Cartoonify The Image

1. Libraries to Import

   Import the Numpy and Open cv2 libraries

   pip commands to install numpy and opencv

   1. pip install numpy
   2. pip install opencv-python
   

   import cv2
   import numpy as np
   

2. Read the Image

   img = cv2.imread("image//nature.jpg")
   cv2.imshow("input-1",img)
   

   If you want to resize the image window, add the below code

   pic = cv2.resize(img, (width,height)) 
   

   

3. Convert the image to gray

   gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
   cv2.imshow("gray-2", gray)
   

   

4. Blur the gray converted image

   Syntax:

   cv2.medianBlur(input_image, kernel_size)
   

   Code:

   gray = cv2.medianBlur(gray,3)
   cv2.imshow("blur-3", gray)
   

   

5. Perform Adaptive Threshold

   AdaptiveThreshold function performs the adaptive threshold to find dark edges

   syntax:

   adaptiveThreshold(src, dst, maxValue, adaptiveMethod, thresholdType, blockSize, C)
   

   Code:

   edges = cv2.adaptiveThreshold(gray,255,cv2.ADAPTIVE_THRESH_MEAN_C,cv2.THRESH_BINARY,3,5)
   

   

   Depending on the Image, change the numbers in the code in order to get best output

6. Apply Bilateral Filter

   A bilateral filter is a non-linear, edge-preserving, and noise-reducing smoothing filter for images.

   Syntax:

   cv2.bilateralFilter ( src, dst, d, sigmaColor,sigmaSpace, borderType = BORDER_DEFAULT )
   

   To know more about bilateral Filter: Link

   Code:

   color = cv2.bilateralFilter(img,2,250,250)
   cv2.imshow("bilateral-5",color)
   

   

   Depending on the Image, change the numbers in the code in order to get best output

7. Final Output

   Performing bitwise_and on blurred image and masking the edged image.

   Syntax:

   bitwise_and(source1_array, source2_array,destination_array, mask)
   

   Code:

   cartoon = cv2.bitwise_and(color,color,mask=edges)
   cv2.imshow("output-6",cartoon)