将PNG图像裁剪为最小尺寸

Question

如何使用Python切断PNG图像的空白边框区域并将其缩小到最小尺寸？

Answer 1

PIL的getbbox正在为我工​​作

im.getbbox()=> 4元组或无

计算图像中非零区域的边界框.边界框作为定义左,上,右和下像素坐标的4元组返回.如果图像完全为空,则此方法返回None.

我尝试过的代码示例,我已经使用bmp进行了测试,但它也适用于png.

>>> import Image
>>> im=Image.open("test.bmp")
>>> im.size
(364, 471)
>>> im.getbbox()
(64, 89, 278, 267)
>>> im2=im.crop(im.getbbox())
>>> im2.size
(214, 178)
>>> im2.save("test2.bmp")

Answer 2

这是现成的解决方案：

import numpy as np
from PIL import Image

def bbox(im):
    a = np.array(im)[:,:,:3]  # keep RGB only
    m = np.any(a != [255, 255, 255], axis=2)
    coords = np.argwhere(m)
    y0, x0, y1, x1 = *np.min(coords, axis=0), *np.max(coords, axis=0)
    return (x0, y0, x1+1, y1+1)

im = Image.open('test.png')
print(bbox(im))  # (33, 12, 223, 80)
im2 = im.crop(bbox(im))
im2.save('test_cropped.png')

输入示例（如果您想尝试，请下载链接）：

输出：

Answer 3

我今天也遇到了同样的问题。这是我裁剪透明边框的解决方案。只需将此脚本与批处理 .png 文件一起放入您的文件夹中即可：

from PIL import Image
import numpy as np
from os import listdir

def crop(png_image_name):
    pil_image = Image.open(png_image_name)
    np_array = np.array(pil_image)
    blank_px = [255, 255, 255, 0]
    mask = np_array != blank_px
    coords = np.argwhere(mask)
    x0, y0, z0 = coords.min(axis=0)
    x1, y1, z1 = coords.max(axis=0) + 1
    cropped_box = np_array[x0:x1, y0:y1, z0:z1]
    pil_image = Image.fromarray(cropped_box, 'RGBA')
    print(pil_image.width, pil_image.height)
    pil_image.save(png_image_name)
    print(png_image_name)

for f in listdir('.'):
    if f.endswith('.png'):
        crop(f)