PyQt Face Detection

import sys

import cv2
import mediapipe as mp
import numpy as np
from PyQt5 import QtGui
from PyQt5.QtCore import pyqtSignal, pyqtSlot, Qt, QThread
from PyQt5.QtGui import QPixmap
from PyQt5.QtWidgets import QWidget, QApplication, QLabel, QVBoxLayout, QPushButton

find_faces = False

class VideoThread(QThread):
  change_pixmap_signal = pyqtSignal(np.ndarray)

  def run(self):

    global find_faces

    mp_face_detection = mp.solutions.face_detection
    mp_drawing = mp.solutions.drawing_utils

    # capture from web cam
    cap = cv2.VideoCapture(0)
    with mp_face_detection.FaceDetection(model_selection=0, min_detection_confidence=0.5) as face_detection:
      while cap.isOpened():
        success, image = cap.read()
        if not success:
          print("Ignoring empty camera frame.")
          # If loading a video, use 'break' instead of 'continue'.
          continue

        if find_faces:
          # To improve performance, optionally mark the image as not writeable to
          # pass by reference.
          image.flags.writeable = False
          image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
          results = face_detection.process(image)

          # Draw the face detection annotations on the image.
          image.flags.writeable = True
          image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
          if results.detections:
            for detection in results.detections:
              mp_drawing.draw_detection(image, detection)

        image = cv2.flip(image, 1)
        self.change_pixmap_signal.emit(image)


class App(QWidget):
  def __init__(self):
    super().__init__()
    self.setWindowTitle("Qt live label demo")
    self.disply_width = 640
    self.display_height = 480
    # create the label that holds the image
    self.image_label = QLabel(self)
    self.image_label.resize(self.disply_width, self.display_height)
    # create a text label
    self.textLabel = QLabel('Webcam')
    # create find button
    self.find_button = QPushButton("Find")
    self.find_button.clicked.connect(self.find_button_clicked)

    # create a vertical box layout and add the two labels
    vbox = QVBoxLayout()
    vbox.addWidget(self.image_label)
    vbox.addWidget(self.textLabel)
    vbox.addWidget(self.find_button)
    # set the vbox layout as the widgets layout
    self.setLayout(vbox)

    # create the video capture thread
    self.thread = VideoThread()
    # connect its signal to the update_image slot
    self.thread.change_pixmap_signal.connect(self.update_image)
    # start the thread
    self.thread.start()

  @pyqtSlot(np.ndarray)
  def update_image(self, cv_img):
    """Updates the image_label with a new opencv image"""
    qt_img = self.convert_cv_qt(cv_img)
    self.image_label.setPixmap(qt_img)

  def convert_cv_qt(self, cv_img):
    """Convert from an opencv image to QPixmap"""
    rgb_image = cv2.cvtColor(cv_img, cv2.COLOR_BGR2RGB)
    h, w, ch = rgb_image.shape
    bytes_per_line = ch * w
    convert_to_Qt_format = QtGui.QImage(rgb_image.data, w, h, bytes_per_line, QtGui.QImage.Format_RGB888)
    p = convert_to_Qt_format.scaled(self.disply_width, self.display_height, Qt.KeepAspectRatio)
    return QPixmap.fromImage(p)

  def find_button_clicked(self):
    global find_faces
    find_faces = not find_faces


if __name__ == "__main__":
  app = QApplication(sys.argv)
  a = App()
  a.show()
  sys.exit(app.exec_())