import os
import cv2
import dlib
import numpy as np
import argparse
import time
import threading
import random
import socket
import glob
import matplotlib.pyplot as plt
import sys
from openpyxl import Workbook
from openpyxl import load_workbook
from PyQt5.QtCore import QTimer
from PyQt5.QtGui import QImage, QPixmap
from PyQt5.QtWidgets import QApplication, QDialog, QWidget, QVBoxLayout, QHBoxLayout, QBoxLayout
from PyQt5.uic import loadUi
from PyQt5.uic.properties import QtCore
from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
from matplotwidgetfile import matplotwidgetFile
from contextlib import contextmanager
from wide_resnet import WideResNet
from keras.utils.data_utils import get_file
global myimge
global Agecnt
global Range
global exitflag
global sock
global sock_on
global th_flag
global testflag
global name
global xl_row
myimge = cv2.imread("waiting.png")
Agecnt = [0, 0, 0, 0, 0, 0, 0, 0, 0]
Agevideo = [r"C:\ProgramData\Age\age-gender-estimation-master\ad\teenF",
r"C:\ProgramData\Age\age-gender-estimation-master\ad\YouthF",
r"C:\ProgramData\Age\age-gender-estimation-master\ad\middleF",
r"C:\ProgramData\Age\age-gender-estimation-master\ad\oldF",
r"C:\ProgramData\Age\age-gender-estimation-master\ad\teenM",
r"C:\ProgramData\Age\age-gender-estimation-master\ad\YouthM",
r"C:\ProgramData\Age\age-gender-estimation-master\ad\middleM",
r"C:\ProgramData\Age\age-gender-estimation-master\ad\oldM",
r"C:\ProgramData\Age\age-gender-estimation-master\ad\079war01.mp4",
r"C:\ProgramData\Age\age-gender-estimation-master\ad\068war02.mp4",
r"C:\ProgramData\Age\age-gender-estimation-master\ad\109war03.mp4"]
Range = ['teenF', 'YouthF', 'middleF', 'oldF', 'teenM', 'YouthM', 'middleM', 'oldM', 'warning']
exitflag = 0
sock_on = 1
th_flag = 0
testflag = 0
if sock_on == 1:
sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
sock.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR,1)
sock.connect(('192.168.43.247', 5005))
class Video(object):
def __init__(self, path):
self.path = path
def play(self):
from os import startfile
startfile(self.path)
class Movie_MP4(Video):
type = "MP4"
class Life2Coding(QDialog):
def __init__(self):
super(Life2Coding, self).__init__()
loadUi('life2coding.ui', self)
self.setGeometry(900, 30, 1006, 729)
# self.timer = QTimer(self)
self.imgtimer = QTimer(self)
self.startButton.clicked.connect(self.start_webcam)
self.stopButton.clicked.connect(self.stop_webcam)
self.warningButton.clicked.connect(self.warning_event)
self.resetButton.clicked.connect(self.reset)
self.fireButton.clicked.connect(self.fire)
self.exitButton.clicked.connect(self.ext)
def start_webcam(self):
global Agecnt
global exitflag
global th_flag
global name
global xl_row
Agecnt = [0, 0, 0, 0, 0, 0, 0, 0, 0]
wb = Workbook()
xl_row = 0
ws1 = wb.active # 현재 열려 있는 Sheet
now = time.gmtime(time.time())
now_list = list(now)
name = str(now_list[0]) + "_" + str(now_list[1]) + "_" + str(now_list[2]) + "-" + str(now_list[3]) + "__" + str(
now_list[4]) + "__" + str(now_list[5])
ws1.title = name
wb.save("D:/" + ws1.title + ".xlsx")
Agecnt = [0, 0, 0, 0, 0, 0, 0, 0, 0]
exitflag = 0
self.imgtimer.timeout.connect(self.update_frame)
