问题描述
所以我有一组数据可以转换成R，G，B波段的单独numpy数组。现在我需要将它们组合起来形成RGB图像。
So I have a set of data which I am able to convert to form separate numpy arrays of R, G, B bands. Now I need to combine them to form an RGB image.
我尝试'Image'来完成这项工作，但需要'模式'来归因。
I tried 'Image' to do the job but it requires 'mode' to be attributed.
我试图做一个技巧。我会使用Image.fromarray（）将数组带到图像，但默认情况下，当Image.merge需要L模式图像进行合并时，它会达到'F'模式。如果我在第一个位置将fromarray（）中的数组属性声明为'L'，则所有RGB图像都会失真。
I tried to do a trick. I would use Image.fromarray() to take the array to image but it attains 'F' mode by default when Image.merge requires 'L' mode images to merge. If I would declare the attribute of array in fromarray() to 'L' at first place, all the R G B images become distorted.
但是，如果我保存图像和然后打开然后合并，它工作正常。图像以L模式读取图像。
But, if I save the images and then open them and then merge, it works fine. Image reads the image with 'L' mode.
现在我有两个问题。
首先，我不认为这是一种优雅的工作方式。因此，如果有人知道更好的方法，请告诉
First, I dont think it is an elegant way of doing the work. So if anyone knows the better way of doing it, please tell
其次，Image.SAVE无法正常工作。以下是我面临的错误：
Secondly, Image.SAVE is not working properly. Following are the errors I face:
In [7]: Image.SAVE(imagefile, 'JPEG')
----------------------------------------------------------------------------------
TypeError Traceback (most recent call last)
/media/New Volume/Documents/My own works/ISAC/SAMPLES/<ipython console> in <module>()
TypeError: 'dict' object is not callable
请建议解决方案。
请注意图像大小在4000x4000左右。
And please mind that the image is around 4000x4000 size array.
推荐答案
我真的不明白你的问题，但这里有一个类似我最近做过的事情的例子似乎可能有所帮助：
I don't really understand your question but here is an example of something similar I've done recently that seems like it might help:
# r, g, and b are 512x512 float arrays with values >= 0 and < 1.
from PIL import Image
import numpy as np
rgbArray = np.zeros((512,512,3), 'uint8')
rgbArray[..., 0] = r*256
rgbArray[..., 1] = g*256
rgbArray[..., 2] = b*256
img = Image.fromarray(rgbArray)
img.save('myimg.jpeg')
我希望有帮助
这篇关于在Python中将3个单独的numpy数组合并为RGB图像的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！