import os
import os.path
import numpy as np
import cv2
import argparse
import random
def resize(image, width=None, height=None, inter=cv2.INTER_AREA):
    dim = None
    (h, w) = image.shape[:2]
    if width is None and height is None:
        return image
    if width is None:
        r = height / float(h)
        dim = (int(w * r), height)
    else:
        r = width / float(w)
        dim = (width, int(h * r))
    resized = cv2.resize(image, dim, interpolation=inter)
    return resized
def getscore(gray,img):
    face_cascade = cv2.CascadeClassifier('./opencv_master/haarcascades/haarcascade_frontalface_default.xml')
    eye_cascade = cv2.CascadeClassifier('./opencv_master/haarcascades/haarcascade_eye.xml')
    faces = face_cascade.detectMultiScale(gray, 1.3, 5)
    facenum = len(faces)
    eyenums = 0
    for (x, y, w, h) in faces:
        img = cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
        roi_gray = gray[y:y + h, x:x + w]
        roi_color = img[y:y + h, x:x + w]
        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)
        eyenums += len(eyes)
    # print(eyenums,facenum)
    return (1-np.abs(facenum*2-eyenums)/(2*facenum))*0.2+0.8
    # cv2.imshow('img', img)
    # cv2.waitKey(0)
    # cv2.destroyAllWindows()
