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‎scripts/arucoDetection.py

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import numpy as np
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import time
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import cv2
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ARUCO_DICT = {
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"DICT_4X4_50": cv2.aruco.DICT_4X4_50,
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"DICT_4X4_100": cv2.aruco.DICT_4X4_100,
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"DICT_4X4_250": cv2.aruco.DICT_4X4_250,
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"DICT_4X4_1000": cv2.aruco.DICT_4X4_1000,
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"DICT_5X5_50": cv2.aruco.DICT_5X5_50,
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"DICT_5X5_100": cv2.aruco.DICT_5X5_100,
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"DICT_5X5_250": cv2.aruco.DICT_5X5_250,
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"DICT_5X5_1000": cv2.aruco.DICT_5X5_1000,
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"DICT_6X6_50": cv2.aruco.DICT_6X6_50,
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"DICT_6X6_100": cv2.aruco.DICT_6X6_100,
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"DICT_6X6_250": cv2.aruco.DICT_6X6_250,
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"DICT_6X6_1000": cv2.aruco.DICT_6X6_1000,
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"DICT_7X7_50": cv2.aruco.DICT_7X7_50,
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"DICT_7X7_100": cv2.aruco.DICT_7X7_100,
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"DICT_7X7_250": cv2.aruco.DICT_7X7_250,
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"DICT_7X7_1000": cv2.aruco.DICT_7X7_1000,
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"DICT_ARUCO_ORIGINAL": cv2.aruco.DICT_ARUCO_ORIGINAL,
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"DICT_APRILTAG_16h5": cv2.aruco.DICT_APRILTAG_16h5,
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"DICT_APRILTAG_25h9": cv2.aruco.DICT_APRILTAG_25h9,
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"DICT_APRILTAG_36h10": cv2.aruco.DICT_APRILTAG_36h10,
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"DICT_APRILTAG_36h11": cv2.aruco.DICT_APRILTAG_36h11
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}
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def aruco_display(corners, ids, rejected, image):
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if len(corners) > 0:
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ids = ids.flatten()
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for (markerCorner, markerID) in zip(corners, ids):
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corners = markerCorner.reshape((4, 2))
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(topLeft, topRight, bottomRight, bottomLeft) = corners
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topRight = (int(topRight[0]), int(topRight[1]))
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bottomRight = (int(bottomRight[0]), int(bottomRight[1]))
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bottomLeft = (int(bottomLeft[0]), int(bottomLeft[1]))
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topLeft = (int(topLeft[0]), int(topLeft[1]))
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cv2.line(image, topLeft, topRight, (0, 255, 0), 2)
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cv2.line(image, topRight, bottomRight, (0, 255, 0), 2)
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cv2.line(image, bottomRight, bottomLeft, (0, 255, 0), 2)
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cv2.line(image, bottomLeft, topLeft, (0, 255, 0), 2)
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cX = int((topLeft[0] + bottomRight[0]) / 2.0)
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cY = int((topLeft[1] + bottomRight[1]) / 2.0)
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cv2.circle(image, (cX, cY), 4, (0, 0, 255), -1)
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cv2.putText(image, str(markerID),(topLeft[0], topLeft[1] - 10), cv2.FONT_HERSHEY_SIMPLEX,
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0.5, (0, 255, 0), 2)
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print("[Inference] ArUco marker ID: {}".format(markerID))
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return image
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aruco_type = "DICT_5X5_100"
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arucoDict = cv2.aruco.Dictionary_get(ARUCO_DICT[aruco_type])
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arucoParams = cv2.aruco.DetectorParameters_create()
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cap = cv2.VideoCapture(0)
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cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1280)
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cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)
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while cap.isOpened():
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ret, img = cap.read()
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h, w, _ = img.shape
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width = 1000
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height = int(width*(h/w))
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img = cv2.resize(img, (width, height), interpolation=cv2.INTER_CUBIC)
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corners, ids, rejected = cv2.aruco.detectMarkers(img, arucoDict, parameters=arucoParams)
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detected_markers = aruco_display(corners, ids, rejected, img)
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cv2.imshow("Image", detected_markers)
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key = cv2.waitKey(1) & 0xFF
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if key == ord("q"):
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break
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cv2.destroyAllWindows()
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cap.release()

