積層画像同士でのパターンマッチを行うプログラムです。

beampattern.py

# -*- coding: utf-8 -*-
"""
Created on Wed Aug 17 15:27:51 2016

@author: ryousuke
"""


import numpy as np
import cv2
#from array import array
#import re

import pandas as pd
from os.path import join, relpath
from glob import glob
import itertools
import ROOT
import math



ROOT.std.__file__ = 'dummy_for_old_pyastro'

ROOT.gROOT.Reset()

path = "C:\\Users\\GTR\\Documents\\lab_log\\log\\H28_11\\20161117\\beam_info\\GTR_test\\img\\"

orizin = 42

#上側の積層画像から輝度値のまとまりを読み取る。
img_u = cv2.imread(path + "beam_8_thre4_{0}-{1}.png".format(orizin,orizin + 7),0);
cv2.imshow('img_u',img_u*30)
img_c_u = img_u.copy()
threshold = 2
max_bri = 255
ret_u,thre_u = cv2.threshold(img_c_u, threshold, max_bri, cv2.THRESH_BINARY)
cv2.imshow('thre_u',thre_u)
contours_u = cv2.findContours(thre_u, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)

#下側の積層画像から輝度値のまとまりを読み取る。
img_d = cv2.imread(path + "beam_8_thre4_{0}-{1}.png".format(orizin + 7,orizin + 14),0);
cv2.imshow('img_d',img_d*30)
img_c_d = img_d.copy()
ret_d,thre_d = cv2.threshold(img_c_d, threshold, max_bri, cv2.THRESH_BINARY)
cv2.imshow('thre_d',thre_d)
cv2.waitKey(0)
cv2.destroyAllWindows()
contours_d = cv2.findContours(thre_d, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)

#cv2.imwrite("beam_8_42-49_bin.png",thre_u)
#cv2.imwrite("beam_8_56-63_bin.png",thre_d)

mom_u = []
#bu = ROOT.TNtuple('bu','beam','cx:cy')
mom_d = []
#bd = ROOT.TNtuple('bd','beam','cx:cy')

#輝度値のまとまりごとに重心を取得する。
for cu in contours_u[0]:
    mom = {}
    M = cv2.moments(cu)
    if M['m00'] != 0:
        cx = int(M['m10']/M['m00'])
        cy = int(M['m01']/M['m00'])
        mom['cx'] = int(cx)
        mom['cy'] = int(cy)
        mom_u.append(mom)
    else:
        cx = 0
        cy = 0

#    bu.Fill(cx,cy)

for cd in contours_d[0]:
    mom = {}
    M = cv2.moments(cd)
    if M['m00'] != 0:
        cx = int(M['m10']/M['m00'])
        cy = int(M['m01']/M['m00'])
        
        mom['cx'] = int(cx)
        mom['cy'] = int(cy)
        mom_d.append(mom)
    else:
        cx = 0
        cy = 0
       
#    mom['cx'] = int(cx)
#    mom['cy'] = int(cy)
#    mom_d.append(mom)
#    bd.Fill(cx,cy)

#取得した重心の座標でパターンマッチを行う。
c1 = ROOT.TCanvas('c1','Example with Formula',200,10,700,700)
h2dydx = ROOT.TH2D("h2dydx",";x[pix];y[pix]",100, -50, 50, 100, -50, 50)

for b_u,b_d in itertools.product(mom_u,mom_u):
#    print(b_u,b_d)
    
#もしかしたら、画像の中心を（0，0）になるようにしなければならないかも
#その場合は、絶対値（abs）を使用する必要あり    
    r = math.sqrt((b_u['cx'] - b_d['cx'])**2 + (b_u['cy'] - b_d['cy'])**2)
    
    if r > 100:
        continue
    
    dx = b_u['cx'] - b_d['cx']
    dy = b_u['cy'] - b_d['cy']
    h2dydx.Fill(dx,dy)

print 'finish'
h2dydx.Draw('colz')
#c1.Print('Beampattern:{0}-{1} to {2}-{3}.png'.format(orizin,orizin + 7,orizin + 7,orizin + 14))