mirror of
https://github.com/modelec/detection_pot.git
synced 2026-01-18 16:47:33 +01:00
70 lines
2.2 KiB
Python
70 lines
2.2 KiB
Python
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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# Actual width of the Aruco tag in some unit (like centimeters)
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W = 1.8
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# Actual distance from the camera to the object in the same unit as W
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D = 15.0
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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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# Créer le détecteur ArUco
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parameters = aruco.DetectorParameters()
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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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ret, frame = cap.read()
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# Convertir l'image en niveaux de gris
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gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
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# Détecter les marqueurs ArUco
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corners, ids, rejectedImgPoints = detector.detectMarkers(gray)
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# Dessiner les résultats
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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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# verify *at least* one ArUco marker was detected
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if len(corners) > 0:
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# Flatten the ArUco IDs list
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ids = ids.flatten()
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# Loop over the detected ArUCo corners
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for (markerCorners, markerID) in zip(corners, ids):
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# Extract the marker corners
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corners = markerCorners.reshape((4, 2))
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(topLeft, topRight, bottomRight, bottomLeft) = corners
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# Convert each of the (x, y)-coordinate pairs to integers
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topRight = (int(topRight[0]), int(topRight[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 focal length
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F = (P * D) / W
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print(f"The focal length of the camera is: {F} pixels")
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# Afficher l'image
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cv.imshow('Frame', frame)
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# Sortir de la boucle si la touche 'q' est enfoncée
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if cv.waitKey(1) & 0xFF == ord('q'):
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break
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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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