How to select all non-black pixels in a NumPy array?

Question

I am trying to get a list of an image\'s pixels that are different from a specific color using NumPy.

For example, while processig the following image:

Answer 1

Necessity: Need matrix with this shape = (any,any,3)

Solution:

COLOR = (255,0,0)
indices = np.where(np.all(mask == COLOR, axis=-1))
indexes = zip(indices[0], indices[1])
for i in indexes:
    print(i)

Solution 2:

get interval of specific color, for example RED:

COLOR1 = [250,0,0]
COLOR2 = [260,0,0] # doesnt matter its over limit

indices1 = np.where(np.all(mask >= COLOR1, axis=-1))
indexes1 = zip(indices[0], indices[1])

indices2 = np.where(np.all(mask <= COLOR2, axis=-1))
indexes2 = zip(indices[0], indices[1])

# You now want indexes that are in both indexes1 and indexes2

Solution 3 - PROVED to be WORKING

If previous doesnt work, then there is one solution that works 100%

Transform from RGB channel to HSV. Make 2D mask from 3D image. 2D mask will contain Hue value. Comparing Hues is easier than RGB as Hue is 1 value while RGB is vector with 3 values. After you have 2D matrix with Hue values, do like above:

HUE1 = 0.5
HUE2 = 0.7 

indices1 = np.where(HUEmask >= HUE1)
indexes1 = zip(indices[0], indices[1])

indices2 = np.where(HUEmask <= HUE2)
indexes2 = zip(indices[0], indices[1])

You can dothe same for Saturation and Value.