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    <p>Here's a function <code>find_groups</code> that groups each pixel in the image into one of three categories: free, closed and border, along with a function <code>print_groups</code> to test it in a readable way.</p> <pre><code>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 &lt; n[0] &lt; height and -1 &lt; n[1] &lt; 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 &lt; y &lt; height-1 and 0 &lt; x &lt; 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])) </code></pre> <p>Now to use it:</p> <pre><code>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)) </code></pre> <p>Outputs:</p> <pre><code># . # # . . . # X X # . . # X X # . . # X X # . . # X # . . . # # . . . . . . . . . closed: [(1, 2), (1, 3), (2, 2), (2, 3), (3, 2), (3, 3), (4, 2)] </code></pre> <p>You'll notice random dots and streaks are classified as borders. But you can always distinguish between real borders and streaks as follows.</p> <pre><code># pseudo code realborders = [i for i in pixelgroups.border if i has an adjacent closed pixel] streaks = [otherwise] </code></pre>
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    1. POFind closed shapes in image
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    1. COThere misses some code in your example, what's after "not n in visited and"?
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    2. COAnd I think it doesn't work if a line that's not in a closed shape hits the image border.
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    3. CO@user2746752 Good point. I got everything working and updated the post. To get around the line hitting the border problem the function now pads the image with white pixels so it will just go around anything in its way.
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