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

import cv2
import os
import sys
import math

from PyQt5 import QtCore
from PyQt5.QtWidgets import *
from PyQt5.uic import loadUi
import matplotlib
from matplotlib import pyplot as plt
matplotlib.use("Qt5Agg")  # 声明使用QT5
from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
matplotlib.use("Qt5Agg")  # 声明使用QT5
from 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scrollscroll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_())