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main.py
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import os.path
import sys
import hashlib
import time
import numpy as np
from PyQt5 import QtWidgets, QtGui, QtCore
import cv2
from tensorflow import keras
from keras_preprocessing.image import img_to_array
from PIL import Image, ImageDraw, ImageFont
class MainWindows(QtWidgets.QWidget):
def __init__(self):
super().__init__()
self.EMOTIONS = ["生气", "厌恶", "害怕", "开心", "悲伤", "惊讶", "正常"]
self.detection_model_path = 'module/haarcascade_frontalface_default.xml' # 人脸检测模型
self.emotion_model_path = 'module/mini_XCEPTION.102-0.66.hdf5'
self.face_detection = cv2.CascadeClassifier('module/haarcascade_frontalface_default.xml')
self.emotion_classifier = keras.models.load_model('module/mini_XCEPTION.102-0.66.hdf5', compile=False)
self.shows = None
self.name_hash = None
self.showImage = None
self.pix = None
self.id = None
self.txt_asin = None
self.__main_layout = None # 总布局
self.__video_layout = None # 视频展示布局
self.__button_layout = None # 按键总布局
self.video_qlabel = None # 视频框
self.button_open_camera = None # 打开摄像头
self.button_photograph = None # 拍照
self.timer_camera = QtCore.QTimer() # 定时器
self.cap = cv2.VideoCapture() # 视频流
# self.cap.set(5, 60)
self.CAM_NUM = 0 # 定义摄像头
self.setWindowTitle("笑脸检测系统")
self.setWindowIcon(QtGui.QIcon('./image/ico.png'))
self.resize(670, 600)
# self.setWindowFlags(QtCore.Qt.WindowMinimizeButtonHint)
self.setFixedSize(680, 610)
self.set_layout() # 设置布局函数
self.init_txt() # 输入框
self.set_video() # 设置视频布局函数
self.set_button() # 设置按键布局函数
self.set_add() # 将元素添加到总布局
self.setLayout(self.__main_layout) # 应用布局
self.slot_init()
def set_layout(self):
self.__main_layout = QtWidgets.QVBoxLayout() # 总布局->垂直布局
self.__video_layout = QtWidgets.QVBoxLayout() # 视频布局->垂直布局
self.__button_layout = QtWidgets.QHBoxLayout() # 按键布局->水平布局
def init_txt(self):
self.txt_asin = QtWidgets.QLineEdit()
self.txt_asin.setPlaceholderText('请输入编号')
self.txt_asin.setValidator(QtGui.QRegExpValidator(QtCore.QRegExp("[^\\\\/:*?\"<>|`·]*")))
def set_video(self):
self.video_qlabel = QtWidgets.QLabel()
self.video_qlabel.setFixedSize(640, 480)
self.pix = QtGui.QPixmap('image/bj.jpg')
# self.video_qlabel.setStyleSheet("background-color:red;border:0px")
self.video_qlabel.setPixmap(self.pix)
self.__video_layout.addWidget(self.video_qlabel)
self.__video_layout.addWidget(self.txt_asin)
def set_button(self):
self.button_open_camera = QtWidgets.QPushButton("打开摄像头")
self.button_photograph = QtWidgets.QPushButton("拍照")
self.__button_layout.addWidget(self.button_open_camera)
self.__button_layout.addWidget(self.button_photograph)
def set_add(self):
self.__main_layout.addLayout(self.__video_layout)
self.__main_layout.addStretch()
self.__main_layout.addLayout(self.__button_layout)
def slot_init(self):
self.button_open_camera.clicked.connect(self.button_open_cameras)
self.button_photograph.clicked.connect(self.button_photographs)
self.timer_camera.timeout.connect(self.show_camera)
def button_open_cameras(self):
if not self.timer_camera.isActive(): # 若定时器未启动
flag = self.cap.open(self.CAM_NUM) # 参数是0，表示打开笔记本的内置摄像头，参数是视频文件路径则打开视频
if not flag: # flag表示open()成不成功
msg = QtWidgets.QMessageBox.warning(self, 'warning', "请检查相机于电脑是否连接正确",
buttons=QtWidgets.QMessageBox.Ok)
else:
self.timer_camera.start(10) # 定时器开始计时30ms，结果是每过30ms从摄像头中取一帧显示
self.button_open_camera.setText('关闭摄像头')
else:
