The mean_shift() function is an inbuilt function in the Python Wand ImageMagick library which is used to recalculate pixel value by comparing neighboring pixels within a color distance and replacing with a mean value.
Syntax:
mean_shift(width, height, color_distance)Parameters: This function accepts two parameters as mentioned above and defined below:
- width: This parameter is used to store the width of neighborhood window in pixels.
- height: This parameter is used to store the height of neighborhood window in pixels.
- color_distance: This parameter is used to store pixel values within this color distance.
Return Value: This function returns the Wand ImageMagick object.
Original Image:
Example 1:
Python3
# Import library from Image from wand.image import Image# Import the imagewith Image(filename ='../neveropen.png') as image: # Clone the image in order to process with image.clone() as mean_shift: # Invoke mean_shift function with width as 30 and height as 10 # and color_distance as 0.2 mean_shift.mean_shift(30, 10, 0.2) # Save the image mean_shift.save(filename ='mean_shift1.jpg') |
Output:
Example 2:
Python3
# Import libraries from the wand from wand.image import Imagefrom wand.drawing import Drawingfrom wand.color import Colorwith Drawing() as draw: # Set Stroke color the circle to black draw.stroke_color = Color('black') # Set Width of the circle to 2 draw.stroke_width = 1 # Set the fill color to 'White (# FFFFFF)' draw.fill_color = Color('white') # Invoke Circle function with center at 50, 50 and radius 25 draw.circle((200, 200), # Center point (100, 100)) # Perimeter point # Set the font style draw.font = '../Helvetica.ttf' # Set the font size draw.font_size = 30 with Image(width = 400, height = 400, background = Color('# 45ff33')) as pic: # Set the text and its location draw.text(int(pic.width / 3), int(pic.height / 2), 'GeeksForGeeks !') # Draw the picture draw(pic) # Invoke mean_shift function with width as 20, height as 30 and color_distance as 0.6 pic.mean_shift(20, 30, 0.6) # Save the image pic.save(filename ='mean_shift2.jpg') |
Output:
