import face_recognition
import cv2


#   1. Process each video frame at 1/4 resolution (though still display it at full resolution)
#   2. Only detect faces in every other frame of video.

class Face_Recognition:

    def __init__(self):
        self.video_capture = cv2.VideoCapture(0)

        # Initialize some variables
        self.face_locations = []
        self.face_encodings = []
        self.face_names = []
        self.process_this_frame = True
        self.ret, self.frame = self.video_capture.read()
        self.small_frame = cv2.resize(self.frame, (0, 0), fx=0.25, fy=0.25)
        #self.list = []
        #self.best_match = []
        self.name = "Unknown"
        self.offset = 10


        #################### Load a sample picture and learn how to recognize it #################################
        self.vasilis_image = face_recognition.load_image_file("/home/bill/amy/src/deep/dataset/vasilis.jpg")
        self.vasilis_face_encoding = face_recognition.face_encodings(self.vasilis_image)[0]

        self.pete_image = face_recognition.load_image_file("/home/bill/amy/src/deep/dataset/pete.jpg")
        self.pete_face_encoding = face_recognition.face_encodings(self.pete_image)[0]

        self.shaheer_image = face_recognition.load_image_file("/home/bill/amy/src/deep/dataset/shaheer.jpg")
        self.shaheer_face_encoding = face_recognition.face_encodings(self.shaheer_image)[0]

        self.guang_image = face_recognition.load_image_file("/home/bill/amy/src/deep/dataset/guang.jpg")
        self.guang_face_encoding = face_recognition.face_encodings(self.guang_image)[0]

        self.toby_image = face_recognition.load_image_file("/home/bill/amy/src/deep/dataset/toby.jpg")
        self.toby_face_encoding = face_recognition.face_encodings(self.toby_image)[0]

        self.cyriac_image = face_recognition.load_image_file("/home/bill/amy/src/deep/dataset/cyriac.jpg")
        self.cyriac_face_encoding = face_recognition.face_encodings(self.cyriac_image)[0]

    def check_cam(self):
        # Check if camera opened successfully
        print('hello')
        if (self.video_capture.isOpened() == False):
            print("Unable to read camera feed")
        else:
            return True

    def detect_face(self):
        # Only process every other frame of video to save time
        if self.process_this_frame:
            # Find all the faces and face encodings in the current frame of video
            self.face_locations = face_recognition.face_locations(self.small_frame)
            self.face_encodings = face_recognition.face_encodings(self.small_frame, self.face_locations)

            #face_names = []
            for self.face_encoding in self.face_encodings:
                # See if the face is a match for the known face(s)
                match1 = face_recognition.compare_faces([self.vasilis_face_encoding], self.face_encoding)
                match2 = face_recognition.compare_faces([self.pete_face_encoding], self.face_encoding)
                match3 = face_recognition.compare_faces([self.shaheer_face_encoding], self.face_encoding)
                match4 = face_recognition.compare_faces([self.guang_face_encoding], self.face_encoding)
                match5 = face_recognition.compare_faces([self.toby_face_encoding], self.face_encoding)
                match6 = face_recognition.compare_faces([self.cyriac_face_encoding], self.face_encoding)

                list = [match1, match2, match3, match4, match5, match6]
                best_match = max(list)

                self.name = "Unknown"
                if best_match == match1:
                    self.name = "Vasilis"
                elif best_match == match2:
                    self.name = "Pete"
                elif best_match == match3:
                    self.name = "Shaheer"
                elif best_match == match4:
                    self.name = "Guang"
                elif best_match == match5:
                    self.name = "Toby"
                elif best_match == match6:
                    self.name = "Cyriac"
                else:
                    self.name = "Unknown"
                self.face_names.append(self.name)
        else:
            self.name = "No face"
            self.face_names.append(self.name)
        self.process_this_frame = not self.process_this_frame

        # Display the results
        for (top, right, bottom, left), name in zip(self.face_locations, self.face_names):
            # Scale back up face locations since the frame we detected in was scaled to 1/4 size
            top *= 4
            right *= 4
            bottom *= 4
            left *= 4

            # Draw a box around the face
            cv2.rectangle(self.frame, (left, top), (right, bottom), (0, 0, 255), 2)

            # Draw a label with a name below the face
            cv2.rectangle(self.frame, (left, bottom - 35), (right, bottom), (0, 0, 255))
            font = cv2.FONT_HERSHEY_DUPLEX
            cv2.putText(self.frame, name, (left + 6, bottom - 6), font, 1.0, (255, 255, 255), 1)
        return self.face_names

    def take_signature(self, face_amount):
        if face_amount == 1:
            cv2.imwrite("/home/bill/amy/src/deep/dataset/TEST.jpg", self.frame)
            #for (x,y,w,h) in zip(self.face_locations, self.face_names) :
                #cv2.imwrite("/home/bill/amy/src/deep/dataset/TEST.jpg", self.frame[y-10:y + h+10, x-10:x + w+10])
                #self.video_capture.release()



A=Face_Recognition()

#A.check_cam()
x = len(A.detect_face())
A.take_signature(x)