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https://github.com/modelec/detection_pot.git
synced 2026-01-18 16:47:33 +01:00
Distance du tag aruco
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45
aruco.py
45
aruco.py
@@ -1,10 +1,23 @@
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import cv2 as cv
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import cv2.aruco as aruco
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import numpy as np
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# Taille du tag aruco
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ARUCO_WIDTH = 2.5
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# Focal de la cam
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# Calculer la focal avec le fichier get_the_focal.py
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FOCAL_LENGTH = 600
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arucoTagMapping = {
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47: ["Solar Panel", 2.2],
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36: ["White flower", 2.5],
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13: ["Purple Flower", 1.8]
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}
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# Charger une image depuis la caméra (0 pour la caméra par défaut, généralement la webcam)
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cap = cv.VideoCapture(0)
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# Définir le dictionnaire ArUco
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aruco_dict = aruco.getPredefinedDictionary(aruco.DICT_4X4_50)
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@@ -12,7 +25,7 @@ aruco_dict = aruco.getPredefinedDictionary(aruco.DICT_4X4_50)
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parameters = aruco.DetectorParameters()
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#
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detector = aruco.ArucoDetector(aruco_dict,parameters)
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detector = aruco.ArucoDetector(aruco_dict, parameters)
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while True:
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# Lire une image depuis la caméra
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@@ -28,6 +41,32 @@ while True:
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if ids is not None:
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aruco.drawDetectedMarkers(frame, corners, ids)
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for i in range(len(ids)):
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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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if markerID not in arucoTagMapping:
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continue
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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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# Calculate the apparent width in pixels
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P = np.sqrt((topRight[0] - topLeft[0]) ** 2 + (topRight[1] - topLeft[1]) ** 2)
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# Calculate the distance to the Aruco tag
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D = (arucoTagMapping[markerID][1] * FOCAL_LENGTH) / P
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print(f"Distance to : {arucoTagMapping[markerID][0]} : {D} cm")
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# Afficher l'image
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cv.imshow('Frame', frame)
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@@ -37,4 +76,4 @@ while True:
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# Libérer la capture et fermer la fenêtre
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cap.release()
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cv.destroyAllWindows()
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cv.destroyAllWindows()
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