Opencv中判断图片里某个颜色值占的比例的方法

/*
在图片里查找指定颜色的比例
*/
int Widget::Mat_color_Find(QImage qimage)
{
  Mat image = QImage2cvMat(qimage);//将图片加载进来
  int num = 0;//记录颜色的像素点
  float rate;//要计算的百分率
  //遍历图片的每一个像素点
  for(int i = 0; i < image.rows;i++) //行数
  {
   for(int j = 0; j <image.cols;j++) //列数
   {
    //对该像素是否为指定颜色进行判断 BGR 像素点
    //OpenCV 中 MAT类的默认三原色通道顺序BGR
    /*
   动态地址访问像素语法：image.at<Vec3b>(i,j)[0]、image.at<uchar>(i, j)
   访问三通道图像的单个像素：
   int b = image.at<Vec3b>(i, j)[0];
   int g = image.at<Vec3b>(i, j)[1];
   int r = image.at<Vec3b>(i, j)[2];
   对于三通道图像，每个像素存储了三个值，分别为蓝色、绿色、红色通道上的数值。
   int gray_data = image.at<uchar>(i, j);
   用来访问灰度图像的单个像素。对于灰度图像，每个像素只存储一个值
   */
    if((image.at<Vec3b>(i, j)[0] <= 120 &&
     image.at<Vec3b>(i, j)[1] <= 120 &&
     image.at<Vec3b>(i, j)[2] <= 120))
    {
     num++;
    }
   }
  }
  rate = (float)num / (float)(image.rows * image.cols);
 
  //阀值为 0.249255 表示为全黑
  if(rate>0.20)
  {
   qDebug()<<":Mat:故意遮挡摄像头";
  }
  qDebug()<<"Mat:比例"<<rate;
  return 0;
}
 
 
Mat Widget::QImage2cvMat(QImage image)
{
 Mat mat;
 switch(image.format())
 {
 case QImage::Format_ARGB32:
 case QImage::Format_RGB32:
 case QImage::Format_ARGB32_Premultiplied:
  mat = Mat(image.height(), image.width(), CV_8UC4, (void*)image.constBits(), image.bytesPerLine());
  break;
 case QImage::Format_RGB888:
  mat = Mat(image.height(), image.width(), CV_8UC3, (void*)image.constBits(), image.bytesPerLine());
  cvtColor(mat, mat, CV_BGR2RGB);
  break;
 case QImage::Format_Indexed8:
  mat = Mat(image.height(), image.width(), CV_8UC1, (void*)image.constBits(), image.bytesPerLine());
  break;
 }
 return mat;
}

/*
在图片里查找指定颜色的比例
*/
int Widget::qimage_color_Find(QImage qimage)
{
 int num = 0;//记录颜色的像素点
 float rate;//要计算的百分率
 quint8 r,g,b;
 //遍历图片的每一个像素点
 for(int i = 0; i < qimage.height();i++) //行数
 {
  for(int j = 0; j <qimage.width();j++) //列数
  {
   QRgb rgb=qimage.pixel(j,i);
   r=qRed(rgb);
   g=qGreen(rgb);
   b=qBlue(rgb);
 
   if((r <= 120 && g <= 120 && b <= 120))
   {
    num++;
   }
  }
 }
 rate = (float)num / (float)(qimage.height() * qimage.width());
 
 //阀值为 0.99777 表示为全黑
 if(rate>0.60)
 {
   //qDebug()<<"qimage:故意遮挡摄像头";
 }
 qDebug()<<"qimage:比例:"<<rate;
 return 0;
}

