OpenCV-Python学习笔记（使用opencv识别物体的位置，找到中心点位）

 使用opencv识别物体的位置，找到中心点位：

步骤：先拿到图像-->进行高斯滤波-->进行灰度处理-->进行二值化-->进行开运算-->轮廓提取-->计算中心点位

效果图如下：

 代码如下：

import cv2
import numpy as np

#读取图片
def ReadImg():
    img = cv2.imread('1.png',1)
    cv2.imshow('src',img)
    return img

#高斯滤波
def GausBlur(src):
    dst = cv2.GaussianBlur(src,(5,5),1.5)
    cv2.imshow('GausBlur',dst)
    return dst

#灰度处理
def Gray_img(src):
    gray = cv2.cvtColor(src,cv2.COLOR_BGR2GRAY)
    cv2.imshow('gray',gray)
    return gray

#二值化
def threshold_img(src):
    ret, binary = cv2.threshold(src,0,255,cv2.THRESH_BINARY | cv2.THRESH_TRIANGLE)
    print("threshold value %s"%ret)
    cv2.imshow('threshold',binary)
    return binary
    
#开运算操作
def open_mor(src):
    kernel = np.ones((5,5),np.uint8)
    opening = cv2.morphologyEx(src,cv2.MORPH_OPEN,kernel, iterations=3) #iterations进行3次操作
    cv2.imshow('open',opening)
    return opening

#轮廓拟合
def draw_shape(open_img,gray_img):
    im2, contours, hierarchy = cv2.findContours(open_img, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    cnt = contours[0] #得到第一个的轮廓
  
    rect = cv2.minAreaRect(cnt)
    box = cv2.boxPoints(rect)
    box = np.int0(box)
    cv2.drawContours(src,[box],0,(0,0,255),3) #画矩形框
    
      
    #图像轮廓及中心点坐标
    M = cv2.moments(cnt)# 计算第一条轮廓的各阶矩,字典形式
    center_x = int(M['m10']/M['m00'])
    center_y = int(M['m01']/M['m00'])
    print('center_x:',center_x)
    print('center_y:',center_y)
    cv2.circle(src,(center_x,center_y),7,128,-1)#绘制中心点
    str1 = '(' + str(center_x)+ ',' +str(center_y) +')' #把坐标转化为字符串
    cv2.putText(src,str1,(center_x-50,center_y+40),cv2.FONT_HERSHEY_SIMPLEX,1,(255,255,0),2,cv2.LINE_AA)#绘制坐标点位
    
    cv2.imshow('show',src)
        
src = ReadImg()
gaus_img = GausBlur(src)
gray_img = Gray_img(gaus_img)
thres_img = threshold_img(gray_img)
open_img = open_mor(thres_img)
draw_shape(open_img,src)



cv2.waitKey(0)