gridのネガの写真から○を抽出し、一枚の画像にするpythonコードである。

griddetect.py

import cv2
import numpy as np
import itertools
import re
import glob


#cv2.namedWindow('trim')

markrad = 30

template = np.zeros((markrad*2, markrad*2), np.uint8)
cv2.circle(template, (markrad,markrad), markrad, 255, -1)

grids = np.zeros((markrad*2*5, markrad*2*1), np.uint8)
canvas = np.zeros((600, 300), np.uint8)

#cv2.imshow('grid',template)
#cv2.waitKey(0)
#cv2.destroyAllWindows()

gridlist = []

path = 'C:\\Users\\GTR\\Documents\\lab_log\\log\\H29_2\\20170209\\nega_pic\\'

#gridname = open(path + 'ver2_gridpoint_stage_type2.txt','r')

files = glob.glob("C:\\Users\\GTR\\Documents\\lab_log\\log\\H29_2\\20170209\\nega_pic\\ver2_20170208_namechange\\*.png")

rowlist = (5,15,25,35,45)
collist = (0,10,20,30,40)

for c in range(len(collist)):
    grids = np.zeros((markrad*2*1, markrad*2*5), np.uint8)
    for r in range(len(rowlist)):
#for c,r in itertools.product(range(len(collist)), range(len(rowlist))):
        print c,r
        for file in files:
            path = file
            #print path
            itemlist = path.split('_')
            num = len(itemlist)
            #print num
            x_p = float(itemlist[6])        
            rx = round(x_p)
            y_p = float(itemlist[7])
            ry = round(y_p)
            #print rx,ry
            
            damy_x = int(rx + 15)
            damy_y = int(abs(ry))
            
            #print damy_x,damy_y
        
            if rowlist[r-1] == damy_x and collist[c- 1] == damy_y:
                #print path
                #print rx,ry
                #print damy_x,damy_y
                aaa = cv2.imread(file,cv2.CV_LOAD_IMAGE_GRAYSCALE)
                aaa_c = aaa.copy()
                
                res = cv2.matchTemplate(aaa,template,eval("cv2.TM_CCORR_NORMED"))
                min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
                top_left = max_loc
                
                x = top_left[0]
                y = top_left[1]
                w, h = template.shape[::-1]
            
                cx = x + w/2
                cy = y + h/2
                
                strings = "{0} {1}   {2} {3}\n".format(cx, cy, x_p, y_p)
                #print strings
                    
                #cv2.imwrite('grids_ver1_{0}_{1}.png'.format(x_p,y_p), aaa_c[y:y+h,x:x+w].copy())
                #grids[0*h:1*h, r*w:(r+1)*w] = aaa_c[y:y+h,x:x+w].copy()

        w_g, h_g = grids.shape[::-1]    
        c_can = 2*c + 1
        #canvas[c_can*h_g:(c_can+1)*h_g,20: 20 + w_g]= grids.copy()

rowlist = (0,10,20,30,40)
collist = (5,15,25,35,45)
for c in range(len(collist)):
    grids = np.zeros((markrad*2*1, markrad*2*5), np.uint8)
    for r in range(len(rowlist)):
#for c,r in itertools.product(range(len(collist)), range(len(rowlist))):
        print c,r
        for file in files:
            path = file
            #print path
            itemlist = path.split('_')
            num = len(itemlist)
            #print num
            x_p = float(itemlist[6])        
            rx = round(x_p)
            y_p = float(itemlist[7])
            ry = round(y_p)
            #print rx,ry
            
            damy_x = int(rx + 15)
            damy_y = int(abs(ry))
            
            #print damy_x,damy_y
        
            if rowlist[r-1] == damy_x and collist[c- 1] == damy_y:
                #print path
                #print rx,ry
                #print damy_x,damy_y
                aaa = cv2.imread(file,cv2.CV_LOAD_IMAGE_GRAYSCALE)
                aaa_c = aaa.copy()
                
                res = cv2.matchTemplate(aaa,template,eval("cv2.TM_CCORR_NORMED"))
                min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
                top_left = max_loc
                
                x = top_left[0]
                y = top_left[1]
                w, h = template.shape[::-1]
            
                cx = x + w/2
                cy = y + h/2
                
                strings = "{0} {1}   {2} {3}\n".format(cx, cy, x_p, y_p)
                #print strings
                #cv2.imwrite('grids_ver1_{0}_{1}.png'.format(x_p,y_p), aaa_c[y:y+h,x:x+w].copy())
                #grids[0*h:1*h, r*w:(r+1)*w] = aaa_c[y:y+h,x:x+w].copy()

        w_g, h_g = grids.shape[::-1]    
        c_can = 2*c
        #canvas[c_can*h_g:(c_can+1)*h_g,0:w_g]= grids.copy()

#cv2.imwrite('grids_ver1.bmp', canvas)

cv2.destroyAllWindows()

'''
rowlist = (0,10,20,30,40)
collist = (5,15,25,35,45)
for c,r in itertools.product(range(len(collist)), range(len(rowlist))):
    #print c,r
    a = 0

'''

for file in files:
    path = file
    #print path
    itemlist = path.split('_')
    num = len(itemlist)
    #print num
    
    x_p = float(itemlist[6])        
    rx = round(x_p)
    y_p = float(itemlist[7])
    ry = round(y_p)
    #print rx,ry
    
    damy_x = int(rx + 15)
    damy_y = int(abs(ry))
    
    #print damy_x,damy_y

    damy_x = 0
    damy_y = 0

    
    aaa = cv2.imread(file,cv2.CV_LOAD_IMAGE_GRAYSCALE)
    aaa_c = aaa.copy()
    
    ret,thre = cv2.threshold(aaa, 50 , 255, cv2.THRESH_BINARY)
    #cv2.imshow('aaa',aaa)
    #cv2.waitKey(0)
    #cv2.destroyAllWindows()
    
#    rev = np.zeros_like(aaa)
#    cv2.bitwise_not(aaa,rev)
#    cv2.imshow('rev',rev)
#    cv2.waitKey(0)
#    cv2.destroyAllWindows()
    
    res = cv2.matchTemplate(thre,template,eval("cv2.TM_CCORR_NORMED"))
    min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
    top_left = max_loc
    
    x = top_left[0]
    y = top_left[1]
    w, h = template.shape[::-1]

    cx = x + w/2
    cy = y + h/2
    
    strings = "{0} {1}   {2} {3}\n".format(cx, cy, x_p, y_p)
    #print strings
    cv2.imwrite('grids_ver2_{0}_{1}.png'.format(x_p,y_p), aaa_c[y:y+h,x:x+w].copy())
    #grids[damy_y*h:(damy_y+1)*h, damy_x*w:(damy_x+1)*w] = aaa_c[y:y+h,x:x+w].copy()

#cv2.imwrite('grids.bmp', canvas)

cv2.destroyAllWindows()