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data_marking.py
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data_marking.py
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# -*- coding: utf-8 -*-
"""
Created on Tue Aug 28 20:16:17 2018
@author: nikhil
"""
import cv2
import numpy as np
import glob
def r_c(hist ):
Ng = 255
tc = 255
index = 0
while index <= tc and index <= Ng:
bck_sum = 0
hist_sum_bck = 0
fr_sum = 0
hist_sum_fr = 0
b = 0
f = 0
for i in range(0, index+1):
bck_sum += i * hist[i][0]
hist_sum_bck += hist[i][0]
for j in range(index+1, Ng+1):
fr_sum += j * hist[j][0]
hist_sum_fr += hist[j][0]
try:
b = (bck_sum / hist_sum_bck)
f = (fr_sum / hist_sum_fr)
if hist_sum_bck == 0.0 :
raise ZeroDivisionError
if hist_sum_fr == 0.0:
raise ZeroDivisionError
except ZeroDivisionError:
index += 1
continue
tc = (b + f) // 2
index += 1
return tc
def excGrnApp(b, g, r, pmin, pmax):
row, col = g.shape
Eg = np.zeros([row, col], np.uint8 )
for i in range(0, row):
for j in range(0, col):
try:
d = (2*g[i][j] - r[i][j] - b[i][j])//(g[i][j] + r[i][j] + b[i][j])
except:
d = 0
try:
d = int((d - pmin) * 255 //( pmax - pmin))
except:
d = 0
Eg[i][j] = d
return Eg
def regionfill(img):
contour, hier = cv2.findContours(img, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
Ar = 0
for cnt in contour:
cv2.drawContours(img, [cnt],0,255,-1)
Ar += cv2.contourArea(cnt)
return img, Ar
def lloret(b, g, r, img):
row, col = b.shape
z = np.zeros([row, col], np.uint8)
for i in range(0, row):
for j in range(0, col):
if g[i][j] > b[i][j] and g[i][j] > r[i][j]:
z[i][j] = g[i][j]
_, thresh = cv2.threshold(z, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
return thresh
def calArea(img):
contour, hier = cv2.findContours(img, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
Ar = 0
for cnt in contour:
Ar += cv2.contourArea(cnt)
return Ar
def leafNDisArea(img):
b, g, r = cv2.split(img)
# LEAF SEGMENTATION & AREA CALC
gray_grn = excGrnApp(b, g, r, -1, 2)
hist = cv2.calcHist([gray_grn],[0],None,[256],[0,256])
thr = int(r_c(hist))
_, bin_img = cv2.threshold(gray_grn, thr, 255, cv2.THRESH_BINARY)
bin_img = cv2.medianBlur(bin_img, 3)
bin_img, AT = regionfill(bin_img)
# LESION SEGMENTATION & GREEN AREA CALCULATION
grn_area = lloret(b, g, r, img.copy())
AU = calArea(grn_area)
per_inf = round(((AT - AU) * 100 / AT), 3)
return AT, AT-AU, per_inf
if __name__ == '__main__':
# change the filename according to the folder
file = open('healthy_test_result.txt', 'r+')
file.write('Filenum\t Total Area\t Infected Area\t Infection (%)\t Category')
filenum = 0
percentSum = 0
for filename in glob.glob('*.JPG'):
filenum += 1
leaf = cv2.imread(filename)
AT, AI, P = leafNDisArea(leaf)
percentSum += P
file.write('\n')
file.write(('{:<15} {:<15} {:<15} {:<10} {:<15}'.format(filenum, AT, AI, P, 'Healthy')))
for filename in glob.glob('*.jpg'):
filenum += 1
leaf = cv2.imread(filename)
AT, AI, P = leafNDisArea(leaf)
percentSum += P
file.write('\n')
file.write(('{:<15} {:<15} {:<15} {:<10} {:<15}'.format(filenum, AT, AI, P, 'Healthy')))
avg_per = round(percentSum/filenum, 3)
#file.write('\n\n Average percentage error = ' + str( avg_per) )
file.close()