ReconocimientoGrayScale.py

import cv2 
import os 


dataPath = "data"
if not os.path.exists(dataPath):
    os.makedirs(dataPath)
imagePaths = os.listdir(dataPath)   
# print('imagePaths=', imagePaths)

face_recognizer = cv2.face.LBPHFaceRecognizer_create() 

#LECTURA DEL VIDEO 
face_recognizer.read('LBPH/modeloLBPHFace_.xml')
cap = cv2.VideoCapture(0)


faceClassif = cv2.CascadeClassifier(cv2.data.haarcascades+'haarcascade_frontalface_default.xml')
while True:
    ret,frame = cap.read() #videoCapture
    if ret == False: break
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    auxFrame = gray.copy()
    faces = faceClassif.detectMultiScale(gray,1.3,5)
    for (x,y,w,h) in faces:
        rostro = auxFrame[y:y+h,x:x+w]
        rostro = cv2.resize(rostro,(150,150),interpolation= cv2.INTER_CUBIC)
        result = face_recognizer.predict(rostro)
        cv2.putText(frame,'{}'.format(result),(x,y-5),1,1.3,(255,255,0),1,cv2.LINE_AA)


        #LBPHFace

        if result[1] < 70:
        
            cv2.putText(gray, '{}'.format(imagePaths[result[0]]),(x,y-25),2,1.1,
            (0,255,0),1,cv2.LINE_AA)
            cv2.rectangle(frame, (x,y),(x+w,y+h),(0,0,255),2)
        

        else: 
            cv2.putText(gray,'desconocido',(x,y-20),2,0.8,(0,0,255),2,cv2.LINE_AA)
            cv2.rectangle(frame, (x,y),(x+w,y+h),(0,0,255),2)


    # cv2.imshow('Reconocimiento Facial',frame)
    cv2.imshow('Reconocimiento Facial',gray)



    k = cv2.waitKey(1)
    if k == 27:
        
        break 

cap.release()
cv2.destroyAllWindows()