face_tk_new.py

import numpy as np
import os
import cv2
import csv
import tkinter as tk
from tkinter import *
from tkinter import messagebox
from PIL import Image
from PIL import ImageTk
import face_recognition
from os import listdir
from os.path import isfile, join
from datetime import datetime
#from IPython import embed

#Set up GUI
window = tk.Tk()  #Makes main window
window.wm_title("Face recognition for access control")
window.config(background="#74b0c0")

font = cv2.FONT_HERSHEY_SIMPLEX
small_font = cv2.FONT_HERSHEY_COMPLEX_SMALL
known_face_encodings = []
known_face_names = []

face_names = []

registration = False

mypath = "people"

for f in listdir(mypath):
     if isfile(join(mypath, f)):
         image = face_recognition.load_image_file(join(mypath,f))
         face_encoding = face_recognition.face_encodings(image)[0]
         known_face_encodings.append(face_encoding)
         known_face_names.append(f[:-4])

file_name = "logs/"+str(datetime.now())[:10]
if not os.path.exists(file_name):
    f = open(file_name, 'a+')
    f.close()

#Graphics window
imageFrame = tk.Frame(window, width=600, height=600, bg = "white")
imageFrame.grid(row=0, column=0, rowspan = 3, padx=10, pady=2)

#Capture video frames

cap = cv2.VideoCapture(0)

def register(window, face_names, welcome):
    global registration
    registration = not registration
    for name in face_names:
            if (name != "Unknown"):
                print(name.capitalize(),"registered at",str(datetime.now())[:-7])
                f = open(file_name, 'a+')
                f.write(str(datetime.now())[11:-10]+"\t"+name+"\n")
                f.close()
                welcome.config(text = "Hi " + name.capitalize())

                log = ""
                with open(file_name) as csv_file:
                    csv_reader = csv.reader(csv_file, delimiter='\t')
                    for row in csv_reader:
                        log = log + row[0] + " "+ row[1] + "\n"

                logs = tk.Label(window, text="Logs \n"+log, font = "Helvetica 16 bold", fg="white", bg="SteelBlue4")
                logs.grid(row = 0, column = 2, rowspan = 3)

def show_frame():
    # Initialize some variables
    face_locations = []
    face_encodings = []
    global face_names
    face_names = []
    global registration
    _, frame = cap.read()
    small_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGBA)

    cv2.putText(frame,str(datetime.now().strftime("%H:%M %d/%m/%Y")),(20,20), font, .5,(255,0,0),2,cv2.LINE_AA)
    # Resize frame of video to 1/4 size for faster face recognition processing
    small_frame = cv2.resize(frame, (0, 0), fx=0.5, fy=0.5)
    if (registration):
        # Convert the image from BGR color (which OpenCV uses) to RGB color (which face_recognition uses)
        # Only process every other frame of video to save time

        # Find all the faces and face encodings in the current frame of video
        face_locations = face_recognition.face_locations(small_frame)
        face_encodings = face_recognition.face_encodings(small_frame, face_locations)
        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(known_face_encodings, face_encoding)
            # If a match was found in known_face_encodings, just use the first one.
            if (sum(matches)==1 and True in matches):
                first_match_index = matches.index(True)
                name = known_face_names[first_match_index]
                face_names.append(name)
                
            elif (sum(matches) > 1):
            # Or instead, use the known face with the smallest distance to the new face
                face_distances = face_recognition.face_distance(known_face_encodings, face_encoding)
                best_match_index = np.argmin(face_distances)
                if face_distances[best_match_index]:
                    name = known_face_names[best_match_index]

                face_names.append(name)

    # 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 1/2 size
        top *= 2
        right *= 2
        bottom *= 2
        left *= 2

        # 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)
        cv2.putText(frame, name, (left + 6, bottom - 6), font, 1.0, (255, 255, 255), 1)

    frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGBA)
    img = Image.fromarray(frame)
    imgtk = ImageTk.PhotoImage(image=img)
    display1.imgtk = imgtk #Shows frame for display 1
    display1.configure(image=imgtk)
    window.after(10, show_frame) 

display1 = tk.Label(imageFrame)
display1.grid(row=1, column=0, columnspan = 3, padx=10, pady=2)  #Display 1

welcome = tk.Label(window, text = "                               ", font = "Helvetica 16 bold", fg="white", bg="SteelBlue4")
welcome.grid(row = 2, column = 1, padx = 5, pady = 5)

# create a button, that when pressed, will take the current frame and save it to file
btn = tk.Button(window, text="Register", font = "Helvetica 16 bold",fg="white",bg="SteelBlue4", command= lambda: register(window, face_names, welcome))
btn.grid(row=0, column=1, padx=5, pady=5)

log = ""

with open(file_name) as csv_file:
    csv_reader = csv.reader(csv_file, delimiter='\t')
    for row in csv_reader:
        log = log + row[0] + " "+ row[1] + "\n"
        
logs = tk.Label(window, text="Logs \n"+log, font = "Helvetica 16 bold", fg="white", bg="SteelBlue4")
logs.grid(row = 0, column = 2, rowspan = 3)

show_frame() #Display
window.mainloop()  #Starts GUI