估计四面覆盖的区域
Estimating Region covered by all sides
我需要一些帮助来估计某种形态学操作（最好使用 skimage 或 scipy 图像或一般的 python），这可以帮助我隔离所有边包围的区域（见图片。）问题是外部 shell 可以有不同的形状和大小。封闭区域也有不同的形状和大小。
封闭（由白色区域）黑色区域需要隔离的图像示例。
隔离是指获取封闭黑色区域中的所有像素坐标。
示例 1
示例 2
另外一个警告是像这样的图像不应该被填满。
使用scipy.ndimage.binary_fill_holes
from scipy import ndimage as ndi
filled = ndi.binary_fill_holes(image)
holes = filled - image # or np.logical_xor(filled, image)
我更喜欢@Juan 的解决方案，但为了好玩，这里有一个稍微不同的方法。从左上角开始用白色填充，剩下的就是完全封闭的像素。
#!/usr/bin/env python3
import numpy as np
from skimage.segmentation import flood_fill
import cv2
im = cv2.imread('scan.png', cv2.IMREAD_GRAYSCALE)
# Fill with white from top-left
filled = flood_fill(im, (0, 0), 255)
# Save result
cv2.imwrite('DEBUG-result.png', filled)
# Get list of black pixels
blk = np.where(filled==0)
print(f'Number of fully enclosed black pixels: {len(blk[0])}')
print(blk)
为了让大家看到图片的范围，我人为加了红色边框：
这是输出：
Number of fully enclosed black pixels: 957
(array([364, 364, 364, 364, 364, 364, 364, 364, 364, 364, 364, 364, 364,
364, 364, 364, 364, 364, 364, 364, 364, 364, 364, 364, 364, 364,
364, 364, 364, 364, 364, 364, 364, 365, 365, 365, 365, 365, 365,
365, 365, 365, 365, 365, 365, 365, 365, 365, 365, 365, 365, 365,
365, 365, 365, 365, 365, 365, 365, 365, 365, 365, 365, 365, 365,
365, 366, 366, 366, 366, 366, 366, 366, 366, 366, 366, 366, 366,
366, 366, 366, 366, 366, 366, 366, 366, 366, 366, 366, 366, 366,
366, 366, 366, 366, 366, 366, 366, 366, 367, 367, 367, 367, 367,
367, 367, 367, 367, 367, 367, 367, 367, 367, 367, 367, 367, 367,
367, 367, 367, 367, 367, 367, 367, 367, 367, 367, 367, 367, 367,
367, 367, 367, 367, 367, 368, 368, 368, 368, 368, 368, 368, 368,
368, 368, 368, 368, 368, 368, 368, 368, 368, 368, 368, 368, 368,
368, 368, 368, 368, 368, 368, 368, 368, 368, 368, 368, 368, 368,
368, 368, 369, 369, 369, 369, 369, 369, 369, 369, 369, 369, 369,
369, 369, 369, 369, 369, 369, 369, 369, 369, 369, 369, 369, 369,
369, 369, 369, 369, 369, 369, 369, 369, 369, 369, 369, 369, 370,
370, 370, 370, 370, 370, 370, 370, 370, 370, 370, 370, 370, 370,
370, 370, 370, 370, 370, 370, 370, 370, 370, 370, 370, 370, 370,
370, 370, 370, 370, 370, 370, 370, 370, 370, 371, 371, 371, 371,
371, 371, 371, 371, 371, 371, 371, 371, 371, 371, 371, 371, 371,
371, 371, 371, 371, 371, 371, 371, 371, 371, 371, 371, 371, 371,
371, 371, 371, 371, 371, 371, 372, 372, 372, 372, 372, 372, 372,
372, 372, 372, 372, 372, 372, 372, 372, 372, 372, 372, 372, 372,
372, 372, 372, 372, 372, 372, 372, 372, 372, 372, 372, 372, 372,
372, 372, 372, 373, 373, 373, 373, 373, 373, 373, 373, 373, 373,
373, 373, 373, 373, 373, 373, 373, 373, 373, 373, 373, 373, 373,
373, 373, 373, 373, 373, 373, 373, 373, 373, 373, 374, 374, 374,
374, 374, 374, 374, 374, 374, 374, 374, 374, 374, 374, 374, 374,
374, 374, 374, 374, 374, 374, 374, 374, 374, 374, 374, 374, 374,
374, 374, 374, 374, 375, 375, 375, 375, 375, 375, 375, 375, 375,
375, 375, 375, 375, 375, 375, 375, 375, 375, 375, 375, 375, 375,
375, 375, 375, 375, 375, 375, 375, 375, 375, 375, 375, 376, 376,
376, 376, 376, 376, 376, 376, 376, 376, 376, 376, 376, 376, 376,
376, 376, 376, 376, 376, 376, 376, 376, 376, 376, 376, 376, 376,
376, 376, 376, 376, 376, 377, 377, 377, 377, 377, 377, 377, 377,
377, 377, 377, 377, 377, 377, 377, 377, 377, 377, 377, 377, 377,
377, 377, 377, 377, 377, 377, 377, 377, 377, 377, 377, 377, 378,
378, 378, 378, 378, 378, 378, 378, 378, 378, 378, 378, 378, 378,
378, 378, 378, 378, 378, 378, 378, 378, 378, 378, 378, 378, 378,