# self.timer.timeout.connect(self.graph)
self.imgtimer.start(1000)
# self.timer.start(1000)
if (th_flag == 0):
self.th_main = threading.Thread(target=main, args=())
# self.th_main.daemon = True
self.th_main.start()
th_flag = 1
print("start webcam")
def stop_webcam(self):
global exitflag
global th_flag
exitflag = 1
# self.timer.stop()
self.imgtimer.stop()
self.th_main.join()
if ad_output.timer.is_alive():
ad_output.timer.cancel()
if warning_output.timer_w.is_alive():
warning_output.timer_w.cancel()
th_flag = 0
if sock_on == 1:
sock.send("qqqqqqqq".encode())
sock.close()
print("stop webcam")
def update_frame(self):
height, width, channel = myimge.shape
bytesPerLine = 3 * width
qImg = QImage(myimge.data, width, height, bytesPerLine, QImage.Format_RGB888).rgbSwapped()
pixmap = QPixmap(qImg)
self.imgLabel.setPixmap(pixmap)
self.widget.canvas.ax.clear()
self.widget.canvas.ax.bar(Range, Agecnt)
self.widget.canvas.draw()
print("update_frame")
def graph(self):
self.widget.canvas.ax.clear()
self.widget.canvas.ax.bar(Range, Agecnt)
self.widget.canvas.draw()
def reset(self):
global Agecnt
global name
global xl_row
wb = load_workbook("D:/" + name + ".xlsx")
ws = wb.active
xl_row = xl_row + 1
for col in range(1, 9):
ws.cell(row=xl_row, column=col, value=int(Agecnt[col - 1]))
wb.save("D:/" + name + ".xlsx")
Agecnt = [0, 0, 0, 0, 0, 0, 0, 0, 0]
print("reset!")
# sock.send("reset123".encode())
def warning_event(self):
Agecnt[8] = -1
warning_output()
# movie = Movie_MP4(Agevideo[8])
# movie.play()
def fire(self):
Agecnt[8] = -2
# movie = Movie_MP4(Agevideo[8])
# movie.play()
warning_output()
def ext(self):
Agecnt[8] = -3
warning_output()
def ad_output():
global Agecnt
if Agecnt[8] == 0:
Max = Agecnt.index(max(Agecnt))
if not Agecnt[Max] == 0: # Data 가 있을 경우 해당 나이에 맞는 광고 표출
path = random.choice(glob.glob(Agevideo[Max] + "\*")) # 랜덤 파일 추출
f_name = os.path.split(path) # 파일명 추출 s[1] -> 파일명
T = int(f_name[1][0]) * 100 + int(f_name[1][1]) * 10 + int(f_name[1][2]) # 파일명에서 시간 추출
s_d = os.path.splitext(path) # mp4 제외 파일명만 추출
s_d = os.path.split(s_d[0])
if sock_on == 1:
sock.send(s_d[1].encode())
print("동영상 제목 전송")
while 1:
receive = sock.recv(8)
print(receive)
if receive :
print("나감")
break;
ad_output.timer = threading.Timer(T, ad_output)
#movie = Movie_MP4(path)
#movie.play()
ad_output.timer.start()
else: # Data 값들이 없을 경우 2초 간격으로 타이머 반복 실행
ad_output.timer = threading.Timer(2, ad_output)
ad_output.timer.start()
else:
ad_output.timer.cancel()
print("광고 타이머가 Warning 에 의해 종료되었습니다.")
def warning_output():
global Agecnt
if Agecnt[8] != 0:
w_index = -1 * Agecnt[8] + 7
f_name = os.path.split(Agevideo[w_index]) # 파일명 추출 s[1] -> 파일명
T = int(f_name[1][0]) * 100 + int(f_name[1][1]) * 10 + int(f_name[1][2]) # 파일명에서 시간 추출
s_d = os.path.splitext(Agevideo[w_index]) # mp4 제외 파일명만 추출
s_d = os.path.split(s_d[0])
if sock_on == 1:
sock.send(s_d[1].encode())
print("Warning 동영상 제목 전송")
warning_output.timer_w = threading.Timer(T, warning_output)
#movie = Movie_MP4(Agevideo[w_index])
#movie.play()
warning_output.timer_w.start()
else:
warning_output.timer_w.cancel()
print("Warning 타이머가 reset에 의해 종료되었습니다.")
