英文:
How to have Image-Saving Function for Images Normalized with [0,1] and [0,255]?
问题
我有一组图像，其中一些在[0,1]范围内进行了归一化，而另一些在[0,255]范围内进行了归一化。我不知道输入图像是以[0,1]形式还是另一种形式进行归一化。这就是为什么我试图编写一个支持两种情况的函数。
换句话说，我想创建一个函数，可以同时支持这两种情况，我可以将图像提供给函数，然后将其保存在相应的范围内。有谁知道如何做到这一点？
英文:
I have a collection of images, with some being normalized within the range of [0,1], and others within the range of [0,255]. I don't know about when input images is normalized in [0,1] form and when the other form. That's why I'm trying to write a function that support both.
In other words, I would like to create a function that can support both cases, where I can provide an image to the function and have it saved accordingly. Does anyone know how to do so?
答案1
得分: 1
我不确定这是否回答了你的问题，但这是我考虑要做的事情。你可以检查图像的范围并将它们转换为标准形式。这是我的意思：
min_val = np.min(image)
max_val = np.max(image)
if min_val >= 0 and max_val <= 1:
# 图像已标准化在[0, 1]范围内
image = (image * 255).astype(np.uint8)
elif min_val >= 0 and max_val <= 255:
# 图像已在[0, 255]范围内
image = image.astype(np.uint8)
else:
# 错误
希望对你有所帮助。
英文:
I am not sure if this answers your question but it is what I thought of doing. You can check the range of image and convert them to a standard form. This is what I mean:
min_val = np.min(image)
max_val = np.max(image)
if min_val >= 0 and max_val <= 1:
# Image normalized in [0, 1] range
image = (image * 255).astype(np.uint8)
elif min_val >= 0 and max_val <= 255:
# Image already in [0, 255] range
image = image.astype(np.uint8)
else:
# Error
Hope this helps.
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