378, 378, 378, 378, 378, 378, 379, 379, 379, 379, 379, 379, 379,
379, 379, 379, 379, 379, 379, 379, 379, 379, 379, 379, 379, 379,
379, 379, 379, 379, 379, 379, 379, 379, 379, 379, 379, 379, 379,
380, 380, 380, 380, 380, 380, 380, 380, 380, 380, 380, 380, 380,
380, 380, 380, 380, 380, 380, 380, 380, 380, 380, 380, 380, 380,
380, 380, 380, 380, 380, 380, 380, 381, 381, 381, 381, 381, 381,
381, 381, 381, 381, 381, 381, 381, 381, 381, 381, 381, 381, 381,
381, 381, 381, 381, 381, 381, 381, 381, 381, 381, 381, 381, 381,
381, 382, 382, 382, 382, 382, 382, 382, 382, 382, 382, 382, 382,
382, 382, 382, 382, 382, 382, 382, 382, 382, 382, 382, 382, 382,
382, 382, 382, 382, 382, 382, 382, 382, 383, 383, 383, 383, 383,
383, 383, 383, 383, 383, 383, 383, 383, 383, 383, 383, 383, 383,
383, 383, 383, 383, 383, 383, 383, 383, 383, 383, 383, 383, 383,
383, 383, 384, 384, 384, 384, 384, 384, 384, 384, 384, 384, 384,
384, 384, 384, 384, 384, 384, 384, 384, 384, 384, 384, 384, 384,
384, 384, 384, 384, 384, 384, 384, 384, 384, 385, 385, 385, 385,
385, 385, 385, 385, 385, 385, 385, 385, 385, 385, 385, 385, 385,
385, 385, 385, 385, 385, 385, 385, 386, 386, 386, 386, 386, 386,
386, 386, 386, 386, 386, 386, 386, 386, 386, 386, 386, 386, 386,
386, 386, 386, 386, 386, 387, 387, 387, 387, 387, 387, 387, 387,
387, 387, 387, 387, 387, 387, 387, 387, 387, 387, 387, 387, 387,
387, 387, 387, 388, 388, 388, 388, 388, 388, 388, 388, 388, 388,
388, 388, 388, 388, 388, 388, 388, 388, 388, 388, 388, 389, 389,
389, 389, 389, 389, 389, 389, 389, 389, 389, 389, 389, 389, 389,
389, 389, 389, 389, 389, 389, 390, 390, 390, 390, 390, 390, 390,
390, 390, 390, 390, 390, 390, 390, 390, 390, 390, 390, 390, 390,
390, 391, 391, 391, 391, 391, 391, 391, 391, 391, 391, 391, 391,
391, 391, 391, 392, 392, 392, 392, 392, 392, 392, 392, 392, 392,
392, 392, 392, 392, 392, 393, 393, 393, 393, 393, 393, 393, 393,
393, 393, 393, 393, 393, 393, 393, 394, 394, 394, 394, 394, 394,
394, 394, 394, 394, 394, 394, 394, 394, 394, 395, 395, 395, 395,
395, 395, 395, 395, 395, 395, 395, 395, 395, 395, 395, 396, 396,
396, 396, 396, 396, 396, 396, 396, 397, 397, 397, 397, 397, 397,
397, 397, 397, 398, 398, 398, 398, 398, 398, 398, 398, 398, 399,
399, 399, 400, 400, 400, 401, 401, 401]), array([244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256,
257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269,
270, 271, 272, 273, 274, 275, 276, 244, 245, 246, 247, 248, 249,
250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262,
263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275,
276, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255,
256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268,
269, 270, 271, 272, 273, 274, 275, 276, 241, 242, 243, 244, 245,
246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258,
259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271,
272, 273, 274, 275, 276, 241, 242, 243, 244, 245, 246, 247, 248,
249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261,
262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274,
275, 276, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251,
252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264,
265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 241,
242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254,
255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267,
268, 269, 270, 271, 272, 273, 274, 275, 276, 241, 242, 243, 244,
245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257,
