added aruco generate and detect

.gitignore

@@ -1 +1,2 @@
 results/
+__pycache__/

README.md

@@ -1,2 +1,6 @@
+# Checker board
 https://docs.opencv.org/4.x/d6/d55/tutorial_table_of_content_calib3d.html
 https://docs.opencv.org/4.x/d9/db7/tutorial_py_table_of_contents_calib3d.html
+
+# Aruco
+https://docs.opencv.org/4.x/d2/d64/tutorial_table_of_content_objdetect.html

aruco_detect.py

@@ -0,0 +1,85 @@
+import argparse
+import cv2
+import sys
+
+import cv2.aruco
+
+from aruco_types import ARUCO_DICT
+
+
+def im_resize(image, new_width: int):
+	# Define new width while maintaining the aspect ratio
+	aspect_ratio = new_width / image.shape[0]
+	new_height = int(image.shape[1] * aspect_ratio)  # Compute height based on aspect ratio
+
+	image = cv2.resize(image, (new_width, new_height))
+	return image
+
+def factory(aruco_type: int) -> cv2.aruco.ArucoDetector:
+	aruco_dict = cv2.aruco.getPredefinedDictionary(aruco_type)
+	aruco_params = cv2.aruco.DetectorParameters()
+	aruco_detector = cv2.aruco.ArucoDetector(aruco_dict, aruco_params)
+
+	return aruco_detector
+
+def process_video(aruco_detector: cv2.aruco.ArucoDetector):
+	# Open camera
+	video = cv2.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(aruco_detector, img)
+		k = cv2.waitKey(1) & 0xFF
+		if k == ord('q'):
+			break
+
+def process_still(aruco_detector, filename: str):
+	image = cv2.imread(filename)
+	image = im_resize(image, 600)
+	process(aruco_detector, image)
+	k = cv2.waitKey(-1) & 0xFF
+
+def process(aruco_detector, img):
+	(corners, ids, rejected) = aruco_detector.detectMarkers(img)
+	img = cv2.aruco.drawDetectedMarkers(img, corners, ids)
+	cv2.imshow("Image", img)
+
+def main():
+	# construct the argument parser and parse the arguments
+	ap = argparse.ArgumentParser()
+	ap.add_argument("-i", "--image",
+		help="path to input image containing ArUCo tag")
+	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"]))
+
+	aruco_detector = factory(ARUCO_DICT[args["type"]])
+
+	# load the input image from disk and resize it
+	print("[INFO] loading image...")
+
+	if args["image"] is not None:
+		process_still(aruco_detector, args["image"])
+	else:
+		process_video(aruco_detector)
+
+
+if __name__ == '__main__':
+	main()

aruco_gen.py

@@ -0,0 +1,51 @@
+import numpy as np
+import argparse
+import cv2
+import sys
+from aruco_types import ARUCO_DICT
+
+def generate(aruco_dict: cv2.aruco.Dictionary, tag_id: int, side_pixels: int = 300):
+	tag = np.zeros((side_pixels, side_pixels, 1), dtype="uint8")
+	cv2.aruco.generateImageMarker(aruco_dict, tag_id, side_pixels, tag, 1)
+
+	return tag
+
+def main():
+	# construct the argument parser and parse the arguments
+	ap = argparse.ArgumentParser()
+	ap.add_argument("-f", "--folder", required=True,
+					help="path to output image containing ArUCo tag")
+	ap.add_argument("-d", "--id", type=int, required=True,
+					help="ID of ArUCo tag to generate")
+	ap.add_argument("-t", "--type", type=str,
+					default="DICT_ARUCO_ORIGINAL",
+					help="type of ArUCo tag to generate")
+	ap.add_argument("-i", "--imagetype", type=str,
+					default="png",
+					help="image file type of ArUCo tag image")
+	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
+	aruco_dict = cv2.aruco.getPredefinedDictionary(ARUCO_DICT[args["type"]])
+
+	# allocate memory for the output ArUCo tag and then draw the ArUCo
+	# tag on the output image
+	print("[INFO] generating ArUCo tag type '{}' with ID '{}'".format(
+		args["type"], args["id"]))
+	tag = generate(aruco_dict, args["id"], 300)
+	# write the generated ArUCo tag to disk and then display it to our
+	# screen
+	filename = f"{args["folder"]}/{args["type"]}_ID_{args["id"]:04d}.{args["imagetype"]}"
+	cv2.imwrite(filename, tag)
+	cv2.imshow("ArUCo Tag", tag)
+	cv2.waitKey(0)
+
+if __name__ == '__main__':
+	main()