pretrained_model = "https://github.com/yu4u/age-gender-estimation/releases/download/v0.5/weights.18-4.06.hdf5"
modhash = '89f56a39a78454e96379348bddd78c0d'
def get_args():
parser = argparse.ArgumentParser(description="This script detects faces from web cam input, "
"and estimates age and gender for the detected faces.",
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument("--weight_file", type=str, default=None,
help="path to weight file (e.g. weights.18-4.06.hdf5)")
parser.add_argument("--depth", type=int, default=16,
help="depth of network")
parser.add_argument("--width", type=int, default=8,
help="width of network")
args = parser.parse_args()
return args
def draw_label(image, point, label, font=cv2.FONT_HERSHEY_SIMPLEX,
font_scale=1, thickness=2):
size = cv2.getTextSize(label, font, font_scale, thickness)[0]
x, y = point
cv2.rectangle(image, (x, y - size[1]), (x + size[0], y), (255, 0, 0), cv2.FILLED)
cv2.putText(image, label, point, font, font_scale, (255, 255, 255), thickness)
@contextmanager
def video_capture(*args, **kwargs):
cap = cv2.VideoCapture(*args, **kwargs)
try:
yield cap
finally:
cap.release()
def yield_images():
# capture video
with video_capture(0) as cap:
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 640)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 480)
while True:
# get video frame
ret, img = cap.read()
if not ret:
raise RuntimeError("Failed to capture image")
yield img
def main():
global exitflag
global testflag
ad_output()
print("일단 메인문은 들어왔습니다잉")
args = get_args()
depth = args.depth
k = args.width
weight_file = args.weight_file
model = 0
if not weight_file:
weight_file = get_file("weights.18-4.06.hdf5", pretrained_model, cache_subdir="pretrained_models",
file_hash=modhash, cache_dir=os.path.dirname(os.path.abspath(__file__)))
print("웨이트 파일이 없으므로 받아옵니다.")
print(weight_file)
print("웨이트 파일 받습니다.")
# for face detection
detector = dlib.get_frontal_face_detector()
print("얼굴인식 라이브러리 사용")
# load model and weights
img_size = 64
print("이미지 사이즈 = 64")
model = WideResNet(img_size, depth=depth, k=k)()
print("wideResNet 설정")
if testflag == 0:
model.load_weights(weight_file)
print("사진 찍기 전!")
for img in yield_images():
input_img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
img_h, img_w, _ = np.shape(input_img)
# detect faces using dlib detector
detected = detector(input_img, 1)
faces = np.empty((len(detected), img_size, img_size, 3))
if len(detected) > 0:
for i, d in enumerate(detected):
x1, y1, x2, y2, w, h = d.left(), d.top(), d.right() + 1, d.bottom() + 1, d.width(), d.height()
xw1 = max(int(x1 - 0.4 * w), 0)
yw1 = max(int(y1 - 0.4 * h), 0)
xw2 = min(int(x2 + 0.4 * w), img_w - 1)
yw2 = min(int(y2 + 0.4 * h), img_h - 1)
cv2.rectangle(img, (x1, y1), (x2, y2), (255, 0, 0), 2)
# cv2.rectangle(img, (xw1, yw1), (xw2, yw2), (255, 0, 0), 2)
faces[i, :, :, :] = cv2.resize(img[yw1:yw2 + 1, xw1:xw2 + 1, :], (img_size, img_size))
# predict ages and genders of the detected faces
results = model.predict(faces)
predicted_genders = results[0]
ages = np.arange(0, 101).reshape(101, 1)
predicted_ages = results[1].dot(ages).flatten()
# draw results
for i, d in enumerate(detected):
label = "{}, {}".format(int(predicted_ages[i]),
"F" if predicted_genders[i][0] > 0.5 else "M")
draw_label(img, (d.left(), d.top()), label)
age_index = (int)(predicted_ages[i] / 20)
if predicted_genders[i][0] > 0.5:
if age_index < 3:
Agecnt[age_index] = Agecnt[age_index] + 1
else:
Agecnt[3] = Agecnt[3] + 1
else:
if age_index + 4 < 7:
Agecnt[age_index + 4] = Agecnt[age_index + 4] + 1
else:
Agecnt[7] = Agecnt[7] + 1
global myimge
myimge = img
print("main 실행")
# cv2.imshow("result", img)
# key = cv2.waitKey(30)
# cv2.waitKey(30)
if exitflag == 1:
break
# while(exitflag):
# time.sleep(2)
print("main 끝")
exitflag = 0
testflag = 1
if __name__ == '__main__':
app = QApplication(sys.argv)
window = Life2Coding()
window.setWindowTitle('AD title')
window.show()
app.exec_()
# sys.exit(app.exec_())