258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270,
271, 272, 273, 274, 275, 276, 241, 242, 243, 244, 245, 246, 247,
248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260,
261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273,
274, 275, 276, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250,
251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263,
264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 241, 242, 243,
244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256,
257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269,
270, 271, 272, 273, 241, 242, 243, 244, 245, 246, 247, 248, 249,
250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262,
263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 241, 242,
243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255,
256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268,
269, 270, 271, 272, 273, 241, 242, 243, 244, 245, 246, 247, 248,
249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261,
262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 241,
242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254,
255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267,
268, 269, 270, 271, 272, 273, 241, 242, 243, 244, 245, 246, 247,
248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260,
261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273,
241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253,
254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266,
267, 268, 269, 270, 271, 272, 273, 241, 242, 243, 244, 245, 246,
247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259,
260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272,
273, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252,
253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265,
266, 267, 268, 269, 270, 271, 272, 273, 241, 242, 243, 244, 245,
246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258,
259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271,
272, 273, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251,
252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264,
265, 266, 267, 268, 269, 270, 271, 272, 273, 253, 254, 255, 256,
257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269,
270, 271, 272, 273, 274, 275, 276, 253, 254, 255, 256, 257, 258,
259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271,
272, 273, 274, 275, 276, 253, 254, 255, 256, 257, 258, 259, 260,
261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273,
274, 275, 276, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265,
266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 256, 257,
258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270,
271, 272, 273, 274, 275, 276, 256, 257, 258, 259, 260, 261, 262,
263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275,
276, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270,
271, 272, 273, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268,
269, 270, 271, 272, 273, 259, 260, 261, 262, 263, 264, 265, 266,
267, 268, 269, 270, 271, 272, 273, 259, 260, 261, 262, 263, 264,
265, 266, 267, 268, 269, 270, 271, 272, 273, 259, 260, 261, 262,
263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 262, 263,
264, 265, 266, 267, 268, 269, 270, 262, 263, 264, 265, 266, 267,
268, 269, 270, 262, 263, 264, 265, 266, 267, 268, 269, 270, 265,
266, 267, 265, 266, 267, 265, 266, 267]))
希望你能从每个数组的第一个元素看出第一个黑色像素在 364,244
请注意，如果扫描有可能触及图像的边缘，则洪水填充将无法“流动”一直围绕边缘.在这种情况下，您可以简单地在边缘周围一直添加一个 1 像素宽的黑色边框，以便 floodfill 流动...然后将其删除。
