初尝图像识别

第一次接触图像识别是在2019的亚太数学建模上当时选择的是A题

利用photoshop对图像进行处理和提取

1. 利用Python寻找SiO2的轮廓坐标

import numpy as np
num = 497
while(num<=610):
    print(num)
    str1 = '%d'%num
    str = 'C:\\Users\\Li\\PycharmProjects\\Demo\\0'+str1+'.jpg'
    img = cv2.imread(str)
    num=num+1
    img_original=cv2.imread(str)
    img_gray=cv2.cvtColor(img_original,cv2.COLOR_BGR2GRAY)
    #求二值图像
    retv,thresh=cv2.threshold(img_gray,125,255,1)
    #寻找轮廓
    contours,hierarchy=cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
    #绘制轮廓
    cv2.drawContours(img_original,contours,-1,(0,0,255),3,lineType=cv2.LINE_AA)
    #显示图像
    #cv2.imshow('Contours',img_original)
    #cv2.namedWindow('Contours',0)
    cv2.waitKey()
    cv2.destroyAllWindows()
    #print(hierarchy)
    #print(contours[1])
    str2 = 'C:\\Users\\Li\\PycharmProjects\\Demo\\data\\'+str1+'.txt'
    data = open(str2, 'w+')
    print(contours[1], file=data)
data.close()

2. 利用Python寻找SiO2的面积、周长、质心

import numpy as np
num = 497
while(num<=610):
    str1 = '%d'%num
    str = 'C:\\Users\\Li\\PycharmProjects\\Demo\\0'+str1+'.jpg'
    img = cv2.imread(str)
    num=num+1
    #print("坐标为"+str1)

    ret,thresh = cv2.threshold(cv2.cvtColor(img,cv2.COLOR_BGR2GRAY),127,255,0)
    contours,hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_NONE)#得到轮廓信息
    cnt = contours[0]#取第一条轮廓
    M = cv2.moments(cnt)#计算第一条轮廓的矩
    imgnew = cv2.drawContours(img, contours, -1, (0,255,0), 3)#把所有轮廓画出来
    #print (M)
    #这两行是计算中心点坐标
    cx = int(M['m10']/M['m00'])
    cy = int(M['m01']/M['m00'])

    #计算轮廓所包含的面积
    area = cv2.contourArea(cnt)

    #计算轮廓的周长
    perimeter = cv2.arcLength(cnt,True)

    #轮廓的近似
    epsilon = 0.02*perimeter
    approx = cv2.approxPolyDP(cnt,epsilon,True)
    imgnew1 = cv2.drawContours(img, approx, -1, (0,0,255), 3)
    #cv2.imshow('lunkuo',imgnew)
    #cv2.imshow('approx_lunkuo',imgnew1)
    #print(str[33:37])
    #print("面积")
    #print(area)
    #print("周长")
    #print(perimeter)
    #print("中心点坐标")
    #print(cx)
    #print(cy)
    #print()
cv2.waitKey(0)
cv2.destroyAllWindows()
cv2.waitKey(0)
cv2.waitKey(0)
cv2.waitKey(0)
cv2.waitKey(0)