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python人脸识别统计人数qt窗体
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运行结果如下：
主要代码：
# coding:utf-8 import sys #从转换的.py文件内调用类 import cv2 from untitled import
Ui_Dialog from PyQt5 import QtWidgets from PyQt5.QtWidgets import * from
PyQt5.QtCore import * class myWin(QtWidgets.QWidget, Ui_Dialog): def
__init__(self): super(myWin, self).__init__() self.setupUi(self) def
openFileButton(self): imgName, imgType =
QFileDialog.getOpenFileName(self,"打开文件","./","files(*.*)") img =
cv2.imread(imgName) cv2.imwrite("temp/original.jpg", img) height, width, pixels
= img.shape print("width,height",width,height)
print("self.label.width()",self.label.width())
print("self.label.height()",self.label.height()) if width>(self.label.width()):
rwidth=self.label.width() print("rwidth-if,rheight-if", width, rheight) elif
height>(self.label.height()): rheight=self.label.height()
print("rwidth-elif,rheight-elfi", rwidth, rheight) elif
((self.label.height())-height)<((self.label.width())-width):
rheight=self.label.height() print("rwidth-elif,rheight-elfi", rwidth, rheight)
else: print("rheight,rwidth", height, width) rheight = height rwidth = width
frame = cv2.resize(img, (int(rwidth), int(rheight)))
print("rwidth-elif,rheight-elfi", rwidth, rheight) img2 = cv2.cvtColor(frame,
cv2.COLOR_BGR2RGB) # opencv读取的bgr格式图片转换成rgb格式 _image = QtGui.QImage(img2[:],
img2.shape[1], img2.shape[0], img2.shape[1] * 3, QtGui.QImage.Format_RGB888)
jpg_out = QtGui.QPixmap(_image).scaled(rwidth, rheight) #设置图片大小
self.label.setPixmap(jpg_out) #设置图片显示 def saveFileButton(self): img =
cv2.imread("temp/original.jpg") file_path = QFileDialog.getSaveFileName(self,
"save file", "./save/test","jpg files (*.jpg);;all files(*.*)")
print(file_path[0]) cv2.imwrite(file_path[0], img) cv2.waitKey(0)
cv2.destroyAllWindows() def recogPerson(self): import cv2 img =
cv2.imread("temp/original.jpg") face_detect =
cv2.CascadeClassifier('haarcascade_frontalface_default.xml') eye_detect =
cv2.CascadeClassifier('haarcascade_eye.xml') # 灰度处理 gray = cv2.cvtColor(img,
code=cv2.COLOR_BGR2GRAY) # 检查人脸 按照1.1倍放到 周围最小像素为5 face_zone =
face_detect.detectMultiScale(gray,1.3,5) # print ('识别人脸的信息：\n',face_zone) ints
= 0 # 绘制矩形和圆形检测人脸 for x, y, w, h in face_zone: ints += 1 # 绘制矩形人脸区域 if w < 101:
cv2.rectangle(img, pt1=(x, y), pt2=(x + w, y + h), color=[0, 0, 255],
thickness=2) # 绘制圆形人脸区域 radius表示半径 cv2.circle(img, center=(x + w // 2, y + h //
2), radius=w // 2, color=[0, 255, 0], thickness=2) roi_face = gray[y:y + h, x:x
+ w] # 灰度图 roi_color = img[y:y + h, x:x + w] # 彩色图 eyes =
eye_detect.detectMultiScale(roi_face) font1 = "Current number:"; font2 = "pcs";
font = cv2.FONT_HERSHEY_TRIPLEX # 使用默认字体 cv2.putText(img, font1 + str(ints) +
font2, (10, 28), font, 1.2, (0, 255, 0), 1) #cv2.namedWindow("Easmount-CSDN",
0) #cv2.imshow("Easmount-CSDN", img) cv2.imwrite("save/recognPerson.jpg", img)
#cv2.waitKey(0) #显示人数到窗体 self.textEdit.setPlainText(str(ints))
#self.textEdit.setPlainText('Hello PyQt5!\n单击按钮') #显示相片到label_2 img =
cv2.imread("save/recognPerson.jpg") rheight = height rwidth = width frame =
cv2.resize(img, (int(rwidth), int(rheight))) img2 = cv2.cvtColor(frame,
cv2.COLOR_BGR2RGB) # opencv读取的bgr格式图片转换成rgb格式 jpg_out =
QtGui.QPixmap(_image).scaled(rwidth, rheight) #设置图片大小
self.label_2.setPixmap(jpg_out) #设置图片显示 if __name__=="__main__":
app=QtWidgets.QApplication(sys.argv) Widget=myWin() Widget.show()
sys.exit(app.exec_())
运行结果如下：