我需要一些帮助来估计某种形态学操作（最好使用 skimage 或 scipy 图像或一般的 python），这可以帮助我隔离所有边包围的区域（见图片。）问题是外部 shell 可以有不同的形状和大小。封闭区域也有不同的形状和大小。 封闭（由白色区域）黑色区域需要隔离的图像示例。
隔离是指获取封闭黑色区域中的所有像素坐标。
示例 1
示例 2
另外一个警告是像这样的图像不应该被填满。
使用scipy.ndimage.binary_fill_holes
from scipy import ndimage as ndi
filled = ndi.binary_fill_holes(image)
holes = filled - image # or np.logical_xor(filled, image)
我更喜欢@Juan 的解决方案，但为了好玩，这里有一个稍微不同的方法。从左上角开始用白色填充，剩下的就是完全封闭的像素。
#!/usr/bin/env python3
import numpy as np
from skimage.segmentation import flood_fill
import cv2
im = cv2.imread('scan.png', cv2.IMREAD_GRAYSCALE)
# Fill with white from top-left
filled = flood_fill(im, (0, 0), 255)
# Save result
cv2.imwrite('DEBUG-result.png', filled)
# Get list of black pixels
blk = np.where(filled==0)
print(f'Number of fully enclosed black pixels: {len(blk[0])}')
print(blk)
为了让大家看到图片的范围，我人为加了红色边框：
这是输出：
Number of fully enclosed black pixels: 957
(array([364, 364, 364, 364, 364, 364, 364, 364, 364, 364, 364, 364, 364,
364, 364, 364, 364, 364, 364, 364, 364, 364, 364, 364, 364, 364,
364, 364, 364, 364, 364, 364, 364, 365, 365, 365, 365, 365, 365,
365, 365, 365, 365, 365, 365, 365, 365, 365, 365, 365, 365, 365,
365, 365, 365, 365, 365, 365, 365, 365, 365, 365, 365, 365, 365,
365, 366, 366, 366, 366, 366, 366, 366, 366, 366, 366, 366, 366,
366, 366, 366, 366, 366, 366, 366, 366, 366, 366, 366, 366, 366,
366, 366, 366, 366, 366, 366, 366, 366, 367, 367, 367, 367, 367,
367, 367, 367, 367, 367, 367, 367, 367, 367, 367, 367, 367, 367,
367, 367, 367, 367, 367, 367, 367, 367, 367, 367, 367, 367, 367,
367, 367, 367, 367, 367, 368, 368, 368, 368, 368, 368, 368, 368,
368, 368, 368, 368, 368, 368, 368, 368, 368, 368, 368, 368, 368,
368, 368, 368, 368, 368, 368, 368, 368, 368, 368, 368, 368, 368,
368, 368, 369, 369, 369, 369, 369, 369, 369, 369, 369, 369, 369,
369, 369, 369, 369, 369, 369, 369, 369, 369, 369, 369, 369, 369,
369, 369, 369, 369, 369, 369, 369, 369, 369, 369, 369, 369, 370,
370, 370, 370, 370, 370, 370, 370, 370, 370, 370, 370, 370, 370,
370, 370, 370, 370, 370, 370, 370, 370, 370, 370, 370, 370, 370,
370, 370, 370, 370, 370, 370, 370, 370, 370, 371, 371, 371, 371,
371, 371, 371, 371, 371, 371, 371, 371, 371, 371, 371, 371, 371,
371, 371, 371, 371, 371, 371, 371, 371, 371, 371, 371, 371, 371,
371, 371, 371, 371, 371, 371, 372, 372, 372, 372, 372, 372, 372,
372, 372, 372, 372, 372, 372, 372, 372, 372, 372, 372, 372, 372,
372, 372, 372, 372, 372, 372, 372, 372, 372, 372, 372, 372, 372,
372, 372, 372, 373, 373, 373, 373, 373, 373, 373, 373, 373, 373,
373, 373, 373, 373, 373, 373, 373, 373, 373, 373, 373, 373, 373,
373, 373, 373, 373, 373, 373, 373, 373, 373, 373, 374, 374, 374,
374, 374, 374, 374, 374, 374, 374, 374, 374, 374, 374, 374, 374,
374, 374, 374, 374, 374, 374, 374, 374, 374, 374, 374, 374, 374,
374, 374, 374, 374, 375, 375, 375, 375, 375, 375, 375, 375, 375,
375, 375, 375, 375, 375, 375, 375, 375, 375, 375, 375, 375, 375,
375, 375, 375, 375, 375, 375, 375, 375, 375, 375, 375, 376, 376,
376, 376, 376, 376, 376, 376, 376, 376, 376, 376, 376, 376, 376,
376, 376, 376, 376, 376, 376, 376, 376, 376, 376, 376, 376, 376,
376, 376, 376, 376, 376, 377, 377, 377, 377, 377, 377, 377, 377,
377, 377, 377, 377, 377, 377, 377, 377, 377, 377, 377, 377, 377,
377, 377, 377, 377, 377, 377, 377, 377, 377, 377, 377, 377, 378,
378, 378, 378, 378, 378, 378, 378, 378, 378, 378, 378, 378, 378,
378, 378, 378, 378, 378, 378, 378, 378, 378, 378, 378, 378, 378,
378, 378, 378, 378, 378, 378, 379, 379, 379, 379, 379, 379, 379,
379, 379, 379, 379, 379, 379, 379, 379, 379, 379, 379, 379, 379,
379, 379, 379, 379, 379, 379, 379, 379, 379, 379, 379, 379, 379,
380, 380, 380, 380, 380, 380, 380, 380, 380, 380, 380, 380, 380,
380, 380, 380, 380, 380, 380, 380, 380, 380, 380, 380, 380, 380,
380, 380, 380, 380, 380, 380, 380, 381, 381, 381, 381, 381, 381,
381, 381, 381, 381, 381, 381, 381, 381, 381, 381, 381, 381, 381,
381, 381, 381, 381, 381, 381, 381, 381, 381, 381, 381, 381, 381,
381, 382, 382, 382, 382, 382, 382, 382, 382, 382, 382, 382, 382,
382, 382, 382, 382, 382, 382, 382, 382, 382, 382, 382, 382, 382,
382, 382, 382, 382, 382, 382, 382, 382, 383, 383, 383, 383, 383,
383, 383, 383, 383, 383, 383, 383, 383, 383, 383, 383, 383, 383,
383, 383, 383, 383, 383, 383, 383, 383, 383, 383, 383, 383, 383,
383, 383, 384, 384, 384, 384, 384, 384, 384, 384, 384, 384, 384,
384, 384, 384, 384, 384, 384, 384, 384, 384, 384, 384, 384, 384,
384, 384, 384, 384, 384, 384, 384, 384, 384, 385, 385, 385, 385,
385, 385, 385, 385, 385, 385, 385, 385, 385, 385, 385, 385, 385,
385, 385, 385, 385, 385, 385, 385, 386, 386, 386, 386, 386, 386,
386, 386, 386, 386, 386, 386, 386, 386, 386, 386, 386, 386, 386,
386, 386, 386, 386, 386, 387, 387, 387, 387, 387, 387, 387, 387,
387, 387, 387, 387, 387, 387, 387, 387, 387, 387, 387, 387, 387,
387, 387, 387, 388, 388, 388, 388, 388, 388, 388, 388, 388, 388,
388, 388, 388, 388, 388, 388, 388, 388, 388, 388, 388, 389, 389,
389, 389, 389, 389, 389, 389, 389, 389, 389, 389, 389, 389, 389,
389, 389, 389, 389, 389, 389, 390, 390, 390, 390, 390, 390, 390,
390, 390, 390, 390, 390, 390, 390, 390, 390, 390, 390, 390, 390,
390, 391, 391, 391, 391, 391, 391, 391, 391, 391, 391, 391, 391,
391, 391, 391, 392, 392, 392, 392, 392, 392, 392, 392, 392, 392,
392, 392, 392, 392, 392, 393, 393, 393, 393, 393, 393, 393, 393,
393, 393, 393, 393, 393, 393, 393, 394, 394, 394, 394, 394, 394,
394, 394, 394, 394, 394, 394, 394, 394, 394, 395, 395, 395, 395,
395, 395, 395, 395, 395, 395, 395, 395, 395, 395, 395, 396, 396,
396, 396, 396, 396, 396, 396, 396, 397, 397, 397, 397, 397, 397,
397, 397, 397, 398, 398, 398, 398, 398, 398, 398, 398, 398, 399,
399, 399, 400, 400, 400, 401, 401, 401]), array([244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256,
257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269,
270, 271, 272, 273, 274, 275, 276, 244, 245, 246, 247, 248, 249,
250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262,
263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275,
276, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255,
256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268,
269, 270, 271, 272, 273, 274, 275, 276, 241, 242, 243, 244, 245,
246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258,
259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271,
272, 273, 274, 275, 276, 241, 242, 243, 244, 245, 246, 247, 248,
249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261,
262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274,
275, 276, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251,
252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264,
265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 241,
242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254,
255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267,
268, 269, 270, 271, 272, 273, 274, 275, 276, 241, 242, 243, 244,
245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257,
258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270,
271, 272, 273, 274, 275, 276, 241, 242, 243, 244, 245, 246, 247,
248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260,
261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273,
274, 275, 276, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250,
251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263,
264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 241, 242, 243,
244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256,
257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269,
270, 271, 272, 273, 241, 242, 243, 244, 245, 246, 247, 248, 249,
250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262,
263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 241, 242,
243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255,
256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268,
269, 270, 271, 272, 273, 241, 242, 243, 244, 245, 246, 247, 248,
249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261,
262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 241,
242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254,
255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267,
268, 269, 270, 271, 272, 273, 241, 242, 243, 244, 245, 246, 247,
248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260,
261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273,
241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253,
254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266,
267, 268, 269, 270, 271, 272, 273, 241, 242, 243, 244, 245, 246,
247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259,
260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272,
273, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252,
253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265,
266, 267, 268, 269, 270, 271, 272, 273, 241, 242, 243, 244, 245,
246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258,
259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271,
272, 273, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251,
252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264,
265, 266, 267, 268, 269, 270, 271, 272, 273, 253, 254, 255, 256,
257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269,
270, 271, 272, 273, 274, 275, 276, 253, 254, 255, 256, 257, 258,
259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271,
272, 273, 274, 275, 276, 253, 254, 255, 256, 257, 258, 259, 260,
261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273,
274, 275, 276, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265,
266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 256, 257,
258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270,
271, 272, 273, 274, 275, 276, 256, 257, 258, 259, 260, 261, 262,
263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275,
276, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270,
271, 272, 273, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268,
269, 270, 271, 272, 273, 259, 260, 261, 262, 263, 264, 265, 266,
267, 268, 269, 270, 271, 272, 273, 259, 260, 261, 262, 263, 264,
265, 266, 267, 268, 269, 270, 271, 272, 273, 259, 260, 261, 262,
263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 262, 263,
264, 265, 266, 267, 268, 269, 270, 262, 263, 264, 265, 266, 267,
268, 269, 270, 262, 263, 264, 265, 266, 267, 268, 269, 270, 265,
266, 267, 265, 266, 267, 265, 266, 267]))
希望你能从每个数组的第一个元素看出第一个黑色像素在 364,244
请注意，如果扫描有可能触及图像的边缘，则洪水填充将无法“流动”一直围绕边缘.在这种情况下，您可以简单地在边缘周围一直添加一个 1 像素宽的黑色边框，以便 floodfill 流动...然后将其删除。