如何切断PNG图像的空白边框区域并使用Python将其缩小到最小尺寸?
答案 0 :(得分:16)
im.getbbox()=> 4元组或无
计算的边界框 图像中的非零区域。该 边界框作为4元组返回 定义左,上,右和 较低的像素坐标。如果是图像 完全是空的,这个方法 返回无。
我试过的代码示例,我已经使用bmp进行了测试,但它也应该适用于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")
答案 1 :(得分:3)
https://gist.github.com/3141140
import Image
import sys
import glob
# Trim all png images with alpha in a folder
# Usage "python PNGAlphaTrim.py ../someFolder"
try:
folderName = sys.argv[1]
except :
print "Usage: python PNGPNGAlphaTrim.py ../someFolder"
sys.exit(1)
filePaths = glob.glob(folderName + "/*.png") #search for all png images in the folder
for filePath in filePaths:
image=Image.open(filePath)
image.load()
imageSize = image.size
imageBox = image.getbbox()
imageComponents = image.split()
if len(imageComponents) < 4: continue #don't process images without alpha
rgbImage = Image.new("RGB", imageSize, (0,0,0))
rgbImage.paste(image, mask=imageComponents[3])
croppedBox = rgbImage.getbbox()
if imageBox != croppedBox:
cropped=image.crop(croppedBox)
print filePath, "Size:", imageSize, "New Size:",croppedBox
cropped.save(filePath)
答案 2 :(得分:3)
我今天遇到了同样的问题。这是我解决透明边框的方法。只需将此脚本与批量.png文件一起放在您的文件夹中:
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)
答案 3 :(得分:1)
答案 4 :(得分:0)
我认为有必要补充@Frank Krueger的回答。他提出了一个很好的观点,但它没有包括如何从图像中正确地裁剪出额外的边框颜色。我发现here。具体来说,我觉得这很有用:
from PIL import Image, ImageChops
def trim(im):
bg = Image.new(im.mode, im.size, im.getpixel((0,0)))
diff = ImageChops.difference(im, bg)
diff = ImageChops.add(diff, diff, 2.0, -100)
bbox = diff.getbbox()
if bbox:
return im.crop(bbox)
im = Image.open("bord3.jpg")
im = trim(im)
im.show()
答案 5 :(得分:0)
以下是现成的解决方案:
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')
示例输入({download link,如果您想尝试):
输出: