当前位置: 动力学知识库 > 问答 > 编程问答 >

python - Find closed shapes in image

问题描述:

I need to find all closed shapes in an image and get coordinates of it. I need this in Python but a explanation on how to do this is also enough. Feel free to answer with Python code if you want though. I already searched a lot on Google and found these two things:

  • WPF: Finding all closed areas in an image (C# or even VB)
  • determine if a point sits inside an arbitrary shape?

The answer in the first link paints all areas instead of giving me coordinates of closed areas. I don't understand the first answer in the second link and some comments say it doesn't work. The second answer in the second link doesn't work for images like this:

I tried to make my own code too, but it took longer than a second to calculate and it has to be much faster (not really, really fast, but at least faster than 1/10 second).

How can I find these areas?

PS: There are some lines in the images that aren't part of a closed shape.

网友答案:

Here's a function find_groups that groups each pixel in the image into one of three categories: free, closed and border, along with a function print_groups to test it in a readable way.

from collections import namedtuple
from copy import deepcopy

def find_groups(inpixels):
    """
    Group the pixels in the image into three categories: free, closed, and
    border.
        free: A white pixel with a path to outside the image.
        closed: A white pixels with no path to outside the image.
        border: A black pixel.

    Params:
        pixels: A collection of columns of rows of pixels. 0 is black 1 is
                white.

    Return:
        PixelGroups with attributes free, closed and border.
        Each is a list of tuples (y, x).
    """

    # Pad the entire image with white pixels.
    width = len(inpixels[0]) + 2
    height = len(inpixels) + 2
    pixels = deepcopy(inpixels)
    for y in pixels:
        y.insert(0, 1)
        y.append(1)
    pixels.insert(0, [1 for x in range(width)])
    pixels.append([1 for x in range(width)])

    # The free pixels are found through a breadth first traversal.
    queue = [(0,0)]
    visited = [(0,0)]
    while queue:
        y, x = queue.pop(0)

        adjacent = ((y+1, x), (y-1, x), (y, x+1), (y, x-1))
        for n in adjacent:
            if (-1 < n[0] < height and -1 < n[1] < width and
                                        not n in visited and 
                                    pixels[n[0]][n[1]] == 1):
                queue.append(n)
                visited.append(n)

    # Remove the padding and make the categories.
    freecoords = [(y-1, x-1) for (y, x) in visited if
                 (0 < y < height-1 and 0 < x < width-1)]
    allcoords = [(y, x) for y in range(height-2) for x in range(width-2)]
    complement = [i for i in allcoords if not i in freecoords]
    bordercoords = [(y, x) for (y, x) in complement if inpixels[y][x] == 0]
    closedcoords = [(y, x) for (y, x) in complement if inpixels[y][x] == 1]

    PixelGroups = namedtuple('PixelGroups', ['free', 'closed', 'border'])
    return PixelGroups(freecoords, closedcoords, bordercoords)

def print_groups(ysize, xsize, pixelgroups):
    ys= []
    for y in range(ysize):
        xs = []
        for x in range(xsize):
            if (y, x) in pixelgroups.free:
                xs.append('.')
            elif (y, x) in pixelgroups.closed:
                xs.append('X')
            elif (y, x) in pixelgroups.border:
                xs.append('#')
        ys.append(xs)
    print('\n'.join([' '.join(k) for k in ys]))

Now to use it:

pixels = [[0, 1, 0, 0, 1, 1],
          [1, 0, 1, 1, 0, 1], 
          [1, 0, 1, 1, 0, 1],
          [1, 0 ,1 ,1 ,0, 1],
          [1, 0, 1 ,0 ,1, 1],
          [1, 0, 0, 1, 1, 1],
          [1, 1, 1, 1, 1, 1]]
pixelgroups = find_groups(pixels)
print_groups(7, 6, pixelgroups)
print("closed: " + str(pixelgroups.closed))

Outputs:

# . # # . .
. # X X # .
. # X X # .
. # X X # .
. # X # . .
. # # . . .
. . . . . .

closed: [(1, 2), (1, 3), (2, 2), (2, 3), (3, 2), (3, 3), (4, 2)]

You'll notice random dots and streaks are classified as borders. But you can always distinguish between real borders and streaks as follows.

# pseudo code
realborders = [i for i in pixelgroups.border if i has an adjacent closed pixel]
streaks = [otherwise]
分享给朋友:
您可能感兴趣的文章:
随机阅读: