Let's say I have a numpy image of some width x and height y. I have to crop the center portion of the image to width cropx and height cropy. Let's assume that cropx and cropy are positive non zero integers and less than the respective image size. What's the best way to apply the slicing for the output image?
可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效,请关闭广告屏蔽插件后再试):
问题:
回答1:
Something along these lines -
def crop_center(img,cropx,cropy):
y,x = img.shape
startx = x//2-(cropx//2)
starty = y//2-(cropy//2)
return img[starty:starty+cropy,startx:startx+cropx]
Sample run -
In [45]: img
Out[45]:
array([[88, 93, 42, 25, 36, 14, 59, 46, 77, 13, 52, 58],
[43, 47, 40, 48, 23, 74, 12, 33, 58, 93, 87, 87],
[54, 75, 79, 21, 15, 44, 51, 68, 28, 94, 78, 48],
[57, 46, 14, 98, 43, 76, 86, 56, 86, 88, 96, 49],
[52, 83, 13, 18, 40, 33, 11, 87, 38, 74, 23, 88],
[81, 28, 86, 89, 16, 28, 66, 67, 80, 23, 95, 98],
[46, 30, 18, 31, 73, 15, 90, 77, 71, 57, 61, 78],
[33, 58, 20, 11, 80, 25, 96, 80, 27, 40, 66, 92],
[13, 59, 77, 53, 91, 16, 47, 79, 33, 78, 25, 66],
[22, 80, 40, 24, 17, 85, 20, 70, 81, 68, 50, 80]])
In [46]: crop_center(img,4,6)
Out[46]:
array([[15, 44, 51, 68],
[43, 76, 86, 56],
[40, 33, 11, 87],
[16, 28, 66, 67],
[73, 15, 90, 77],
[80, 25, 96, 80]])
回答2:
A more general solution based on @Divakar 's answer:
def cropND(img, bounding):
start = tuple(map(lambda a, da: a//2-da//2, img.shape, bounding))
end = tuple(map(operator.add, start, bounding))
slices = tuple(map(slice, start, end))
return img[slices]
and if we have an array a
>>> a = np.arange(100).reshape((10,10))
array([[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
[10, 11, 12, 13, 14, 15, 16, 17, 18, 19],
[20, 21, 22, 23, 24, 25, 26, 27, 28, 29],
[30, 31, 32, 33, 34, 35, 36, 37, 38, 39],
[40, 41, 42, 43, 44, 45, 46, 47, 48, 49],
[50, 51, 52, 53, 54, 55, 56, 57, 58, 59],
[60, 61, 62, 63, 64, 65, 66, 67, 68, 69],
[70, 71, 72, 73, 74, 75, 76, 77, 78, 79],
[80, 81, 82, 83, 84, 85, 86, 87, 88, 89],
[90, 91, 92, 93, 94, 95, 96, 97, 98, 99]])
We can clip it with cropND(a, (5,5))
, you will get:
>>> cropND(a, (5,5))
array([[33, 34, 35, 36, 37],
[43, 44, 45, 46, 47],
[53, 54, 55, 56, 57],
[63, 64, 65, 66, 67],
[73, 74, 75, 76, 77]])
It not only works with 2D image but also 3D image.
Have a nice day.
回答3:
Thanks, Divakar.
Your answer got me going the right direction. I came up with this using negative slice offsets to count 'from the end':
def cropimread(crop, xcrop, ycrop, fn):
"Function to crop center of an image file"
img_pre= msc.imread(fn)
if crop:
ysize, xsize, chan = img_pre.shape
xoff = (xsize - xcrop) // 2
yoff = (ysize - ycrop) // 2
img= img_pre[yoff:-yoff,xoff:-xoff]
else:
img= img_pre
return img