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)