import cv2
import os
import matplotlib.pyplot as plt
picture_path="/home/wsb/桌面/picture"
picture_list=os.listdir(picture_path)
total_picture=len(picture_list)
total=total_picture
per=[]
number=0#图片中道路类型为1的个数
number1=0#一种道路类型并且比例小于0.0638的个数
number2=0
for item in picture_list:
  src = os.path.join(os.path.abspath(picture_path), item)
  print("start: %s "%item)
  total_picture-=1
  mat=cv2.imread(src)
  height=mat.shape[0]
  width=mat.shape[1]
  ground=0
  zero=0  
  one=0
  two=0
  three=0
  four=0
  five=0
  six=0
  seven=0
  eight=0
  rateground=0
  rate0=0
  rate1=0
  rate2=0
  rate3=0
  rate4=0
  rate5=0
  rate6=0
  rate7=0
  rate8=0
  rate=0
  road_type=0
  for i in range(height):
    for j in range(width):
#      print("r:%s"%mat[i][j][0])
#      print("r:%s"%mat[i][j][1])
#      print("r:%s"%mat[i][j][2])

      '''
      我这里共有9种分类情况，况且我已知道每一种颜色的具体rgb值，我将它们作为我的判断条件
      如不你不知道可以在网上查找自己想查看比例的rgb值或者范围
      '''
      if mat[i][j][0]==0 and mat[i][j][1]==0 and mat[i][j][2]==0:
        ground+=1
      elif mat[i][j][0]==128 and mat[i][j][1]==0 and mat[i][j][2]==0:
        zero+=1
      elif mat[i][j][0]==0 and mat[i][j][1]==128 and mat[i][j][2]==0:
        one+=1
      elif mat[i][j][0]==128 and mat[i][j][1]==128 and mat[i][j][2]==0:
        two+=1
      elif mat[i][j][0]==0 and mat[i][j][1]==0 and mat[i][j][2]==128:
        three+=1
      elif mat[i][j][0]==128 and mat[i][j][1]==0 and mat[i][j][2]==128:
        four+=1
      elif mat[i][j][0]==0 and mat[i][j][1]==128 and mat[i][j][2]==128:
        five+=1
      elif mat[i][j][0]==128 and mat[i][j][1]==128 and mat[i][j][2]==128:
        six+=1
      elif mat[i][j][0]==0 and mat[i][j][1]==0 and mat[i][j][2]==64:
        seven+=1
      elif mat[i][j][0]==0 and mat[i][j][1]==0 and mat[i][j][2]==192:
        eight+=1
      else:
        print("输入正确的图片，或者更改上面判断条件的像素值")
  rateground=ground/(height*width)
  rate0=zero/(height*width)
  if rate0!=0:
    road_type+=1
  rate1=one/(height*width)
  if rate1!=0:
    road_type+=1
  rate2=two/(height*width)
  if rate2!=0:
    road_type+=1
  rate3=three/(height*width)
  if rate3!=0:
    road_type+=1
  rate4=four/(height*width)
  if rate4!=0:
    road_type+=1
  rate5=five/(height*width)
  if rate5!=0:
    road_type+=1
  rate6=six/(height*width)
  if rate6!=0:
    road_type+=1
  rate7=seven/(height*width)
  if rate7!=0:
    road_type+=1
  rate8=eight/(height*width)
  if rate8!=0:
    road_type+=1
  rate=rate0+rate1+rate2+rate3+rate4+rate5+rate6+rate7+rate8
  per.append(rate)
  if road_type==1:
    number+=1
    if rate<0.0638:
      number1+=1#一种类型道路并且所占比例小于0.0638的情况 
  else:
    if rate<0.532:
      number2+=1#两种道路类型，并且正确正确道路类型所占比例小于0.532时的个数
  print("the remaining %d"%total_picture)
A=number/total#图片中道路类型大于1种的概率
A1=number1/total#图片中一种道路类型并且比例小于0.0638的概率
A2=number2/total#图片中有两种道路，并且一种道路所占比例小于0.532时的概率
print("A1:%s"%A1)
print("the precentage of one road is %s"%A)
print("the precentage of two road is %s"%(1-A))
print("A2:%s"%A2)
plt.plot(per)
plt.ylabel('the percentage of road')
plt.show()