自学教程：PyQt5实现将Matplotlib图像嵌入到Scoll Area中显示滚动条效果

import cv2import osimport sysimport mathfrom PyQt5 import QtCorefrom PyQt5.QtWidgets import *from PyQt5.uic import loadUiimport matplotlibfrom matplotlib import pyplot as pltmatplotlib.use("Qt5Agg")  # 声明使用QT5from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvasmatplotlib.use("Qt5Agg")  # 声明使用QT5from matplotlib.backends.backend_qt5agg import NavigationToolbar2QT as NavigationToolbar#创建一个matplotlib图形绘制类class MyFigure(FigureCanvas):    def __init__(self,width, height, dpi):         # 创建一个Figure,该Figure为matplotlib下的Figure，不是matplotlib.pyplot下面的Figure        self.fig = plt.figure(figsize=(width, height), dpi=dpi)         # 在父类中激活Figure窗口，此句必不可少，否则不能显示图形        super(MyFigure,self).__init__(self.fig)         # 调用Figure下面的add_subplot方法，类似于matplotlib.pyplot下面的subplot(1,1,1)方法class scollarea_showpic(QMainWindow):    def __init__(self, queryPath=None, samplePath=None,limit_value = None):        super().__init__()        self.queryPath = queryPath  # 图库路径        self.samplePath = samplePath  # 样本图片        self.limit_value = limit_value        self.ui()        plt.rcParams['font.sans-serif'] = ['KaiTi']  # 只有这样中文字体才可以显示    def ui(self):        loadUi('./testpiv.ui', self)        self.SIFT(self.queryPath,self.samplePath,self.limit_value)    def getMatchNum(self,matches,ratio):        '''返回特征点匹配数量和匹配掩码'''        matchesMask=[[0,0] for i in range(len(matches))]        matchNum=0        for i,(m,n) in enumerate(matches):            if m.distance < ratio * n.distance: #将距离比率小于ratio的匹配点删选出来                matchesMask[i]=[1,0]                matchNum+=1        return (matchNum,matchesMask)    def SIFT(self,dirpath,picpath,limit_value):        # path='F:/python/gradu_design/gra_des/'        queryPath=dirpath #图库路径        samplePath=picpath  #样本图片        comparisonImageList=[] #记录比较结果        #创建SIFT特征提取器        sift = cv2.xfeatures2d.SIFT_create()        #创建FLANN匹配对象        """        FLANN是类似最近邻的快速匹配库            它会根据数据本身选择最合适的算法来处理数据            比其他搜索算法快10倍        """        FLANN_INDEX_KDTREE=0        indexParams=dict(algorithm=FLANN_INDEX_KDTREE,trees=5)        searchParams=dict(checks=50)        flann=cv2.FlannBasedMatcher(indexParams,searchParams)        sampleImage=cv2.imread(samplePath,0)        kp1, des1 = sift.detectAndCompute(sampleImage, None) #提取样本图片的特征        for parent,dirnames,filenames in os.walk(queryPath):            print('parent :',parent,'   ','dirnames :',dirnames)            for p in filenames:                p=queryPath+p                # print('pic file name :',p)                queryImage=cv2.imread(p,0)                kp2, des2 = sift.detectAndCompute(queryImage, None) #提取比对图片的特征                matches=flann.knnMatch(des1,des2,k=2) #匹配特征点，为了删选匹配点，指定k为2，这样对样本图的每个特征点，返回两个匹配                (matchNum,matchesMask) = self.getMatchNum(matches,0.9) #通过比率条件，计算出匹配程度                matchRatio=matchNum*100/len(matches)                drawParams=dict(matchColor=(0,255,0),                        singlePointColor=(255,0,0),                        matchesMask=matchesMask,                        flags=0)                comparisonImage=cv2.drawMatchesKnn(sampleImage,kp1,queryImage,kp2,matches,None,**drawParams)                comparisonImageList.append((comparisonImage,matchRatio)) #记录下结果        comparisonImageList.sort(key=lambda x:x[1],reverse=True) #按照匹配度排序  降序        new_comparisonImageList = comparisonImageList[:limit_value]        count=len(new_comparisonImageList)        column = 1 # 列        row = math.ceil(count/column) # 行   math.ceil: 函数返回大于或等于一个给定数字的最小整数        print('列:',column,  '  ','行:',row)        #绘图显示        F = MyFigure(width=10, height=10, dpi=100)  # 500 * 400        for index,(image,ratio) in enumerate(new_comparisonImageList):            F.axes = F.fig.add_subplot(row,column,index+1)            F.axes.set_title('Similiarity %.2f%%' % ratio)            plt.imshow(image)            # 调整subplot之间的间隙大小            plt.subplots_adjust(hspace=0.2)        self.figure = F.fig        # FigureCanvas:画布        self.canvas = FigureCanvas(self.figure)  # fig 有 canvas        self.canvas.resize(self.picwidget.width(), 3000) # 画布大小        self.scrollArea = QScrollArea(self.picwidget)  # picwidget上有scroll        self.scrollArea.setFixedSize(self.picwidget.width(), self.picwidget.height())        self.scrollArea.setWidget(self.canvas)  # widget上有scroll   scroll有canvas        self.nav = NavigationToolbar(self.canvas, self.picwidget)  # 创建工具栏        self.setMinimumSize(self.width(), self.height())        self.setMaximumSize(self.width(), self.height())        self.setWindowTitle('Test')if __name__ == "__main__":    app = QApplication(sys.argv)    queryPath='F:/python/gradu_design/gra_des/imges/' #图库路径    samplePath='F:/python/gradu_design/gra_des/imges/resized_logo1_1.jpg'  #样本图片    main = scollarea_showpic(queryPath,samplePath,3)    main.show()    sys.exit(app.exec_())