import cv2
import numpy as np
from scipy.spatial.distance import pdist,squareform
from matplotlib import pyplot as plt
from skimage.transform import resize
if __name__=='__main__':
    picture_with_face_path=r'IlanAtCampNou.jpg'
    video_path=r'Hightechzone_video.mp4'
    face_cascade1 = cv2.CascadeClassifier(r'lbpcascade_frontalface_improved.xml')
    face_cascade2=cv2.CascadeClassifier(r'haarcascade_frontalface_default.xml')
    capture = cv2.VideoCapture(video_path)

    width = capture.get(cv2.CAP_PROP_FRAME_WIDTH)
    height =capture.get(cv2.CAP_PROP_FRAME_HEIGHT)
    fps = capture.get(cv2.CAP_PROP_FPS)

    fourcc = cv2.VideoWriter_fourcc(*'XVID')

    out = cv2.VideoWriter('Output_video.avi',fourcc , fps, (int(width), int(height)))
    image=cv2.imread(picture_with_face_path)
    distance_threshold = 50
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    faces = face_cascade1.detectMultiScale(gray, 1.5, 5)
    for (x, y, w, h) in faces:
        cv2.rectangle(image, (x, y), (x + w, y + h), (255, 0, 0), 2)

        Ilan_color = image[y:y + h, x:x + w]

    ret,im = capture.read()
    while(ret):
        gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
        if np.any(gray):
            faces1 = face_cascade1.detectMultiScale(gray, 1.05,15)
            faces2 = face_cascade2.detectMultiScale(gray, 1.05,12)
            if (len(faces1)>0) & (len (faces2)>0):
                xs_ys_lengths_width=np.vstack((faces1,faces2))
                mean_points=np.array((xs_ys_lengths_width[:,0]+xs_ys_lengths_width[:,2]/2,xs_ys_lengths_width[:,1]+xs_ys_lengths_width[:,3]/2)).T
                distances=squareform(pdist(mean_points))
                if np.all(distances<distance_threshold):
                    faces=faces1 if len(faces1) >len(faces2) else faces2
                else:
                    needed_to_be_deleted=np.bitwise_xor(distances<distance_threshold,np.eye(distances.shape[0]).astype(np.bool))
                    indices=np.argwhere(needed_to_be_deleted)
                    if len(indices)>0:
                        try:
                            indices=indices[indices[:,0]>indices[:,1]]

                            for ind in indices[:,0]:
                                xs_ys_lengths_width=np.delete(xs_ys_lengths_width,ind,axis=0)
                        except:
                            print('Error is here')
                    faces=xs_ys_lengths_width
            else:
                faces=faces1 if len(faces1) else faces2
            for (x, y, w, h) in faces:
                face_1=resize(Ilan_color,(h,w))
                im[y:y + h, x:x + w]=(255*face_1).astype(np.uint8)

            # for (x, y, w, h) in faces_at_profile:
            #     face_1=resize(Ilan_color,(h,w))
            #     im[y:y + h, x:x + w]=(255*face_1).astype(np.uint8)
            out.write(im)
        ret, im = capture.read()
    capture.release()
    out.release()
    cv2.imshow('img', image)
    cv2.waitKey(0)
    cv2.destroyAllWindows()