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# -*- coding: utf-8 -*-
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"""
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Created on Thu Jul  2 03:40:59 2020
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@author: hp
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"""
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import cv2
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import dlib
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from mtcnn.mtcnn import MTCNN
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import numpy as np
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detector1 = MTCNN()
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detector2 = dlib.get_frontal_face_detector()
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modelFile = "models/res10_300x300_ssd_iter_140000.caffemodel"
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configFile = "models/deploy.prototxt.txt"
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net = cv2.dnn.readNetFromCaffe(configFile, modelFile)
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classifier2 = cv2.CascadeClassifier('models/haarcascade_frontalface2.xml')
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cap = cv2.VideoCapture('video/occlusion.mp4')
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font = cv2.FONT_HERSHEY_SIMPLEX 
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while(True):
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    ret, img = cap.read()
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    if ret == True:
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        img = cv2.resize(img, None, fx=0.5, fy=0.5)
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        height, width = img.shape[:2]
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        img1 = img.copy()
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        img2 = img.copy()
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        img3 = img.copy()
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        # detect faces in the image
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        faces1 = detector1.detect_faces(img)
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        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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        faces2 = detector2(gray, 1)
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        blob = cv2.dnn.blobFromImage(cv2.resize(img, (300, 300)),
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                                        1.0, (300, 300), (104.0, 117.0, 123.0))
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        net.setInput(blob)
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        faces3 = net.forward()
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        faces4 = classifier2.detectMultiScale(img)
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        # display faces on the original image
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        for result in faces1:
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            x, y, w, h = result['box']
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            x1, y1 = x + w, y + h
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            cv2.rectangle(img, (x, y), (x1, y1), (0, 0, 255), 2)
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        cv2.putText(img, 'mtcnn', (30, 30), font, 1, (255, 255, 0), 2, cv2.LINE_AA)
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        for result in faces2:
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            x = result.left()
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            y = result.top()
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            x1 = result.right()
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            y1 = result.bottom()
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            cv2.rectangle(img1, (x, y), (x1, y1), (0, 0, 255), 2)
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        cv2.putText(img1, 'dlib', (30, 30), font, 1, (255, 255, 0), 2, cv2.LINE_AA)
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        for i in range(faces3.shape[2]):
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            confidence = faces3[0, 0, i, 2]
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            if confidence > 0.5:
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                box = faces3[0, 0, i, 3:7] * np.array([width, height, width, height])
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                (x, y, x1, y1) = box.astype("int")
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                cv2.rectangle(img2, (x, y), (x1, y1), (0, 0, 255), 2)
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        cv2.putText(img2, 'dnn', (30, 30), font, 1, (255, 255, 0), 2, cv2.LINE_AA)
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        for result in faces4:
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            x, y, w, h = result
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            x1, y1 = x + w, y + h
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            cv2.rectangle(img3, (x, y), (x1, y1), (0, 0, 255), 2)
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        cv2.putText(img3, 'haar', (30, 30), font, 1, (255, 255, 0), 2, cv2.LINE_AA)
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        h1 = cv2.hconcat([img3, img1])
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        h2 = cv2.hconcat([img, img2])
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        fin = cv2.vconcat([h1, h2])
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        cv2.imshow("mtcnn", img)
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        cv2.imshow("dlib", img1)
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        cv2.imshow("dnn", img2)
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        cv2.imshow("haar", img3)
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        if cv2.waitKey(1) & 0xFF == ord('q'):
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            break
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    else:
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        break
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cap.release()
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cv2.destroyAllWindows()
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