python opencv detects and extracts target color

This time I will bring you python opencv detects and extracts the target color, python opencv detects and extracts the target color. What are the precautions? Here is a practical case, let’s take a look one time.

An example is shown below:

# -*- coding:utf-8 -*-
author = 'kingking'
version = '1.0'
date = '14/07/2017'
import cv2
import numpy as np
import time
if name == 'main':
 Img = cv2.imread('example.png')#读入一幅图像
 kernel_2 = np.ones((2,2),np.uint8)#2x2的卷积核
 kernel_3 = np.ones((3,3),np.uint8)#3x3的卷积核
 kernel_4 = np.ones((4,4),np.uint8)#4x4的卷积核
 if Img is not None:#判断图片是否读入
  HSV = cv2.cvtColor(Img, cv2.COLOR_BGR2HSV)#把BGR图像转换为HSV格式
  '''
  HSV模型中颜色的参数分别是：色调（H），饱和度（S），明度（V）
  下面两个值是要识别的颜色范围
  '''
  Lower = np.array([20, 20, 20])#要识别颜色的下限
  Upper = np.array([30, 255, 255])#要识别的颜色的上限
  #mask是把HSV图片中在颜色范围内的区域变成白色，其他区域变成黑色
  mask = cv2.inRange(HSV, Lower, Upper)
  #下面四行是用卷积进行滤波
  erosion = cv2.erode(mask,kernel_4,iterations = 1)
  erosion = cv2.erode(erosion,kernel_4,iterations = 1)
  dilation = cv2.dilate(erosion,kernel_4,iterations = 1)
  dilation = cv2.dilate(dilation,kernel_4,iterations = 1)
  #target是把原图中的非目标颜色区域去掉剩下的图像
  target = cv2.bitwise_and(Img, Img, mask=dilation)
  #将滤波后的图像变成二值图像放在binary中
  ret, binary = cv2.threshold(dilation,127,255,cv2.THRESH_BINARY) 
  #在binary中发现轮廓，轮廓按照面积从小到大排列
  contours, hierarchy = cv2.findContours(binary,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE) 
  p=0
  for i in contours:#遍历所有的轮廓
   x,y,w,h = cv2.boundingRect(i)#将轮廓分解为识别对象的左上角坐标和宽、高
   #在图像上画上矩形（图片、左上角坐标、右下角坐标、颜色、线条宽度）
   cv2.rectangle(Img,(x,y),(x+w,y+h),(0,255,),3)
   #给识别对象写上标号
   font=cv2.FONT_HERSHEY_SIMPLEX
   cv2.putText(Img,str(p),(x-10,y+10), font, 1,(0,0,255),2)#加减10是调整字符位置
   p +=1
  print '黄色方块的数量是',p,'个'#终端输出目标数量
  cv2.imshow('target', target)
  cv2.imshow('Mask', mask)
  cv2.imshow("prod", dilation)
  cv2.imshow('Img', Img)
  cv2.imwrite('Img.png', Img)#将画上矩形的图形保存到当前目录  
 while True:
  Key = chr(cv2.waitKey(15) & 255)
  if Key == 'q':
   cv2.destroyAllWindows()
   break

Original image

Image saved after processing

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Recommended reading:

Implementation of python batch reading of images and storing them in the database

In Python3.5 in Window10 How to install opencv

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