np.where select pixels that red value bigger than green value in an BGR image-CodePudding

It's my first time using np.where to select pixels from a bgr image, i have no idea how to select pixels that r>g from image by using np.where, I tried to do that by using codes like this:

bgr = cv2.imread('im.jpg')
bgr = np.where(bgr[1]>bgr[2],np.full_like(bgr,[255,255,255]),bgr)
cv2.imshow('result',bgr)
cv2.waitKey(0)

but it seems didn't work. Can anybody help me?

CodePudding user response：

I think that it doesn't work because RGB is the last dimension of your image. Rewrite the slicing in np.where. Something like that:

bgr = cv2.imread('im.jpg')
print(bgr.shape)  # (h, w, 3)
bgr = np.where(bgr[..., 1:2] > bgr[..., 2:3],  # make sure that tensors are of shape 3
               np.full_like(bgr, 255), bgr)
cv2.imshow('result', bgr)
cv2.waitKey(0)

Note that the ellipsis bgr[..., 1:2] means bgr[:, :, 1:2] here.

CodePudding user response：

You seem to want to make all pixels white where red exceeds green and retain the original colours elsewhere. If so, I find it clearer this way:

# Load image
im = cv2.imread('image.png')

# Make simple synonyms for red and green
R = im[...,2]
G = im[...,1]

# Make True/False Boolean of pixels where red exceeds green
MoreRedThanGreen = R > G

# Make the image white wherever it is more red than green
im[MoreRedThanGreen,:] = [255,255,255]

# Save result
cv2.imwrite('result.png', im)

That makes this start image:

into this:

Note: Read the colon (:) in this line as meaning "all the channels":

im[MoreRedThanGreen,:] = [255,255,255]