CharucoBoard( # type: ignore
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(square_x, square_y), square_length, marker_length, dictionary
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)
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# IMAGE_PATH = Path("/Users/crosstyan/Downloads/IMG_1505.jpeg")
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# IMAGE_PATH = Path("ss.png")
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IMAGE_FOLDER = Path("at")
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OUTPUT_FOLDER = Path("output")
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DICTIONARY = ArucoDictionary.Dict_4X4_50
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def main():
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OUTPUT_FOLDER.mkdir(exist_ok=True)
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images = chain(IMAGE_FOLDER.glob("*.jpeg"), IMAGE_FOLDER.glob("*.png"), IMAGE_FOLDER.glob("*.jpg"))
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for img_path in images:
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img = cv2.imread(str(img_path))
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# 10x7
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# minus 1
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border_num_x = 9
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border_num_y = 6
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# 115mm square
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# 90mm marker
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# https://docs.opencv.org/4.x/d9/d6a/group__aruco.html#ga3bc50d61fe4db7bce8d26d56b5a6428a
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# https://docs.opencv.org/4.x/df/d4a/tutorial_charuco_detection.html
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# https://docs.opencv.org/3.4/df/d4a/tutorial_charuco_detection.html
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# https://docs.opencv.org/4.x/dc/dbb/tutorial_py_calibration.html
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# https://docs.opencv.org/4.x/d9/d0c/group__calib3d.html#ga93efa9b0aa890de240ca32b11253dd4a
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# https://docs.opencv.org/4.x/da/d13/tutorial_aruco_calibration.html
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# https://github.com/opencv/opencv/issues/22083
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ret, chess_corners = cv2.findChessboardCorners(
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img,
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(border_num_x, border_num_y),
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flags=cv2.CALIB_CB_ADAPTIVE_THRESH
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| cv2.CALIB_CB_NORMALIZE_IMAGE
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| cv2.CALIB_CB_FAST_CHECK,
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)
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if ret:
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cv2.drawChessboardCorners(
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img, (border_num_x, border_num_y), chess_corners, ret
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)
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cv2.imwrite(str(OUTPUT_FOLDER / f"{img_path.stem}_chess.jpg"), img)
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logger.info("Chessboard found for {}", img_path)
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else:
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logger.warning("Chessboard not found for {}", img_path)
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# predefined_dict = aruco.getPredefinedDictionary(DICTIONARY.value)
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# corners, ids, rejected = aruco.detectMarkers(img, predefined_dict)
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# board = create_charuco_board(10, 7, 115, 90, predefined_dict)
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# detector = aruco.CharucoDetector(board)
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# if ids is not None:
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# aruco.drawDetectedMarkers(img, corners, ids)
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# ret, ch_corners, ch_ids = aruco.interpolateCornersCharuco(corners, ids, img, board)
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# if ch_corners is not None and ch_ids is not None:
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# aruco.drawDetectedCornersCharuco(img, ch_corners, ch_ids)
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# cv2.imwrite("output.jpg", img)
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if __name__ == "__main__":
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main()
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