aruco_types.py

@@ -0,0 +1,25 @@
+import cv2
+
+ARUCO_DICT = {
+	"DICT_4X4_50": cv2.aruco.DICT_4X4_50,
+	"DICT_4X4_100": cv2.aruco.DICT_4X4_100,
+	"DICT_4X4_250": cv2.aruco.DICT_4X4_250,
+	"DICT_4X4_1000": cv2.aruco.DICT_4X4_1000,
+	"DICT_5X5_50": cv2.aruco.DICT_5X5_50,
+	"DICT_5X5_100": cv2.aruco.DICT_5X5_100,
+	"DICT_5X5_250": cv2.aruco.DICT_5X5_250,
+	"DICT_5X5_1000": cv2.aruco.DICT_5X5_1000,
+	"DICT_6X6_50": cv2.aruco.DICT_6X6_50,
+	"DICT_6X6_100": cv2.aruco.DICT_6X6_100,
+	"DICT_6X6_250": cv2.aruco.DICT_6X6_250,
+	"DICT_6X6_1000": cv2.aruco.DICT_6X6_1000,
+	"DICT_7X7_50": cv2.aruco.DICT_7X7_50,
+	"DICT_7X7_100": cv2.aruco.DICT_7X7_100,
+	"DICT_7X7_250": cv2.aruco.DICT_7X7_250,
+	"DICT_7X7_1000": cv2.aruco.DICT_7X7_1000,
+	"DICT_ARUCO_ORIGINAL": cv2.aruco.DICT_ARUCO_ORIGINAL,
+	"DICT_APRILTAG_16h5": cv2.aruco.DICT_APRILTAG_16h5,
+	"DICT_APRILTAG_25h9": cv2.aruco.DICT_APRILTAG_25h9,
+	"DICT_APRILTAG_36h10": cv2.aruco.DICT_APRILTAG_36h10,
+	"DICT_APRILTAG_36h11": cv2.aruco.DICT_APRILTAG_36h11
+}

cam_pose.py

@@ -14,7 +14,7 @@ def draw_gizmo(img, corners, imgpts):
 	return img
 
 
-def draw_cube(img, corners, imgpts):
+def draw_cube(img, imgpts):
 	imgpts = np.int32(imgpts).reshape(-1, 2)
 
 	# draw ground floor in green
@@ -29,7 +29,7 @@ def draw_cube(img, corners, imgpts):
 
 	return img
 
-def init_data():
+def factory():
 	criteria = (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_MAX_ITER, 30, 0.001)
 	objp = np.zeros((PAT_NX * PAT_NY, 3), np.float32)
 	objp[:, :2] = np.mgrid[0:PAT_NX, 0:PAT_NY].T.reshape(-1, 2)
@@ -46,7 +46,7 @@ def process_video():
 		mtx, dist, _, _ = [X[i] for i in ('mtx', 'dist', 'rvecs', 'tvecs')]
 
 	# Init
-	criteria, objp, axis = init_data()
+	criteria, objp, axis = factory()
 
 	# Open camera
 	video = cv.VideoCapture(0)
@@ -69,7 +69,7 @@ def process_still():
 		mtx, dist, _, _ = [X[i] for i in ('mtx', 'dist', 'rvecs', 'tvecs')]
 
 	# Init
-	criteria, objp, axis = init_data()
+	criteria, objp, axis = factory()
 
 	for fname in glob.glob('check*.jpg'):
 		img = cv.imread(fname)