52 lines
1.7 KiB
Python
52 lines
1.7 KiB
Python
#!/usr/bin/env python
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import cv2
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import pickle
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import numpy as np
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min_size=50
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face_cascade= cv2.CascadeClassifier("server-ia/data/haarcascades/haarcascade_frontalface_alt2.xml")
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recognizer=cv2.face.LBPHFaceRecognizer_create()
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recognizer.read("server-ia/data/modeles/camera_identification_user/trainner.yml")
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id_image=0
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color_info=(255, 255, 255)
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color_ko=(0, 0, 255)
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color_ok=(0, 255, 0)
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url = "http://192.168.52.194:8081"
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with open("server-ia/data/modeles/camera_identification_user/labels.pickle", "rb") as f:
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og_labels=pickle.load(f)
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labels={v:k for k, v in og_labels.items()}
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cap=cv2.VideoCapture(0)
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while True:
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ret, frame=cap.read()
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tickmark=cv2.getTickCount()
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gray=cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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faces=face_cascade.detectMultiScale(gray, scaleFactor=1.2,minNeighbors=4, minSize=(min_size, min_size))
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for (x, y, w, h) in faces:
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roi_gray=gray[y:y+h, x:x+w]
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#id_, conf=recognizer.predict(cv2.resize(roi_gray, (min_size, min_size)))
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id_, conf=recognizer.predict(roi_gray)
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if conf<=95:
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color=color_ok
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name=labels[id_]
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else:
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color=color_ko
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name="Inconnu"
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label=name+" "+'{:5.2f}'.format(conf)
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cv2.putText(frame, label, (x, y-10), cv2.FONT_HERSHEY_DUPLEX, 1, color_info, 1, cv2.LINE_AA)
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cv2.rectangle(frame, (x, y), (x+w, y+h), color, 2)
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fps=cv2.getTickFrequency()/(cv2.getTickCount()-tickmark)
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cv2.putText(frame, "FPS: {:05.2f}".format(fps), (10, 30), cv2.FONT_HERSHEY_PLAIN, 2, color_info, 2)
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cv2.imshow('L42Project', frame)
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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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if key==ord('a'):
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for cpt in range(100):
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ret, frame=cap.read()
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cv2.destroyAllWindows()
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print("Fin")
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