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@ -1,7 +1,6 @@
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import os
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import sys
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import cv2 as cv
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import numpy as np
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from PyQt5 import QtCore, QtGui, QtWidgets
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from PyQt5.QtCore import *
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@ -13,52 +12,70 @@ os.chdir(sys.path[0])
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class PyQtMainEntry(QMainWindow, Ui_MainWindow):
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def __init__(self):
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super().__init__()
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self.setupUi(self)
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super().__init__() # 调用父类的初始化函数
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self.setupUi(self) # 设置用户界面
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# 初始化摄像头,并尝试打开,默认尝试打开摄像头索引为0
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self.camera = cv.VideoCapture(0)
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self.is_camera_opened = False
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self.is_camera_opened = False # 标记摄像头是否成功打开
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# 创建一个定时器,并设置其触发间隔为10毫秒
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self._timer = QtCore.QTimer(self)
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self._timer.timeout.connect(self._queryFrame)
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self._timer.setInterval(10)
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self._timer.timeout.connect(self._queryFrame) # 定时器触发时调用_queryFrame函数
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self._timer.setInterval(10) # 设置定时器触发间隔
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def btnOpenCamera_Clicked(self):
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def btnOpenCamera_Clicked(self):
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# 切换摄像头的打开状态
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self.is_camera_opened = ~self.is_camera_opened
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if self.is_camera_opened:
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# 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
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self.btnOpenCamera.setText("关闭摄像头")
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self._timer.start()
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else:
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# 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
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self.btnOpenCamera.setText("打开摄像头")
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self._timer.stop()
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def btnCapture_Clicked(self):
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if not self.is_camera_opened:
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# 如果相机未打开,则直接返回,不做任何操作
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return
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# 捕获图像
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self.captured = self.frame
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# 获取捕获图像的行数、列数和通道数
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rows, cols, channels = self.captured.shape
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# 计算每行字节数
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bytesPerLine = channels * cols
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# 使用捕获的图像数据创建QImage对象
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QImg = QImage(self.captured.data, cols, rows, bytesPerLine, QImage.Format_RGB888)
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# 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
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self.labelCapture.setPixmap(QPixmap.fromImage(QImg).scaled(
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self.labelCapture.size(), Qt.KeepAspectRatio, Qt.SmoothTransformation))
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def btnReadImage_Clicked(self):
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# 使用QFileDialog获取选择的图像文件名
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# ,_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
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filename, _ = QFileDialog.getOpenFileName(self, '打开图片')
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if filename:
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# 通过文件名读取图像,并转换为RGB格式
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self.captured = cv.imread(str(filename))
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self.captured = cv.cvtColor(self.captured, cv.COLOR_BGR2RGB)
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# 获取图像的尺寸信息,用于创建QImage
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rows, cols, channels = self.captured.shape
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bytesPerLine = channels * cols
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# 将OpenCV图像转换为QImage格式
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QImg = QImage(self.captured.data, cols, rows, bytesPerLine, QImage.Format_RGB888)
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# 将QImage设置为标签的图片,并保持原始比例进行缩放
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self.labelCapture.setPixmap(QPixmap.fromImage(QImg).scaled(
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self.labelCapture.size(), Qt.KeepAspectRatio, Qt.SmoothTransformation))
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@ -93,19 +110,27 @@ class PyQtMainEntry(QMainWindow, Ui_MainWindow):
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@QtCore.pyqtSlot()
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def _queryFrame(self):
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"""
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从相机读取一帧图像,并将其显示在标签上。
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"""
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# 从相机读取图像
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ret, self.frame = self.camera.read()
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# 获取图像的尺寸和每行字节数
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img_rows, img_cols, channels = self.frame.shape
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bytesPerLine = channels * img_cols
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# 将图像从BGR转换为RGB格式
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cv.cvtColor(self.frame, cv.COLOR_BGR2RGB, self.frame)
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# 创建QImage对象
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QImg = QImage(self.frame.data, img_cols, img_rows, bytesPerLine, QImage.Format_RGB888)
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# 将QImage设置为标签的图片,并保持宽高比
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self.labelCamera.setPixmap(QPixmap.fromImage(QImg).scaled(
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self.labelCamera.size(), Qt.KeepAspectRatio, Qt.SmoothTransformation))
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def btnDenoising_Clicked(self):
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if not hasattr(self, "captured"):
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return
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@ -119,6 +144,17 @@ class PyQtMainEntry(QMainWindow, Ui_MainWindow):
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self.labelResult.setPixmap(QPixmap.fromImage(QImg).scaled(
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self.labelResult.size(), Qt.KeepAspectRatio, Qt.SmoothTransformation))
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def btnSaveImage_Clicked(self):
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if not hasattr(self, "captured"): # 检查是否已捕获图像
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return
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filename, _ = QFileDialog.getSaveFileName(self, '保存图片') # 弹出保存文件对话框
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if filename: # 如果用户选择了保存路径
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cv.imwrite(str(filename), self.captured) # 将捕获的图像保存到选择的路径
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if __name__ == "__main__":
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app = QtWidgets.QApplication(sys.argv)
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window = PyQtMainEntry()
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