替换阈值以上的所有rgb值 [英] Replace all rgb values above a threshold

问题描述

我有一个充满RGB值的numpy 3 d数组，例如 形状=(高度，宽度，3)

I have a numpy 3 d array full of RGB values like for exemple shape = (height,width,3)

  matrix = np.array( [[[0,0.5,0.6],[0.9,1.2,0]])

如果任何值都超过阈值，我必须替换RGB值，例如，阈值= 0.8，则替换= [2,2,2]，然后

I have to replace the RGB value if any of the values is above a threshold, for exemple threshold = 0.8, replacement = [2,2,2] then

matrix = [[[0,0.5,0.6],[2,2,2]]

我该如何使用numpy以高效的方式做到这一点? 目前，我正在使用double for循环，并检查是否有任何rgb值高于阈值，我将其替换，但是对于n = 4000数组，这是非常缓慢的.

How can I do this on a efficient mannner with numpy ? Currently I am using a double for loop and checking if any rgb value is above treshold, i replace it however this is quiet slow for n = 4000 array.

我如何使用numpy来提高效率，也许使用np.where来做到这一点?

How would I do this more efficient with numpy, maybe something with np.where ?

推荐答案

我将矩阵扩展了另一个width维.

I've expanded your matrix by another width dimension.

matrix = np.array([[[0,0.5,0.6],[0.9,1.2,0]],[[0,0.5,0.6],[0.9,1.2,0]]])

您可以通过在轴2上使用np.any(从0开始，所以是第三轴)来构建蒙版:

You can build a mask by using np.any on axis 2 (starts with 0, so third axis):

mask = np.any((matrix > 0.8), axis=2)

# mask:
array([[False,  True],
       [False,  True]], dtype=bool)

matrix[mask] = np.array([2,2,2])

您得到的matrix:

array([[[ 0. ,  0.5,  0.6],
        [ 2. ,  2. ,  2. ]],

       [[ 0. ,  0.5,  0.6],
        [ 2. ,  2. ,  2. ]]])

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