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**Aruco Marker Detection** | ||
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**GOAL** | ||
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To Detect Aruco markers and their id from the dataset. | ||
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**DESCRIPTION** | ||
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The main aim of the project is to detect aruco markers in the images. | ||
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**Preprocessing** | ||
Resized image for better accuracy. | ||
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**Libraries Used** | ||
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* cv2 | ||
* cv2.aruco | ||
* os | ||
* numpy | ||
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**WORK DONE** | ||
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1. Loaded images from the dataset folder. | ||
2. Reshaped and copied original image. | ||
3. Using open cv's aruco library, detected and drawn markers on the image. |
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# importing libraries | ||
import cv2 as cv | ||
import os | ||
import numpy as np | ||
import cv2.aruco as aruco | ||
# import matplotlib.pyplot as plt | ||
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# Creating list of all dictionary to make sure all the markers get detected | ||
dic_list = [ | ||
aruco.DICT_4X4_50, | ||
aruco.DICT_4X4_100, | ||
aruco.DICT_4X4_250, | ||
aruco.DICT_4X4_1000, | ||
aruco.DICT_4X4_100, | ||
aruco.DICT_4X4_250, | ||
aruco.DICT_4X4_1000, | ||
aruco.DICT_4X4_100, | ||
aruco.DICT_4X4_250, | ||
aruco.DICT_4X4_1000, | ||
aruco.DICT_4X4_100, | ||
aruco.DICT_4X4_250, | ||
aruco.DICT_4X4_1000, | ||
aruco.DICT_4X4_100, | ||
aruco.DICT_4X4_250, | ||
aruco.DICT_4X4_1000, | ||
aruco.DICT_5X5_50, | ||
aruco.DICT_5X5_100, | ||
aruco.DICT_5X5_250, | ||
aruco.DICT_5X5_1000, | ||
aruco.DICT_6X6_50, | ||
aruco.DICT_6X6_100, | ||
aruco.DICT_6X6_250, | ||
aruco.DICT_6X6_1000, | ||
aruco.DICT_7X7_50, | ||
aruco.DICT_7X7_100, | ||
aruco.DICT_7X7_250, | ||
aruco.DICT_7X7_1000, | ||
aruco.DICT_ARUCO_ORIGINAL, | ||
aruco.DICT_APRILTAG_16h5, | ||
aruco.DICT_APRILTAG_25h9, | ||
aruco.DICT_APRILTAG_36h10, | ||
aruco.DICT_APRILTAG_36h11, | ||
] | ||
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# Path to the folder | ||
folder_path = "Dataset" | ||
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# Initializing aruco dictionary | ||
aruco_dict = aruco.Dictionary_get(aruco.DICT_4X4_250) | ||
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# Initializing detector parameters | ||
parameters = aruco.DetectorParameters_create() | ||
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# Accessing each image | ||
for image_item in os.listdir(path= folder_path): | ||
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img_path = os.path.join(folder_path, image_item) | ||
img = cv.imread(str(img_path)) | ||
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img = cv.resize(img, (250, 250), interpolation=cv.INTER_AREA) | ||
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#Creating copy of the image | ||
img_copy = img | ||
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cv.waitKey(0) | ||
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# Got the image now converting it to grayscale | ||
gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY) | ||
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aruco_ids = set() | ||
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for dic in dic_list: | ||
aruco_dict = aruco.Dictionary_get(dic) | ||
corners, ids, rejectedImgPoints = aruco.detectMarkers(gray, aruco_dict, parameters=parameters) | ||
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if ids is not None: | ||
aruco.drawDetectedMarkers(img, corners, ids) | ||
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# Adding ids to the set | ||
ids = np.ravel(ids) | ||
for id in ids: | ||
aruco_ids.add(id) | ||
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# print(f""" | ||
# corners = {corners} | ||
# ids = {ids} | ||
# rejected = {rejectedImgPoints} | ||
# """) | ||
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if not aruco_ids: | ||
print("Not able to detect.") | ||
else: | ||
print(f"Detected Ids: {aruco_ids}") | ||
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# Displaying the marked image | ||
cv.imshow("Original Image", img_copy) | ||
cv.imshow('ArUco Marked Image', img) | ||
# cv.waitKey(0) | ||
# Break the loop when 'q' key is pressed | ||
if cv.waitKey(0) & 0xFF == ord('q'): | ||
break |