aruco.py

import numpy as np
import cv2, PIL
from cv2 import aruco
import matplotlib.pyplot as plt
import matplotlib as mpl
import tkinter
import pandas as pd
import argparse


mpl.use('TKAgg')

ap = argparse.ArgumentParser()


def aruco_read(frame):
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    aruco_dict = aruco.Dictionary_get(aruco.DICT_ARUCO_ORIGINAL)
    parameters =  aruco.DetectorParameters_create()
    corners, ids, rejectedImgPoints = aruco.detectMarkers(gray, aruco_dict, parameters=parameters)
    frame_markers = aruco.drawDetectedMarkers(frame.copy(), corners, ids)
    
    return corners, ids, frame_markers   

def aruco_display(corners, ids, rejected, image):
	if len(corners) > 0:
		# flatten the ArUco IDs list
		ids = ids.flatten()
		# loop over the detected ArUCo corners
		for (markerCorner, markerID) in zip(corners, ids):
			# extract the marker corners (which are always returned in
			# top-left, top-right, bottom-right, and bottom-left order)
			corners = markerCorner.reshape((4, 2))
			(topLeft, topRight, bottomRight, bottomLeft) = corners
			# convert each of the (x, y)-coordinate pairs to integers
			topRight = (int(topRight[0]), int(topRight[1]))
			bottomRight = (int(bottomRight[0]), int(bottomRight[1]))
			bottomLeft = (int(bottomLeft[0]), int(bottomLeft[1]))
			topLeft = (int(topLeft[0]), int(topLeft[1]))

			cv2.line(image, topLeft, topRight, (0, 255, 0), 2)
			cv2.line(image, topRight, bottomRight, (0, 255, 0), 2)
			cv2.line(image, bottomRight, bottomLeft, (0, 255, 0), 2)
			cv2.line(image, bottomLeft, topLeft, (0, 255, 0), 2)
			# compute and draw the center (x, y)-coordinates of the ArUco
			# marker
			cX = int((topLeft[0] + bottomRight[0]) / 2.0)
			cY = int((topLeft[1] + bottomRight[1]) / 2.0)
			cv2.circle(image, (cX, cY), 4, (0, 0, 255), -1)
			# draw the ArUco marker ID on the image
			cv2.putText(image, str(markerID),(topLeft[0], topLeft[1] - 10), cv2.FONT_HERSHEY_SIMPLEX,
				0.5, (0, 255, 0), 2)
			print("[Inference] ArUco marker ID: {}".format(markerID))
			# show the output image
	return image

if __name__ == '__main__':
    ap.add_argument("-i", "--image", required=True,
	help="path to input image containing ArUCo tag")
    args = vars(ap.parse_args())
    frame = cv2.imread(args["image"])
    corners, ids, frame_markers = aruco_read(frame)
    plt.figure()
    plt.imshow(frame_markers)
    for i in range(len(ids)):
        c = corners[i][0]
        plt.plot([c[:, 0].mean()], [c[:, 1].mean()], "o", label = "id={0}".format(ids[i]))
    plt.legend()
    plt.show()