This page contains some simple OpenCV-Python codes that you may find useful
(See here if you want to know how to install OpenCV-Python)
Code 1: Generate simulated fringe patterns of various wavelengths (pitches)
import cv2 as cv
import numpy as np
import math
I1 = np.zeros((300,300), np.uint8)
p = 0.06 # p controls the fringe pitch
for i in range(0,300):
for j in range(0,300):
I1[i,j] = ((2+2*math.cos(p*math.pi*j))*1/4)*255
cv.imshow('Fringe pattern',I1)
cv.imwrite('fringe.jpg',I1)
cv.waitKey(0)
cv.destroyAllWindows()
Code 2: Find average of four grayscale images captured using four directional lightings
import cv2 as cv
import numpy as np
# read images
I1 = cv.imread('image1a.jpg',0)
cv.imshow('Image 1',I1)
I2 = cv.imread('image1b.jpg',0)
cv.imshow('Image 2',I2)
I3 = cv.imread('image1c.jpg',0)
cv.imshow('Image 3',I3)
I4 = cv.imread('image1d.jpg',0)
cv.imshow('Image 4',I4)
# normalize images
I1n = I1/255
I2n = I2/255
I3n = I3/255
I4n = I4/255
# find size of image
m = I1.shape[0]
n = I1.shape[1]
# find average of all images
I_avg = np.zeros((m,n))
for i in range(0,m):
for j in range(0,n):
I_avg[i,j] = (I1n[i,j]+I2n[i,j]+I3n[i,j]+I4n[i,j])/4
I_out = I_avg*255
I_out2 = I_out.astype(np.uint8)
# brighten image
I_out3 = I_out2+30
cv.imshow('Average image 2',I_out3)
cv.waitKey(0)
cv.destroyAllWindows()
Output
Code 3: Detect subpixel edge in grayscale image
(Note: The code is based on the moment invariant algorithm first developed by A.J. Tabatabai and O.R. Mitchell, 'Edge Location to Subpixel Values in Digital Imagery' - DOI: 10.1109/TPAMI.1984.4767502)
import cv2 as cv
import numpy as np
import matplotlib.pyplot as plt
import math
# read input image
I1 = cv.imread('image2.tif',0)
# display image
cv.imshow('Input image',I1)
plt.imshow(I1,cmap='gray')
# get image size
m = I1.shape[0]
n = I1.shape[1]
k1 = np.arange(n,dtype=float)
k2 = np.arange(n,dtype=float)
for j in range(0,n):
arr1 = np.array(I1[0:m,j],dtype=np.int64)
m1 = sum(arr1)/m
m2 = sum(np.square(arr1))/m
m3 = sum(np.power(arr1,3))/m
sg = math.sqrt(abs(m2 - m1**2))
s = (m3+2*m1**3-3*m1*m2)/sg**3
p1 = (1+s*(math.sqrt(1/(4+s**2))))/2
p2 = 1-p1
h1 = m1-sg*(math.sqrt(p2/p1))
h2 = m1+sg*(math.sqrt(p2/p1))
k1[j] = p1*m
k2[j] = p2*m
plt.plot(np.arange(n),k1,'r',linewidth=1.2)
plt.xticks([]), plt.yticks([]), plt.show()
cv.waitKey()
cv.destroyAllWindows()
Code 4: Detect damage on pill tablet using webcam and Arduino board
(Note: This code will enable you to develop a simple machine vision system using a webcam and output the result of inspection by lighting up LEDs on an Arduino board)
​import cv2 as cv
import pyfirmata
import time
cam = cv.VideoCapture(0)
result, I1 = cam.read()
I2 = I1[150:400,150:400]
cv.imshow("Cropped image", I2)
I3 = cv.cvtColor(I2,cv.COLOR_BGR2GRAY)
cv.imshow("Gray image", I3)
ret,I3bw = cv.threshold(I3,150,255,cv.THRESH_BINARY)
cv.imshow('After threshold',I3bw)
# determine area
output = cv.connectedComponentsWithStats(I3bw,8,cv.CV_32S)
stats = output[2]
area = stats[1][cv.CC_STAT_AREA]
print('Area = ',area)
board = pyfirmata.Arduino('COM3')
if area > 3300:
print('PASSED')
board.digital[11].write(1)
time.sleep(1)
elif area < 3300:
print('FAILED')
board.digital[12].write(1)
time.sleep(1)
cv.waitKey(0)
cv.destroyAllWindows()
board.digital[11].write(0)
board.digital[12].write(0)