self.timer_camera.stop() # 关闭定时器
self.cap.release() # 释放视频流
self.video_qlabel.clear() # 清空视频显示区域
self.video_qlabel.setPixmap(self.pix)
self.button_open_camera.setText('打开摄像头')
def button_photographs(self):
if self.cap.isOpened():
if self.txt_asin.text() != '':
code = self.opens()
if code[0] == 0:
self.init_error_tips(code[1])
else:
self.init_success_tips()
# thread = NewThread(self)
# thread.success.connect(self.init_success_tips)
# thread.error.connect(self.init_error_tips)
# thread.start()
else:
QtWidgets.QMessageBox.warning(self, '警告', '未输入编号', QtWidgets.QMessageBox.Yes,
QtWidgets.QMessageBox.Yes)
else:
QtWidgets.QMessageBox.warning(self, '警告', '摄像头未打开', QtWidgets.QMessageBox.Yes,
QtWidgets.QMessageBox.Yes)
def init_success_tips(self):
infoBox = QtWidgets.QMessageBox()
# infoBox.setIcon(QtWidgets.QMessageBox.Information)
infoBox.setWindowIcon(QtGui.QIcon('./image/ico.png'))
infoBox.setText("保存完成！")
infoBox.setWindowTitle("提示")
infoBox.setStandardButtons(QtWidgets.QMessageBox.Ok)
infoBox.button(QtWidgets.QMessageBox.Ok).animateClick(500) # 3秒自动关闭
infoBox.exec_()
def init_error_tips(self, state):
infoBox = QtWidgets.QMessageBox.warning(self, '警告', state, QtWidgets.QMessageBox.Yes,
QtWidgets.QMessageBox.Yes)
def show_camera(self):
flag, image = self.cap.read() # 从视频流中读取
self.shows = cv2.resize(image, (640, 480)) # 把读到的帧的大小重新设置为 640x480
self.shows = cv2.cvtColor(self.shows, cv2.COLOR_BGR2RGB) # 视频色彩转换回RGB，这样才是现实的颜色
self.shows = cv2.flip(self.shows, 1)
self.showImage = QtGui.QImage(self.shows.data, self.shows.shape[1], self.shows.shape[0],
QtGui.QImage.Format_RGB888) # 把读取到的视频数据变成QImage形式
self.video_qlabel.setPixmap(QtGui.QPixmap.fromImage(self.showImage)) # 往显示视频的Label里 显示QImage
def opens(self):
flag, image = self.cap.read()
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
images = image.copy()
images = cv2.flip(images, 1)
faces = self.face_detection.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30),
flags=cv2.CASCADE_SCALE_IMAGE)
canvas = np.zeros((480, 300, 3), dtype="uint8")
if len(faces) > 0:
faces = sorted(faces, reverse=True,
key=lambda x: (x[2] - x[0]) * (x[3] - x[1]))[0]
(fX, fY, fW, fH) = faces
roi = gray[fY:fY + fH, fX:fX + fW]
roi = cv2.resize(roi, (64, 64))
roi = roi.astype("float") / 255.0
roi = img_to_array(roi)
roi = np.expand_dims(roi, axis=0)
preds = self.emotion_classifier.predict(roi)[0]
emotion_probability = np.max(preds)
label = self.EMOTIONS[preds.argmax()]
text = '情绪:{}:{:.2f}%'.format(label, emotion_probability * 100)
images = Image.fromarray(cv2.cvtColor(images, cv2.COLOR_BGR2RGB))
draw = ImageDraw.Draw(images)
fontText = ImageFont.truetype('./module/SIMYOU.TTF', 20, encoding="utf-8")
draw.text(xy=(10, 450), text=text, font=fontText, fill=(255, 0, 0))
images = cv2.cvtColor(np.asarray(images), cv2.COLOR_RGB2BGR)
self.name_hash = hashlib.md5()
self.name_hash.update(str(time.time()).encode("utf-8"))
if not os.path.exists('data_img'):
os.mkdir("data_img")
if not os.path.exists('./data_img/' + self.txt_asin.text()):
os.makedirs('./data_img/' + self.txt_asin.text())
name = './data_img/' + self.txt_asin.text() + '/' + str(self.name_hash.hexdigest()) + '.jpg'
# print(preds[preds.argmax()])
cv2.imwrite(name, images)
self.txt_asin.setText('')
else:
return [0, '未检测到人脸']
return [1, '成功']
if __name__ == '__main__':
app = QtWidgets.QApplication(sys.argv)
windows = MainWindows()
windows.show()
sys.exit(app.exec_())