CODEWITHSUNDEEP
pythonnumpy
MaxouMask
MaxouMask

Reputation: 1037

Python, Numpy, replace certain values in an image

I'm looking for an efficient way to replace certain values within a numpy image. So far this is where I got :

def observation(self, img):
    # 45 50 184
    background = np.array([45, 50, 184])
    # 80 0 132
    border = np.array([80, 0, 132])
    img = self.crop(img)
    for line_index, line in enumerate(img):
        for pixel_index, pixel in enumerate(line):
            if not np.array_equal(pixel, background) and not np.array_equal(pixel, border):
                img[line_index][pixel_index] = [254, 254, 254]

The idea is to replace all the colors that are not background or border to white. I'm quite new to this, so I'm fairly sure that there is a more efficient way to do this.

Thanks all.

Upvotes: 1

Views: 2352

Answers (1)

ractiv
ractiv

Reputation: 762

numpy.where should do the job. You have to call it twice (one for the background and one for the border) or combine the 2 conditions img != background and img != border:

np.where(np.logical_and(img!=background, img != border), img, [254, 254, 254])

See this post for a small example (possible duplicate?)

Hope it helps

Upvotes: 2

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