from flask import Flask, Response, json, render_template
from werkzeug.utils import secure_filename
from flask import request
from os import path, getcwd
import time
from face import Face
import cv2
from db import Database
import face_recognition
app = Flask(__name__)

app.config['file_allowed'] = ['image/png', 'image/jpeg']
app.config['train_img'] = path.join(getcwd(), 'train_img')
app.db = Database()
aface = Face(app) #You would need an app here
aface.load_all()
known_encoding_faces = aface.known_encoding_faces
user_id = aface.face_user_keys

class VideoCamera:
    def __init__(self,app):
        self.known_encoding_faces = aface.known_encoding_faces
        self.user_id = aface.face_user_keys
        #print face.known_encoding_faces
        # Using OpenCV to capture from device 0. If you have trouble capturing
        # from a webcam, comment the line below out and use a video file
        # instead.
        self.faces = []
        self.video_capture = cv2.VideoCapture(0)
        self.face_user_keys = {}
        #self.recognize()
        self.name_face()
        # If you decide to use video.mp4, you must have this file in the folder
        # as the main.py
    def load_user_by_index_key(self, index_key=0):

        key_str = str(index_key)

        if key_str in self.face_user_keys:
            return self.face_user_keys[key_str]

        return None

    def name_face (self):
        results = app.db.select('SELECT users.name,faces.id, faces.user_id, faces.filename, faces.created FROM faces INNER JOIN users on users.id = faces.user_id')
        for row in results:
            user = {
                "name": row[0]
            }
            face = {
                "id": row[1],
                "user_id": row[2],
                "filename": row[3],
                "created": row[4]
            }
            self.faces.append(user)

    def get_frame(self):
        face_locations = []
        face_encodings = []
        face_names = []
        process_this_frame = True
        success, frame = self.video_capture.read()
        small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)
        rgb_small_frame = small_frame[:, :, ::-1]

        # Only process every other frame of video to save time
        if process_this_frame:
            # Find all the faces and face encodings in the current frame of video
            face_locations = face_recognition.face_locations(rgb_small_frame)
            #print(face_locations)
            face_encodings = face_recognition.face_encodings(rgb_small_frame, face_locations)[0]
            #print(face_encodings)


            face_names = []
            for face_encoding in face_encodings:
                # See if the face is a match for the known face(s)
                matches = face_recognition.compare_faces(self.known_encoding_faces, face_encodings)
                name = "Unknown"

                # If a match was found in known_face_encodings, just use the first one.
                if True in matches:
                    first_match_index = matches.index(True)
                    name = self.faces[first_match_index]


                face_names.append(name)
                #print(face_names)

        process_this_frame = not process_this_frame

        # Display the results
        for (top, right, bottom, left), name in zip(face_locations, 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(frame, (left, top), (right, bottom), (0, 0, 255), 2)

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


        ret, jpeg = cv2.imencode('.jpg', frame)
        return jpeg.tobytes()

    def __del__(self):
        self.video_capture.release()

File "C:tutorialface_recognitionvenvsrccamera.py", line 110, in get_frame
    cv2.putText(frame, name, (left + 6, bottom - 6), font, 1.0, (255, 255, 255), 1)
TypeError: bad argument type for built-in operation