PyQt&OpenCV实现边缘检测

首先设计UI界面, 调整自己满意的布局. 其中黑色为 QLabel, 对象名为labelImage, 用于显示图像. 左下角为拖动条, 对称为sliderThreshold, 用于修改参数. Open按钮用于打开文件, 对象名为openButton. 在界面编辑器中, 将Close按钮的clicked信号连接到窗口的close槽.

窗口设计完成后保存到edge.ui, 然后基于edge.ui文件构造程序:

# -*- coding:utf-8 -*-
###########################################################
# PyQt+OpenCV example
#
# 查找图像中的边界.
# 参考 OpenCV\samples\python\edge.py 改写
#
# By chaishushan{AT}gmail.com 2008
###########################################################

import sys

# 导入PyQt模块
from PyQt4.Qt import *
from PyQt4 import uic

# 导入OpenCV模块
from opencv.cv import *
from opencv.highgui import *

# 边界检测类
class WinEdge(QWidget):
    def __init__(self, parent=None):
        QWidget.__init__(self, parent)
        uic.loadUi("edge.ui", self)

        # OpenCV相关参数
        self.cv_img = None
        self.cv_col_edge = None
        self.cv_gray = None
        self.cv_edge = None

        # 标题
        self.defaultTitle = self.windowTitle()


    @pyqtSignature("")
    def on_openButton_clicked(self):
        filename = QFileDialog.getOpenFileName(self,
                            self.tr("Choose a Image"), ".",
                            self.tr("Image Files (*.jpg;*.bmp);;All Files (*)"))

        if not filename.isEmpty():
            self.sliderThreshold.setEnabled(False)

            self.openImage(filename)
            self.dectorEdge(self.sliderThreshold.value())

            # 更新UI
            if self.cv_col_edge:
                self.setWindowTitle(filename)
                self.sliderThreshold.setEnabled(True)
            else:
                self.setWindowTitle(self.defaultTitle)
                self.sliderThreshold.setEnabled(False)

    @pyqtSignature("int")
    def on_sliderThreshold_valueChanged(self, val):

        # 重新计算边界
        self.dectorEdge(val)

    def resizeEvent(self, event):
        self.showImage()

    # 打开图像
    def openImage(self, qstringName):
        # 将QString转换为char *
        filename = qstringName.toLocal8Bit().data()

        # 释放以前的图像
        if self.cv_img :
            cvReleaseImage( self.cv_img ); self.cv_img = None
            cvReleaseImage( self.cv_col_edge ); self.cv_col_edge = None
            cvReleaseImage( self.cv_gray ); self.cv_gray = None
            cvReleaseImage( self.cv_edge ); self.cv_edge = None

        # 打开新的图像
        self.cv_img = cvLoadImage(filename)
        if not self.cv_img:
            msg = self.tr("Can't open %1 file!").arg(filename)
            QMessageBox.warning (self, "Warning", msg)
            return False

        # 创建辅助空间
        size = cvSize(self.cv_img.width, self.cv_img.height)

        self.cv_col_edge = cvCreateImage (size, 8, 3)
        self.cv_gray = cvCreateImage (size, 8, 1)
        self.cv_edge = cvCreateImage (size, 8, 1)

        return True

    # 生成边界

    def dectorEdge(self, position):

        if not self.cv_img: return

        # 转换为灰度
        cvCvtColor (self.cv_img, self.cv_gray, CV_BGR2GRAY)

        cvSmooth (self.cv_gray, self.cv_edge, CV_BLUR, 3, 3, 0)
        cvNot (self.cv_gray, self.cv_edge)

        # run the edge dector on gray scale
        cvCanny (self.cv_gray, self.cv_edge, position, position * 3, 3)

        # 结构保存到cv_col_edge中
        cvSetZero (self.cv_col_edge)
        cvCopy (self.cv_img, self.cv_col_edge, self.cv_edge)

        # 显示
        self.showImage()

    # 显示图像
    def showImage(self):
        if not self.cv_col_edge: return

        # 转化IplImage为QImage
        w = self.cv_col_edge.width
        h = self.cv_col_edge.height

        step = self.cv_col_edge.widthStep
        data = self.cv_col_edge.imageData

        img = QImage(data, w, h, step, QImage.Format_RGB888).rgbSwapped()

        # 显示图像[缩放到窗口大小]
        size = self.labelImage.size()
        self.labelImage.setPixmap(QPixmap.fromImage(img.scaled(size)))

if __name__ == '__main__':
    app = QApplication(sys.argv)
    widget = WinEdge()
    widget.show()
    app.exec_()

运行结果如图:

完整的代码以后补充。

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