OpenCV-Python基础教程2-PyQt编写GUI界面

import sys
from PyQt5.QtWidgets import QApplication, QWidget

if __name__ == ‘__main__‘:
    app = QApplication(sys.argv)
    window = QWidget()
    window.setWindowTitle(‘Hello World!‘)
    window.show()
    sys.exit(app.exec_())

import sys
import cv2
from PyQt5 import QtCore, QtGui, QtWidgets
from PyQt5.QtCore import *
from PyQt5.QtGui import *
from PyQt5.QtWidgets import QFileDialog, QMainWindow
from mainForm import Ui_MainWindow


class PyQtMainEntry(QMainWindow, Ui_MainWindow):
    def __init__(self):
        super().__init__()
        self.setupUi(self)

        self.camera = cv2.VideoCapture(0)
        self.is_camera_opened = False  # 摄像头有没有打开标记

        # 定时器：30ms捕获一帧
        self._timer = QtCore.QTimer(self)
        self._timer.timeout.connect(self._queryFrame)
        self._timer.setInterval(30)

    # QT显示图片
    def Qt_ShowImage(self):
        rows, cols, channels = self.captured.shape
        bytesPerLine = channels * cols
        # Qt显示图片时，需要先转换成QImgage类型
        QImg = QImage(self.captured.data, cols, rows, bytesPerLine, QImage.Format_RGB888)
        self.labelCapture.setPixmap(QPixmap.fromImage(QImg).scaled(
            self.labelCapture.size(), Qt.KeepAspectRatio, Qt.SmoothTransformation))

    def Qt_ShowImage2(self):
        rows, columns = self.cpatured.shape
        bytesPerLine = columns
        # 灰度图是单通道，所以需要用Format_Indexed8
        QImg = QImage(self.cpatured.data, columns, rows, bytesPerLine, QImage.Format_Indexed8)
        self.labelResult.setPixmap(QPixmap.fromImage(QImg).scaled(
            self.labelResult.size(), Qt.KeepAspectRatio, Qt.SmoothTransformation))

    def btnOpenCamera_Clicked(self):
        ‘‘‘
        打开和关闭摄像头
        ‘‘‘
        self.is_camera_opened = ~self.is_camera_opened
        if self.is_camera_opened:
            self.btnOpenCamera.setText("关闭摄像头")
            self._timer.start()
        else:
            self.btnOpenCamera.setText("打开摄像头")
            self._timer.stop()

    def btnCapture_Clicked(self):
        ‘‘‘
        捕获图片
        ‘‘‘
        # 摄像头未打开，不执行任何操作
        if not self.is_camera_opened:
            return

        self.captured = self.frame
        # 后面这几行代码几乎都一样，可以尝试封装成一个函数
        # rows, cols, channels = self.captured.shape
        # bytesPerLine = channels * cols
        # # Qt显示图片时，需要先转换成QImgage类型
        # QImg = QImage(self.captured.data, cols, rows, bytesPerLine, QImage.Format_RGB888)
        # self.labelCapture.setPixmap(QPixmap.fromImage(QImg).scaled(
        #     self.labelCapture.size(), Qt.KeepAspectRatio, Qt.SmoothTransformation))
        Qt_ShowImage()

    def btnReadImage_Clicked(self):
        ‘‘‘
        从本地读取图片,文件路径不能有中文
        ‘‘‘
        # 打开文件选取对话框
        filename, _ = QFileDialog.getOpenFileName(self, ‘打开图片‘)
        if filename:
            self.captured = cv2.imread(str(filename))
            # OpenCV图像以BGR通道存储，显示时需要从BGR转到RGB
            self.captured = cv2.cvtColor(self.captured, cv2.COLOR_BGR2RGB)

            # rows, cols, channels = self.captured.shape
            # bytesPerLine = channels * cols
            # QImg = QImage(self.captured.data, cols, rows, bytesPerLine, QImage.Format_RGB888)
            # self.labelCapture.setPixmap(QPixmap.fromImage(QImg).scaled(
            #     self.labelCapture.size(), Qt.KeepAspectRatio, Qt.SmoothTransformation))
            Qt_ShowImage(self)

    def btnGray_Clicked(self):
        ‘‘‘
        灰度化
        ‘‘‘
        # 如果没有捕获图片，则不执行操作
        if not hasattr(self, "captured"):
            return
        self.cpatured = cv2.cvtColor(self.captured, cv2.COLOR_RGB2GRAY)
        # rows, columns = self.cpatured.shape
        # bytesPerLine = columns
        # # 灰度图是单通道，所以需要用Format_Indexed8
        # QImg = QImage(self.cpatured.data, columns, rows, bytesPerLine, QImage.Format_Indexed8)
        # self.labelResult.setPixmap(QPixmap.fromImage(QImg).scaled(
        #     self.labelResult.size(), Qt.KeepAspectRatio, Qt.SmoothTransformation))
        Qt_ShowImage2(self)

    def btnThreshold_Clicked(self):
        ‘‘‘
        Otsu自动阈值分割
        ‘‘‘
        if not hasattr(self, "captured"):
            return

        _, self.cpatured = cv2.threshold(
            self.cpatured, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
        # rows, columns = self.cpatured.shape
        # bytesPerLine = columns
        # # 阈值分割图也是单通道，也需要用Format_Indexed8
        # QImg = QImage(self.cpatured.data, columns, rows, bytesPerLine, QImage.Format_Indexed8)
        # self.labelResult.setPixmap(QPixmap.fromImage(QImg).scaled(
        #     self.labelResult.size(), Qt.KeepAspectRatio, Qt.SmoothTransformation))
        Qt_ShowImage2(self)

    @QtCore.pyqtSlot()
    def _queryFrame(self):
        ‘‘‘
        循环捕获图片
        ‘‘‘
        ret, self.frame = self.camera.read()
        # img_rows, img_cols, channels = self.frame.shape
        # bytesPerLine = channels * img_cols
        #
        # cv2.cvtColor(self.frame, cv2.COLOR_BGR2RGB, self.frame)
        # QImg = QImage(self.frame.data, img_cols, img_rows, bytesPerLine, QImage.Format_RGB888)
        # self.labelCamera.setPixmap(QPixmap.fromImage(QImg).scaled(
        #     self.labelCamera.size(), Qt.KeepAspectRatio, Qt.SmoothTransformation))
        Qt_ShowImage(self)

if __name__ == "__main__":
    app = QtWidgets.QApplication(sys.argv)
    window = PyQtMainEntry()
    window.show()
    sys.exit(app.exec_())