import numpy as np
import cv2
import pickle

face_cascade=cv2.CascadeClassifier('cascades/data/haarcascade_frontalface_alt2.xml')
eye_cascade=cv2.CascadeClassifier('cascades/data/haarcascade_eye.xml')
smile_cascade=cv2.CascadeClassifier('cascades/data/haarcascade_smile.xml')

recognizer=cv2.face.LBPHFaceRecognizer_create()
recognizer.read("trainner.yml")
labels={"person's name":1}
with open("labels.pickle",'rb') as f:
    og_labels=pickle.load(f)
    labels={v:k for k, v in og_labels.items() }


cap=cv2.VideoCapture(0)

while(True):
    #capture frame by frame
    ret,frame=cap.read()
    gray=cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    faces=face_cascade.detectMultiScale(gray,scaleFactor=1.5,minNeighbors=1)
    for(x,y,w,h) in faces:
        #print(x,y,w,h)
        roi_gray=gray[y:y+h,x:x+w] #(ycord_start, ycord_end)
        roi_color=frame[y:y+h,x:x+w]

        #recognize? deep learned model predict keras tensorflow pytorch scikit learn

        id_,conf=recognizer.predict(roi_gray)
        if conf>=4 and conf<=85:
            #print(id_)
            #print(labels[id_])
            font=cv2.FONT_HERSHEY_SIMPLEX
            name=labels[id_]
            color=(255, 255, 255)
            stroke=2
            cv2.putText(frame, name,(x,y), font,1,color,stroke,cv2.LINE_AA)
            
        img_item="7.png"
        cv2.imwrite(img_item,roi_gray)
        color=(255,0,0)#BGR 0-255
        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)
        #eyes=eye_cascade.detectMultiScale(roi_gray)
        #for(ex,ey,ew,eh) in eyes:
         #   cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)
            
        subitems=smile_cascade.detectMultiScale(roi_gray)
        for(sx,sy,sw,sh) in subitems:
            cv2.rectangle(roi_color,(sx,sy),(sx+sw,sy+sh),(0,255,0),2)
            
    #display the resulting frame
    cv2.imshow('frame',frame)
    if cv2.waitKey(20)&0xFF==ord('q'):
        break

#when everything done then release the capture.
cap.release()
cv2.destroyAllWindows()    
    
    
