更改图片中的随机像素,python

2019年8月4日 271次阅读

我想编写一个函数,在这张图片的天空中创建一个随机数(在m和n之间,包括m和n)(
http://tinypic.com/r/34il9hu/6).我希望星星应该由一个白色像素或一个4个相邻白色像素的正方形组成.我也不想在树枝,月亮或鸟上放置一个“星”(1像素)虽然

我怎么能在python中这样做？有人可以帮忙吗？谢谢！

到目前为止我有这个：

到目前为止,我已经开始并且已经出来了,我不知道它是否是正确的,或者即使我在正确的轨道上：

def randomStars(small, large):
   import random
   file = pickAFile()
   pic = makePicture(myPic)
   #x = random.randrange(getWidth(pic))
   #y = random.randrange(getHeight(pic))
   for pixel in pic.getAllPixels():
      if random.random() < 0.25:
         pixel.red = random.randint(256)
         pixel.green = random.randint(256)
         pixel.blue = random.randint(256) 
   show(pic)

我不知道我在做什么:(

最佳答案 这似乎是尝试
superpixels的一个很好的例子,由
skimage实现.你可以更容易地解决你的问题.

import urllib
import random
import io
import matplotlib.pyplot as plt
import skimage.segmentation
import pandas

# Read the image
f = io.BytesIO(urllib.urlopen('http://oi46.tinypic.com/34il9hu.jpg').read())
img = plt.imread(f, format='jpg')

# Prefer to keep pixels together based on location
# But not too much, so we still get some branches.
superpixel = skimage.segmentation.slic(img, n_segments=200, ratio=20)
plt.imshow(superpixel%7, cmap='Set2')

现在我们有超像素,我们可以通过每个超像素来做分类更容易一些.你可以在这里使用一些花哨的分类,但是这个例子很简单,蓝天,让我们手工完成.

# Create a data frame with the relative blueish of every super pixel

# Convert image to hsv 
hsv = matplotlib.colors.rgb_to_hsv(img.astype('float32')/255)
# Define blueish as the percentage of pixels in the blueish range of the hue space
df =pandas.DataFrame({'superpixel':superpixel.ravel(), 
    'blue':((hsv[:,:,0] > 0.4) & (hsv[:,:,0]<0.8)).astype('float32').ravel(), 
    'value':hsv[:,:,2].ravel()})    
grouped = df.groupby('superpixel').mean()    
# Lookup the superpixels with the least blue
blue = grouped.sort('blue', ascending=True).head(100)
# Lookup the darkest pixels
light = grouped.sort('value', ascending=True).head(50)

# If superpixels are too dark or too blue, get rid of them
mask = (np.in1d(superpixel, light.index ).reshape(superpixel.shape) | 
    np.in1d(superpixel, blue.index ).reshape(superpixel.shape))

# Now we can put the stars on the blueish, not too darkish areas
def randomstar(img, mask):
    """random located star"""
    x,y = random.randint(1,img.shape[0]-1), random.randint(1,img.shape[1]-1)
    if not mask[x-1:x+1, y-1:y+1].any():
        # color not so random
        img[x,y,:] = 255
        img[x-1,y,:] = 255
        img[x+1,y,:] = 255
        img[x,y-1,:] = 255
        img[x,y+1,:] = 255

for i in range(100):
    randomstar(img, mask)
plt.imshow(img)
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