import os
import sys
import cv2 as cv

from PyQt5 import QtCore, QtGui, QtWidgets
from PyQt5.QtCore import *
from PyQt5.QtGui import *
from PyQt5.QtWidgets import QFileDialog, QMainWindow

from surface import (Ui_MainWindow)
os.chdir(sys.path[0])

class PyQtMainEntry(QMainWindow, Ui_MainWindow):
    def __init__(self):

        super().__init__()  # 调用父类的初始化函数
        self.setupUi(self)  # 设置用户界面

        # 初始化摄像头，并尝试打开，默认尝试打开摄像头索引为0
        self.camera = cv.VideoCapture(0)
        self.is_camera_opened = False  # 标记摄像头是否成功打开

        # 创建一个定时器，并设置其触发间隔为10毫秒
        self._timer = QtCore.QTimer(self)
        self._timer.timeout.connect(self._queryFrame)  # 定时器触发时调用_queryFrame函数
        self._timer.setInterval(10)  # 设置定时器触发间隔


    def btnOpenCamera_Clicked(self):

        # 切换摄像头的打开状态
        self.is_camera_opened = ~self.is_camera_opened
        if self.is_camera_opened:
            # 当摄像头打开时，更改按钮文本为关闭摄像头，并启动定时器
            self.btnOpenCamera.setText("关闭摄像头")
            self._timer.start()
        else:
            # 当摄像头关闭时，更改按钮文本为打开摄像头，并停止定时器
            self.btnOpenCamera.setText("打开摄像头")
            self._timer.stop()

    def btnCapture_Clicked(self):

        if not self.is_camera_opened:
            # 如果相机未打开，则直接返回，不做任何操作
            return
        # 捕获图像
        self.captured = self.frame

        # 获取捕获图像的行数、列数和通道数
        rows, cols, channels = self.captured.shape
        # 计算每行字节数
        bytesPerLine = channels * cols

        # 使用捕获的图像数据创建QImage对象
        QImg = QImage(self.captured.data, cols, rows, bytesPerLine, QImage.Format_RGB888)
        # 将QImage对象转换为QPixmap，并按比例缩放以适应标签的大小，然后设置到标签上
        self.labelCapture.setPixmap(QPixmap.fromImage(QImg).scaled(
            self.labelCapture.size(), Qt.KeepAspectRatio, Qt.SmoothTransformation))

    def btnReadImage_Clicked(self):

        # 使用QFileDialog获取选择的图像文件名
        # ,_是占位符用来忽略返回值比如这里面会返回文件名和文件类型，使用占位符可以忽略文件类型
        filename,  _ = QFileDialog.getOpenFileName(self, '打开图片')
        if filename:
            # 通过文件名读取图像，并转换为RGB格式
            self.captured = cv.imread(str(filename))
            self.captured = cv.cvtColor(self.captured, cv.COLOR_BGR2RGB)

            # 获取图像的尺寸信息，用于创建QImage
            rows, cols, channels = self.captured.shape
            bytesPerLine = channels * cols

            # 将OpenCV图像转换为QImage格式
            QImg = QImage(self.captured.data, cols, rows, bytesPerLine, QImage.Format_RGB888)

            # 将QImage设置为标签的图片，并保持原始比例进行缩放
            self.labelCapture.setPixmap(QPixmap.fromImage(QImg).scaled(
                self.labelCapture.size(), Qt.KeepAspectRatio, Qt.SmoothTransformation))

    def btnGray_Clicked(self):

        if not hasattr(self, "captured"):
            return

        self.cpatured = cv.cvtColor(self.captured, cv.COLOR_RGB2GRAY)

        rows, columns = self.cpatured.shape
        bytesPerLine = columns

        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 btnThreshold_Clicked(self):

        if not hasattr(self, "captured"):
            return

        _, self.cpatured = cv.threshold(
            self.cpatured, 0, 255, cv.THRESH_BINARY + cv.THRESH_OTSU)

        rows, columns = self.cpatured.shape
        bytesPerLine = columns

        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))

    @QtCore.pyqtSlot()
    def _queryFrame(self):
        """
        从相机读取一帧图像，并将其显示在标签上。
        """
        # 从相机读取图像
        ret, self.frame = self.camera.read()

        # 获取图像的尺寸和每行字节数
        img_rows, img_cols, channels = self.frame.shape
        bytesPerLine = channels * img_cols

        # 将图像从BGR转换为RGB格式
        cv.cvtColor(self.frame, cv.COLOR_BGR2RGB, self.frame)
        # 创建QImage对象
        QImg = QImage(self.frame.data, img_cols, img_rows, bytesPerLine, QImage.Format_RGB888)
        # 将QImage设置为标签的图片，并保持宽高比
        self.labelCamera.setPixmap(QPixmap.fromImage(QImg).scaled(
            self.labelCamera.size(), Qt.KeepAspectRatio, Qt.SmoothTransformation))




    def btnDenoising_Clicked(self):
        if not hasattr(self, "captured"):
            return

        self.cpatured = cv.fastNlMeansDenoising(self.cpatured, None, 10, 7, 21)

        rows, columns = self.cpatured.shape
        bytesPerLine = columns

        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 btnSaveImage_Clicked(self):

        if not hasattr(self, "captured"):  # 检查是否已捕获图像
            return

        filename,  _ = QFileDialog.getSaveFileName(self, '保存图片')  # 弹出保存文件对话框
        if filename:  # 如果用户选择了保存路径
            cv.imwrite(str(filename), self.captured)  # 将捕获的图像保存到选择的路径


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