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boltmeasure.py
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boltmeasure.py
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import cv2
import time
import numpy as np
def find_peak(th_row, th_col): #Finds the positions of all the threads in the bolt
rows = th_row.shape[0]
check_width = 20
p_row = np.array([], np.int16)
p_column = np.array([], np.int16)
i = check_width
end_flag = False
first_time = True
while i < rows - check_width:
if th_row[i] <= th_row[i-1] and th_row[i] <= th_row[i+1]:
peak_flag = True
for p in range(1, check_width):
if th_row[i] > th_row[i-p] or th_row[i] > th_row[i+p]:
peak_flag = False
break
if peak_flag:
if first_time:
first_time = False
elif p_row[-1] - th_row[i] > 50:
end_flag = True
break
p_row = np.append(p_row, th_row[i])
p_column = np.append(p_column, th_col[i])
i += check_width - 5
if end_flag:
break
i += 1
return p_row, p_column
def find_valley(th_row, th_col): #Finds the position of all the valleys between two threads in the bolt
rows = th_row.shape[0]
check_width = 30
v_row = np.array([], np.int16)
v_column = np.array([], np.int16)
i = check_width
end_flag = False
first_time = True
while i < rows - check_width:
if th_row[i] >= th_row[i-1] and th_row[i] >= th_row[i+1]:
valley_flag = True
for p in range(1, check_width):
if th_row[i] < th_row[i-p] or th_row[i] < th_row[i+p]:
valley_flag = False
break
if valley_flag:
if first_time:
first_time = False
elif (v_row[-1] - th_row[i]) > 50:
end_flag = True
break
v_row = np.append(v_row, th_row[i])
v_column = np.append(v_column, th_col[i])
i += check_width - 5
if end_flag:
break
i += 1
return v_row, v_column
def Noise(p_row,v_row): #Removes Noise caused by glare
p_avg=np.mean(p_row)
noisepos_peak=list()
for i in range(0,len(p_row)):
if(p_row[i]> p_avg+30 or p_row[i]< p_avg-30):
noisepos_peak.append(i)
peak=np.array(np.delete(p_row,noisepos_peak),np.int16)
v_avg=np.mean(v_row)
noisepos_valley=list()
for i in range(0,len(valley_row)):
if(v_row[i]> v_avg+30 or v_row[i]< v_avg-30):
noisepos_valley.append(i)
valley=np.array(np.delete(v_row,noisepos_valley),np.int16)
return peak,valley
def show_peak_valley(img, v_row, v_column, p_row, p_column): #Plots a point on the individual threads as given by the laser profile
#cv2.circle(img, (250, 250), 50, (100, 50, 200), -1)
for i in range(v_row.shape[0]):
cv2.circle(img, (int(v_column[i]), int(v_row[i])), 1, (0, 255, 0), -1)
for i in range(p_row.shape[0]):
cv2.circle(img, (int(p_column[i]), int(p_row[i])), 1, (255, 0, 0), -1)
cv2.imshow("valleysssss", img)
img = cv2.imread('znap24.jpg')
img = img[100:1200,100:2000]
redChannel = img[:, :, 2]
#redChannel = cv2.bilateralFilter(redChannel, 10, 100, 100)
retval,binaryImage = cv2.threshold(redChannel, 80, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU)
thread_row = np.array([])
thread_col = np.array([])
top=0
bottom=0
#print(binaryImage.shape[0])
#print(binaryImage.shape[1])
'''start = time.time()
for column in range(1, binaryImage.shape[1]):
top_flag = False
for row in range(1, binaryImage.shape[0]):
if binaryImage[row, column] != 0:
top = column
break
if top != 0:
break
for column in range(binaryImage.shape[1] - 1, top, -1):
for row in range(1, binaryImage.shape[0]):
if binaryImage[row, column] != 0:
bottom = column;
break
if bottom != 0:
break
stop = time.time()
'''
for column in range(binaryImage.shape[1]):
for row in range(binaryImage.shape[0]):
if binaryImage[row, column] != 0:
thread_row = np.append(thread_row, row)
thread_col = np.append(thread_col, column)
break
temp = np.diff(thread_row, 1)
temp = np.where(temp < -50)
print("Hello")
print(temp)
valley_row, valley_column = find_valley(thread_row, thread_col)
peak_row, peak_column = find_peak(thread_row, thread_col)
top = thread_col[0]
bottom = thread_col[-1]
print("No of pixels from top to bottom is {}".format((bottom - top)*5.9/1104))
#print("Time is {}".format(stop-start))
print("Peaks:")
print(peak_row)
print("their pos:")
print(peak_column)
print("peak diff")
print(np.diff(peak_column, 1))
print("Valleys")
print(valley_row)
print("their pos:")
print(valley_column)
print("valley diff")
print(np.diff(valley_column,1)*5.9/1104)
peaks,valleys=Noise(peak_row,valley_row)
show_peak_valley(img, valleys, valley_column, peaks, peak_column)
#cv2.imshow('org', redChannel)
cv2.imshow('otsu', binaryImage)
cv2.waitKey(0)
cv2.destroyAllWindows()