您可以在不加载整个图像的情况下遍历图像中的像素吗? [英] Can you loop through pixels in an image without loading the whole image?

问题描述

我有一些非常大的图像.我不想将整个图像加载到内存中，我只想按行顺序对图像进行一次遍历.是否可以在 Python/scipy 中做到这一点?

I have some very large images. I don't want to load the whole image into memory, I just want to make a single pass through the image in row order. Is it possible to do this in Python/scipy?

我使用的是 .PNG，但我可以将它们转换为 PPM、BMP 或其他无损格式.

I'm using .PNG, but I could convert them to PPM, BMP or something else lossless.

推荐答案

GDAL (带有Python绑定)提供一些非常好的驱动程序.虽然它是一个地理空间包，但它可以很好地与 BMP 和 PNG 一起使用.此示例显示如何逐行加载 PNG:

GDAL (with Python bindings) offers some very good drivers for this. Although its a geospatial package, it works fine with BMP and PNG for example. This example show how to load a PNG row by row:

import gdal

# only loads the dataset
ds = gdal.Open('D:\\my_large_image.png')

# read 1 row at the time
for row in range(ds.RasterYSize):
    row_data = ds.ReadAsArray(0,row,ds.RasterXSize,1)

ds = None # this closes the file

因此，它为您提供了一个Numpy数组，因此可以进行处理.您可以用类似的方式编写任何结果.

It gives you a Numpy array as a result, so ready for procesing. You could write any result in a similar fashion.

print type(row_data)
<type 'numpy.ndarray'>

print row_data.shape
(3, 1, 763)

print row_data
[[[  0   0 255 ..., 230 230   0]]

 [[  0   0 252 ..., 232 233   0]]

 [[  0   0 252 ..., 232 233   0]]]

如果 PIL 或其他东西可以做到的话，安装一个专门用于阅读的包可能有点矫枉过正.但是它是一个可靠的选择，我已经像这样处理了30000 * 30000像素的图像.

Installing a package specific for reading might be a bit overkill if PIL or something else can do it. But its a robust option, i have processed images of 30000*30000 pixels like this.

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