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from __future__ import division | |
import cv2 | |
import numpy as np | |
import os | |
#Initalize directory to images | |
path_to_folder = "E:\\New folder" | |
#Initialize different filesets | |
path_to_file_approach1 = "E:\\Approach1.csv" | |
path_to_file_approach2 = "E:\\Approach2.csv" | |
path_to_file_approach3 = "E:\\Approach3.csv" | |
path_to_file_approach4 = "E:\\Approach4.csv" | |
#Initialize output file for each approach | |
def InitializeOutputfile(ApproachCode): | |
if(ApproachCode == '01'): | |
filehandle = open(path_to_file_approach1,'w') | |
return filehandle | |
if(ApproachCode == '02'): | |
filehandle = open(path_to_file_approach2,'w') | |
return filehandle | |
if(ApproachCode == '03'): | |
filehandle = open(path_to_file_approach3,'w') | |
return filehandle | |
if(ApproachCode == '04'): | |
filehandle = open(path_to_file_approach4,'w') | |
return filehandle | |
#Compute EPI DPI | |
def ComputeDPI(ApproachCode, filehandle): | |
files = [] | |
for i in os.listdir(path_to_folder): | |
files.append(i) | |
print(i) | |
if(ApproachCode == '01'): | |
EP_DPI = Approach1(i) | |
print(EP_DPI) | |
filehandle.write(i + "," + str(EP_DPI) + "\n") | |
if(ApproachCode == '02'): | |
EP_DPI = Approach2(i) | |
print(EP_DPI) | |
filehandle.write(i + "," + str(EP_DPI) + "\n") | |
if(ApproachCode == '03'): | |
EP_DPI = Approach3(i) | |
print(EP_DPI) | |
filehandle.write(i + "," + str(EP_DPI) + "\n") | |
if(ApproachCode == '04'): | |
EP_DPI = Approach4(i) | |
print(EP_DPI) | |
filehandle.write(i + "," + str(EP_DPI) + "\n") | |
filehandle.close() | |
def Approach1(img): | |
c = 0.00 | |
img = cv2.imread(path_to_folder + "\\" + img) | |
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) | |
img_gaussian1 = cv2.GaussianBlur(gray,(3,3),0) | |
img_gaussian = img_gaussian1[100:400, 100:400] | |
img_sobelx = cv2.Sobel(img_gaussian,cv2.CV_8U,1,0,ksize=5) | |
img_sobely = cv2.Sobel(img_gaussian,cv2.CV_8U,0,1,ksize=5) | |
#Compute lines using Hough Transformation | |
xlines = cv2.HoughLines(img_sobelx,1,np.pi/180,200) | |
ylines = cv2.HoughLines(img_sobely,1,np.pi/180,200) | |
if(ylines is not None): | |
if(xlines is not None): | |
print('sobel - HoughLines') | |
c = ylines.size/xlines.size | |
return c | |
def Approach2(img): | |
c = 0.00 | |
img = cv2.imread(path_to_folder + "\\" + img) | |
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) | |
img_gaussian1 = cv2.GaussianBlur(gray,(3,3),0) | |
img_gaussian = img_gaussian1[100:400, 100:400] | |
img_sobelx = cv2.Sobel(img_gaussian,cv2.CV_8U,1,0,ksize=5) | |
img_sobely = cv2.Sobel(img_gaussian,cv2.CV_8U,0,1,ksize=5) | |
#Erosion Followed by Dialiton | |
kernel = np.ones((5,5),np.uint8) | |
sobelErosionDialotionx = cv2.morphologyEx(img_sobelx, cv2.MORPH_OPEN, kernel) | |
sobelErosionDialotiony = cv2.morphologyEx(img_sobely, cv2.MORPH_OPEN, kernel) | |
#Compute lines using Hough Transformation | |
xlines = cv2.HoughLines(sobelErosionDialotionx,1,np.pi/180,100) | |
ylines = cv2.HoughLines(sobelErosionDialotiony,1,np.pi/180,100) | |
if(ylines is not None): | |
if(xlines is not None): | |
print('sobel - Erosion Followed by Dialiton') | |
c = ylines.size/xlines.size | |
return c | |
def Approach3(img): | |
c = 0.00 | |
img = cv2.imread(path_to_folder + "\\" + img) | |
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) | |
img_gaussian1 = cv2.GaussianBlur(gray,(3,3),0) | |
img_gaussian = img_gaussian1[100:400, 100:400] | |
img_sobelx = cv2.Sobel(img_gaussian,cv2.CV_8U,1,0,ksize=5) | |
img_sobely = cv2.Sobel(img_gaussian,cv2.CV_8U,0,1,ksize=5) | |
#Dilation followed by Erosion | |
kernel = np.ones((5,5),np.uint8) | |
sobelDialotionErosionx = cv2.morphologyEx(img_sobelx, cv2.MORPH_CLOSE, kernel) | |
sobelDialotionErosiony = cv2.morphologyEx(img_sobely, cv2.MORPH_CLOSE, kernel) | |
xlines = cv2.HoughLines(sobelDialotionErosionx,1,np.pi/180,100) | |
ylines = cv2.HoughLines(sobelDialotionErosiony,1,np.pi/180,100) | |
if(ylines is not None): | |
if(xlines is not None): | |
print('sobel - Dilation followed by Erosion') | |
c = ylines.size/xlines.size | |
return c | |
def Approach4(img): | |
c = 0.00 | |
minLineLength = 200 | |
maxLineGap = 10 | |
img = cv2.imread(path_to_folder + "\\" + img) | |
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) | |
img_gaussian1 = cv2.GaussianBlur(gray,(3,3),0) | |
img_gaussian = img_gaussian1[100:400, 100:400] | |
img_sobelx = cv2.Sobel(img_gaussian,cv2.CV_8U,1,0,ksize=5) | |
img_sobely = cv2.Sobel(img_gaussian,cv2.CV_8U,0,1,ksize=5) | |
#Compute lines using Hough Transformation | |
xlines = cv2.HoughLinesP(img_sobelx,1,np.pi/180,15,minLineLength,maxLineGap) | |
ylines = cv2.HoughLinesP(img_sobely,1,np.pi/180,15,minLineLength,maxLineGap) | |
if(ylines is not None): | |
if(xlines is not None): | |
print('sobel - HoughLinesP') | |
c = ylines.size/xlines.size | |
return c | |
filehandle = InitializeOutputfile("01") | |
ComputeDPI("01", filehandle) | |
filehandle = InitializeOutputfile("02") | |
ComputeDPI("02", filehandle) | |
filehandle = InitializeOutputfile("03") | |
ComputeDPI("03", filehandle) | |
filehandle = InitializeOutputfile("04") | |
ComputeDPI("04", filehandle) |
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