videoFacial.py

import numpy as np
import cv2

#detection de face

face_cascade = cv2.CascadeClassifier("tools/data/haarcascade_frontalface_alt2.xml")
recognizer = cv2.face.LBPHFaceRecognizer_create()
recognizer.read("trainner.yml")
cap = cv2.VideoCapture(0)
while(True):

    ret, frame = cap.read()
    #facial recognition
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    faces = face_cascade.detectMultiScale(gray, scaleFactor=1.5, minNeighbors=5)

    for (x, y, w, h) in faces: 
        print(x,y,w,h)
        roi_gray = gray[y:y+h, x:x+w]
        roi_color = frame[y:y+h, x:x+w]
        
        id_, conf = recognizer.predict(roi_gray)
        if conf>= 45 and conf <= 85:
            print(id_)


        img_item = "myface.jpg"
        cv2.imwrite(img_item, roi_gray)

        color = (255, 0, 0)
        stroke = 2
        end_cord_x = x + w
        end_cord_y = y + h
        cv2.rectangle(frame, (x,y), (end_cord_x,end_cord_y),color,stroke)
    
    cv2.imshow('frame',frame)
    if cv2.waitKey(20) & 0xFF == ord('q'):
        break
        
cap.release()
cv2.destroyAllWindows()