[英]Cutting one image into multiple images using the Python Image Library
我需要使用PIL将此图像分为三部分,然后选择中间部分。 我该怎么做?
http://thedilbertstore.com/images/periodic_content/dilbert/dt110507dhct.jpg
假设您的图片非常长。
现在,您想将其切成较小的垂直位,因为它很长。
这是一个将执行此操作的Python脚本。 这对我为LaTeX文档准备非常长的图像很有用。
from __future__ import division
import Image
import math
import os
def long_slice(image_path, out_name, outdir, slice_size):
"""slice an image into parts slice_size tall"""
img = Image.open(image_path)
width, height = img.size
upper = 0
left = 0
slices = int(math.ceil(height/slice_size))
count = 1
for slice in range(slices):
#if we are at the end, set the lower bound to be the bottom of the image
if count == slices:
lower = height
else:
lower = int(count * slice_size)
#set the bounding box! The important bit
bbox = (left, upper, width, lower)
working_slice = img.crop(bbox)
upper += slice_size
#save the slice
working_slice.save(os.path.join(outdir, "slice_" + out_name + "_" + str(count)+".png"))
count +=1
if __name__ == '__main__':
#slice_size is the max height of the slices in pixels
long_slice("longcat.jpg","longcat", os.getcwd(), 300)
这是输出
我想投票支持古尔诺的解决方案,但缺乏足够的声誉。 但是,我认为我会发布我根据他的回答开发的代码,以防万一它可能对其他人有所帮助。 我还添加了遍历文件结构并选择图像宽度的功能。
import Image
import os
# Set the root directory
rootdir = 'path/to/your/file/directory'
def long_slice(image_path, out_name, outdir, sliceHeight, sliceWidth):
img = Image.open(image_path) # Load image
imageWidth, imageHeight = img.size # Get image dimensions
left = 0 # Set the left-most edge
upper = 0 # Set the top-most edge
while (left < imageWidth):
while (upper < imageHeight):
# If the bottom and right of the cropping box overruns the image.
if (upper + sliceHeight > imageHeight and \
left + sliceWidth > imageWidth):
bbox = (left, upper, imageWidth, imageHeight)
# If the right of the cropping box overruns the image
elif (left + sliceWidth > imageWidth):
bbox = (left, upper, imageWidth, upper + sliceHeight)
# If the bottom of the cropping box overruns the image
elif (upper + sliceHeight > imageHeight):
bbox = (left, upper, left + sliceWidth, imageHeight)
# If the entire cropping box is inside the image,
# proceed normally.
else:
bbox = (left, upper, left + sliceWidth, upper + sliceHeight)
working_slice = img.crop(bbox) # Crop image based on created bounds
# Save your new cropped image.
working_slice.save(os.path.join(outdir, 'slice_' + out_name + \
'_' + str(upper) + '_' + str(left) + '.jpg'))
upper += sliceHeight # Increment the horizontal position
left += sliceWidth # Increment the vertical position
upper = 0
if __name__ == '__main__':
# Iterate through all the files in a set of directories.
for subdir, dirs, files in os.walk(rootdir):
for file in files:
long_slice(subdir + '/' + file, 'longcat', subdir, 128, 128)
对于这个特定的图像,你会做
import Image
i = Image.open('dt110507dhct.jpg')
frame2 = i.crop(((275, 0, 528, 250)))
frame2.save('dt110507dhct_frame2.jpg')
看一下PIL的crop()方法
http://effbot.org/imagingbook/image.htm
(需要了解图像的边界框...假设图像每天都有相同的尺寸,那么您应该能够一次确定边界框并一直使用它)。
如果事先不知道盒子,我将对图像(x和y方向)运行一个简单的边缘查找过滤器,以找到盒子的边界。
一种简单的方法是:
如果您认为框的边界始终是黑色的,则可以先仅提取黑色(或接近黑色)的像素来进行一些预处理。 但是我怀疑是否有必要,因为上述方法应该非常稳定。
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