This commit is contained in:
2024-11-21 18:28:32 +08:00
parent 6be586a26e
commit 3ca9712cdd
2 changed files with 218 additions and 34 deletions

167
.gitignore vendored
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@ -1,2 +1,167 @@
*.jpg *.jpg
*.jpeg *.jpeg
*.pdf
*.png
# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class
# C extensions
*.so
# Distribution / packaging
.Python
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
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var/
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share/python-wheels/
*.egg-info/
.installed.cfg
*.egg
MANIFEST
# PyInstaller
# Usually these files are written by a python script from a template
# before PyInstaller builds the exe, so as to inject date/other infos into it.
*.manifest
*.spec
# Installer logs
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# Unit test / coverage reports
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.tox/
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.coverage
.coverage.*
.cache
nosetests.xml
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*.cover
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.hypothesis/
.pytest_cache/
cover/
# Translations
*.mo
*.pot
# Django stuff:
*.log
local_settings.py
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db.sqlite3-journal
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# For a library or package, you might want to ignore these files since the code is
# intended to run in multiple environments; otherwise, check them in:
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# However, in case of collaboration, if having platform-specific dependencies or dependencies
# having no cross-platform support, pipenv may install dependencies that don't work, or not
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# This is especially recommended for binary packages to ensure reproducibility, and is more
# commonly ignored for libraries.
# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
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# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
#pdm.lock
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*.sage.py
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.env
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# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
# and can be added to the global gitignore or merged into this file. For a more nuclear
# option (not recommended) you can uncomment the following to ignore the entire idea folder.
#.idea/

85
test.py
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@ -3,6 +3,8 @@ from cv2 import aruco
from cv2.typing import MatLike from cv2.typing import MatLike
from enum import Enum from enum import Enum
from pathlib import Path from pathlib import Path
from loguru import logger
from itertools import chain
class ArucoDictionary(Enum): class ArucoDictionary(Enum):
@ -36,46 +38,63 @@ def create_charuco_board(
marker_length: float, marker_length: float,
dictionary: aruco.Dictionary, dictionary: aruco.Dictionary,
) -> aruco.CharucoBoard: ) -> aruco.CharucoBoard:
return aruco.CharucoBoard( # type: ignore return aruco.CharucoBoard( # type: ignore
(square_x, square_y), square_length, marker_length, dictionary (square_x, square_y), square_length, marker_length, dictionary
) )
IMAGE_PATH= Path("/Users/crosstyan/Downloads/IMG_1505.jpeg")
# IMAGE_PATH = Path("/Users/crosstyan/Downloads/IMG_1505.jpeg")
# IMAGE_PATH = Path("ss.png")
IMAGE_FOLDER = Path("at")
OUTPUT_FOLDER = Path("output")
DICTIONARY = ArucoDictionary.Dict_4X4_50
def main(): def main():
img: MatLike OUTPUT_FOLDER.mkdir(exist_ok=True)
img = cv2.imread(str(IMAGE_PATH)) images = chain(IMAGE_FOLDER.glob("*.jpeg"), IMAGE_FOLDER.glob("*.png"), IMAGE_FOLDER.glob("*.jpg"))
# 10x7 for img_path in images:
border_num_x = 10 img = cv2.imread(str(img_path))
border_num_y = 7 # 10x7
# 115mm square # minus 1
# 90mm marker border_num_x = 9
dictionary = ArucoDictionary.Dict_4X4_50 border_num_y = 6
predifined = aruco.getPredefinedDictionary(dictionary.value) # 115mm square
# https://docs.opencv.org/4.x/d9/d6a/group__aruco.html#ga3bc50d61fe4db7bce8d26d56b5a6428a # 90mm marker
# https://docs.opencv.org/4.x/df/d4a/tutorial_charuco_detection.html # https://docs.opencv.org/4.x/d9/d6a/group__aruco.html#ga3bc50d61fe4db7bce8d26d56b5a6428a
# https://docs.opencv.org/3.4/df/d4a/tutorial_charuco_detection.html # https://docs.opencv.org/4.x/df/d4a/tutorial_charuco_detection.html
# https://docs.opencv.org/4.x/dc/dbb/tutorial_py_calibration.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) # https://docs.opencv.org/4.x/d9/d0c/group__calib3d.html#ga93efa9b0aa890de240ca32b11253dd4a
ret, chess_corners = cv2.findChessboardCorners(gray, (border_num_x, border_num_y), None) # https://docs.opencv.org/4.x/da/d13/tutorial_aruco_calibration.html
if ret: # https://github.com/opencv/opencv/issues/22083
cv2.drawChessboardCorners(img, (border_num_x, border_num_y), chess_corners, ret) ret, chess_corners = cv2.findChessboardCorners(
cv2.imwrite("output.jpg", img) img,
else: (border_num_x, border_num_y),
print("not found") flags=cv2.CALIB_CB_ADAPTIVE_THRESH
| cv2.CALIB_CB_NORMALIZE_IMAGE
| cv2.CALIB_CB_FAST_CHECK,
)
if ret:
cv2.drawChessboardCorners(
img, (border_num_x, border_num_y), chess_corners, ret
)
cv2.imwrite(str(OUTPUT_FOLDER / f"{img_path.stem}_chess.jpg"), img)
logger.info("Chessboard found for {}", img_path)
else:
logger.warning("Chessboard not found for {}", img_path)
# predefined_dict = aruco.getPredefinedDictionary(DICTIONARY.value)
# corners, ids, rejected = aruco.detectMarkers(img, predefined_dict)
# board = create_charuco_board(10, 7, 115, 90, predefined_dict)
# detector = aruco.CharucoDetector(board)
# if ids is not None:
# aruco.drawDetectedMarkers(img, corners, ids)
# ret, 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)
# 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__": if __name__ == "__main__":
main() main()