Image to sketch using Python

Image_Processing/src/Image_To_Sketch/README.md

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+# Image to sketch
+
+Program to turn any image into a pencil sketch using OpenCV in Python.
+
+## Setup 
+
+Run the file
+
+`python image_2_sketch.py`
+
+
+## Screenshot
+
+![image](https://github.com/bislara/ScriptsDump/blob/ip/image2sketch/Image_Processing/src/Image_To_Sketch/combined.png)
+
+

Image_Processing/src/Image_To_Sketch/image_2_sketch.py

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+from cv2 import cv2
+import numpy as np
+import sys
+
+image_name = input("Enter the name of the input image: ")
+
+# reading the image
+img = cv2.imread(image_name)
+
+while img is None:
+ image_name = input("Enter the name of the input image or Enter 'exit' to end program : ")
+ # if end the program 
+ if image_name == "exit":
+ sys.exit()
+
+ # reading the image
+ img = cv2.imread(image_name) 
+
+# resize the image to fit it to show in the screen
+img = cv2.resize(img, (0, 0), None, .75, .75)
+
+# converting the image to grayscale
+img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+# inverting the image
+img_invert = cv2.bitwise_not(img_gray)
+# bluring or smoothing the inverted image with the kernel size (25,25)
+img_blur = cv2.blur(img_invert, (25, 25))
+
+# Applying another type of blur for cheaking
+img_blur_2 = cv2.GaussianBlur(img_invert, (23, 23),0)
+
+# The Dodge blend function divides the bottom layer by the inverted top layer. 
+# This lightens the bottom layer depending on the value of the top layer. 
+# We have the blurred image, which highlights the boldest edges.
+def dodgeV2(image, mask):
+ # inverting color with 255 - ...
+ return cv2.divide(image, 255 - mask, scale=256)
+
+
+final_img = dodgeV2(img_gray, img_blur)
+
+final_img_2 = dodgeV2(img_gray, img_blur_2)
+# final_img_2 = cv2.blur(final_img_2, (3, 3),0)
+final_img_2 = cv2.bilateralFilter(final_img_2,9,50,50)
+
+# convert to bgr for showing the input and output in the same window
+# this will convert the output from 2 channel to 3 channel
+final_img = cv2.cvtColor(final_img, cv2.COLOR_GRAY2BGR)
+# concatenate both the input and output 
+numpy_vertical_concat = np.concatenate((img, final_img), axis=1)
+
+# cv2.imshow('image', final_img)
+# cv2.imshow('image_2', final_img_2)
+
+# displaying the sketch image
+cv2.imshow('image', numpy_vertical_concat)
+print("Press 'Esc' button to exit or Press 's' to save the image and exit.")
+
+k = cv2.waitKey(0)
+# if escape is pressed
+if k == 27:
+ cv2.destroyAllWindows()
+# save the output image
+elif k == ord('s'):
+ cv2.imwrite('output.png', final_img)
+ cv2.imwrite('combined.png',numpy_vertical_concat)
+ cv2.destroyAllWindows()