‎scripts/pose_estimation.py renamed to ‎scripts/arucoPoseEstimation.py

Lines changed: 14 additions & 14 deletions
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import time
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8-
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ARUCO_DICT = {
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"DICT_4X4_50": cv2.aruco.DICT_4X4_50,
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"DICT_4X4_100": cv2.aruco.DICT_4X4_100,
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def pose_estimation(frame, aruco_dict_type, matrix_coefficients, distortion_coefficients):
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gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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aruco_dict = cv2.aruco.Dictionary_get(aruco_dict_type) # Changed to use local variable
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cv2.aruco_dict = cv2.aruco.Dictionary_get(aruco_dict_type)
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parameters = cv2.aruco.DetectorParameters_create()
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corners, ids, rejected_img_points = cv2.aruco.detectMarkers(
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gray, aruco_dict, parameters=parameters,
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corners, ids, rejected_img_points = cv2.aruco.detectMarkers(gray, cv2.aruco_dict,parameters=parameters,
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cameraMatrix=matrix_coefficients,
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distCoeff=distortion_coefficients
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)
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distCoeff=distortion_coefficients)
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if len(corners) > 0:
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# Draw detected markers
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cv2.aruco.drawDetectedMarkers(frame, corners, ids)
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for i in range(len(ids)):
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rvec, tvec, _ = cv2.aruco.estimatePoseSingleMarkers(corners[i], 0.02, matrix_coefficients, distortion_coefficients)
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for i in range(0, len(ids)):
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rvec, tvec, markerPoints = cv2.aruco.estimatePoseSingleMarkers(corners[i], 0.02, matrix_coefficients,
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distortion_coefficients)
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cv2.aruco.drawDetectedMarkers(frame, corners)
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# Draw the axis for each marker
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cv2.aruco.drawAxis(frame, matrix_coefficients, distortion_coefficients, rvec, tvec, 0.01)
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cv2.aruco.drawAxis(frame, matrix_coefficients, distortion_coefficients, rvec, tvec, 0.01)
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return frame
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aruco_type = "DICT_5X5_100"

‎scripts/generateAruco.py

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import numpy as np
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import cv2
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ARUCO_DICT = {
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"DICT_4X4_50": cv2.aruco.DICT_4X4_50,
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"DICT_4X4_100": cv2.aruco.DICT_4X4_100,
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"DICT_4X4_250": cv2.aruco.DICT_4X4_250,
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"DICT_4X4_1000": cv2.aruco.DICT_4X4_1000,
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"DICT_5X5_50": cv2.aruco.DICT_5X5_50,
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"DICT_5X5_100": cv2.aruco.DICT_5X5_100,
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"DICT_5X5_250": cv2.aruco.DICT_5X5_250,
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"DICT_5X5_1000": cv2.aruco.DICT_5X5_1000,
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"DICT_6X6_50": cv2.aruco.DICT_6X6_50,
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"DICT_6X6_100": cv2.aruco.DICT_6X6_100,
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"DICT_6X6_250": cv2.aruco.DICT_6X6_250,
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"DICT_6X6_1000": cv2.aruco.DICT_6X6_1000,
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"DICT_7X7_50": cv2.aruco.DICT_7X7_50,
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"DICT_7X7_100": cv2.aruco.DICT_7X7_100,
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"DICT_7X7_250": cv2.aruco.DICT_7X7_250,
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"DICT_7X7_1000": cv2.aruco.DICT_7X7_1000,
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"DICT_ARUCO_ORIGINAL": cv2.aruco.DICT_ARUCO_ORIGINAL,
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"DICT_APRILTAG_16h5": cv2.aruco.DICT_APRILTAG_16h5,
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"DICT_APRILTAG_25h9": cv2.aruco.DICT_APRILTAG_25h9,
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"DICT_APRILTAG_36h10": cv2.aruco.DICT_APRILTAG_36h10,
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"DICT_APRILTAG_36h11": cv2.aruco.DICT_APRILTAG_36h11
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}
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aruco_type = "DICT_5X5_250"
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id = 1
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arucoDict = cv2.aruco.Dictionary_get(ARUCO_DICT[aruco_type])
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print("ArUCo type '{}' with ID '{}'".format(aruco_type, id))
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tag_size = 250
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tag = np.zeros((tag_size, tag_size, 1), dtype="uint8")
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cv2.aruco.drawMarker(arucoDict, id, tag_size, tag, 1)
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# Save the tag g
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# enerated
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tag_name = "arucoMarkers/" + aruco_type + "_" + str(id) + ".png"
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cv2.imwrite(tag_name, tag)
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cv2.imshow("ArUCo Tag", tag)
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cv2.waitKey(0)
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cv2.destroyAllWindows()

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