simple_thresholding.py

# Python programe to illustrate  
# simple thresholding type on an image 
      
# organizing imports  
import os

import cv2  
import numpy as np  

FILE_PATH = os.path.dirname(__file__)  
# path to input image is specified and   
# image is loaded with imread command  
image1 = cv2.imread(os.path.join(FILE_PATH, 'input1.jpg'))

# cv2.cvtColor is applied over the 
# image input with applied parameters 
# to convert the image in grayscale  
img = cv2.cvtColor(image1, cv2.COLOR_BGR2GRAY) 
  
# applying different thresholding  
# techniques on the input image 
# all pixels value above 120 will  
# be set to 255 
ret, thresh1 = cv2.threshold(img, 120, 255, cv2.THRESH_BINARY) 
ret, thresh2 = cv2.threshold(img, 120, 255, cv2.THRESH_BINARY_INV) 
ret, thresh3 = cv2.threshold(img, 120, 255, cv2.THRESH_TRUNC) 
ret, thresh4 = cv2.threshold(img, 120, 255, cv2.THRESH_TOZERO) 
ret, thresh5 = cv2.threshold(img, 120, 255, cv2.THRESH_TOZERO_INV) 
  
# the window showing output images 
# with the corresponding thresholding  
# techniques applied to the input images 
cv2.imshow('Binary Threshold', thresh1) 
cv2.imshow('Binary Threshold Inverted', thresh2) 
cv2.imshow('Truncated Threshold', thresh3) 
cv2.imshow('Set to 0', thresh4) 
cv2.imshow('Set to 0 Inverted', thresh5) 
    
# De-allocate any associated memory usage   
if cv2.waitKey(0) & 0xff == 27:  
    cv2.destroyAllWindows()