魔杖 mean_shift()函数– Python

mean_shift()函数是Python Wand ImageMagick 库中的一个内置函数，用于通过比较颜色距离内的相邻像素并替换为平均值来重新计算像素值。

Syntax:

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.

编程需要懂一点英语

原图：

示例 1：

Python3

mean_shift(width, height, color_distance)

Python3

# Import library from Image
from wand.image import Image
 
# Import the image
with Image(filename ='../geeksforgeeks.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')

输出：

示例 2：

Python3

# Import libraries from the wand 
from wand.image import Image
from wand.drawing import Drawing
from wand.color import Color
 
with 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')

输出：