client.py
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##################################################
#1. webcam에서 얼굴을 인식합니다.
#2. 얼굴일 확률이 97% 이상이고 영역이 15000 이상인 이미지를 서버에 전송
##################################################
import tkinter as tk
import tkinter.font
import tkinter.messagebox
import tkinter.scrolledtext
import threading
import torch
import numpy as np
import cv2
import asyncio
import websockets
import json
import os
import timeit
import base64
import time
from PIL import Image, ImageTk
from io import BytesIO
import requests
from models.mtcnn import MTCNN
device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
print('Running on device: {}'.format(device))
mtcnn = MTCNN(keep_all=True, post_process=True, device=device)
uri = 'ws://169.56.95.131:8765'
class Client(tk.Frame):
def __init__(self, parent, *args, **kwargs):
tk.Frame.__init__(self, parent, *args, **kwargs)
# URI
self.uri = 'ws://169.56.95.131:8765'
# Pytorch Model
self.device = device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
self.mtcnn = MTCNN(keep_all=True, device=device)
# OpenCV
self.cap = cv2.VideoCapture(0, cv2.CAP_DSHOW)
self.cam_width = 640
self.cam_height = 480
self.cap.set(3, self.cam_width)
self.cap.set(4, self.cam_height)
# Application Function
# cam에서 MTCNN 적용하는 영역
self.detecting_square = (500, 300)
# 영상 위에 사각형 색상 지정
self.rectangle_color = (0, 0, 255)
# tkinter GUI
self.width = 740
self.height = 700
self.parent = parent
self.parent.title("출석시스템")
self.parent.geometry("%dx%d+100+100" % (self.width, self.height))
self.pack()
self.create_widgets()
# Event loop and Thread
self.event_loop = asyncio.new_event_loop()
self.thread = threading.Thread(target=self.mainthread)
self.thread.start()
def create_widgets(self):
image = np.zeros([self.cam_height, self.cam_width, 3], dtype=np.uint8)
image = Image.fromarray(image)
image = ImageTk.PhotoImage(image)
font = tk.font.Font(family="맑은 고딕", size=15)
self.alert = tk.Label(self, text="출석시스템", font=font)
self.alert.grid(row=0, column=0, columnspan=20)
self.label = tk.Label(self, image=image)
self.label.grid(row=1, column=0, columnspan=20)
self.log = tk.scrolledtext.ScrolledText(self, wrap = tk.WORD, state=tk.DISABLED, width = 96, height = 10)
self.log.grid(row=2, column=0, columnspan=20)
self.quit = tk.Button(self, text="나가기", fg="red", command=self.stop)
self.quit.grid(row=3, column=10)
def logging(self, text):
self.log.config(state=tk.NORMAL)
self.log.insert(tkinter.CURRENT, text)
self.log.insert(tkinter.CURRENT, '\n')
self.log.config(state=tk.DISABLED)
def detect_face(self, frame):
results = self.mtcnn.detect(frame)
faces = self.mtcnn(frame, return_prob = False)
image_list = []
face_list = []
if results[1][0] == None:
return [], []
for box, face, prob in zip(results[0], faces, results[1]):
if prob < 0.97:
continue
# for debug
# print('face detected. prob:', prob)
x1, y1, x2, y2 = box
if (x2-x1) * (y2-y1) < 15000:
# 얼굴 해상도가 너무 낮으면 무시
continue
image = frame[int(y1):int(y2), int(x1):int(x2)]
image_list.append(image)
# tensor 데이터 저장
face_list.append(face.numpy())
return face_list, image_list
def mainthread(self):
t = threading.currentThread()
asyncio.set_event_loop(self.event_loop)
x1 = int(self.cam_width / 2 - self.detecting_square[0] / 2)
x2 = int(self.cam_width / 2 + self.detecting_square[0] / 2)
y1 = int(self.cam_height / 2 - self.detecting_square[1] / 2)
y2 = int(self.cam_height / 2 + self.detecting_square[1] / 2)
while getattr(t, "do_run", True):
ret, frame = self.cap.read()
# BGR to RGB
converted = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
face_list, image_list = self.detect_face(converted[y1:y2, x1:x2])
# 얼굴이 인식되면 출석요청
if face_list:
self.event_loop.run_until_complete(self.send_face(face_list, image_list))
# 사각형 영역 표시
frame = cv2.rectangle(frame, (x1, y1), (x2, y2), self.rectangle_color, 3)
converted = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
# 거울상으로 보여준다
converted = cv2.flip(converted,1)
image = Image.fromarray(converted)
image = ImageTk.PhotoImage(image)
self.label.configure(image=image)
self.label.image = image # kind of double buffering
@asyncio.coroutine
def set_rectangle(self):
self.rectangle_color = (255, 0, 0)
yield from asyncio.sleep(2)
self.rectangle_color = (0, 0, 255)
async def send_face(self, face_list, image_list):
try:
async with websockets.connect(uri) as websocket:
for face, image in zip(face_list, image_list):
#type: np.float32
send = json.dumps({'action': 'verify', 'tensor': face.tolist()})
await websocket.send(send)
recv = await websocket.recv()
data = json.loads(recv)
if data['status'] == 'success':
# 성공
self.logging('출석확인: ' + data['student_id'])
asyncio.ensure_future(self.set_rectangle())
else:
# 이미지 DB에 저장, 일단 보류
#if data['status'] == 'fail':
# send = json.dumps({'action': 'save_image', 'image': image.tolist()})
# await websocket.send(send)
if data['status'] == 'already':
asyncio.ensure_future(self.set_rectangle())
except Exception as e:
self.logging(e)
def stop(self):
self.thread.do_run = False
# self.thread.join() # there is a freeze problem
self.event_loop.close()
self.cap.release()
self.parent.destroy()
if __name__ == '__main__':
root = tk.Tk()
Client(root)
root.mainloop()