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How to remove specific shade of grey from a greyscale image in python PIL

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0

I have a python PIL script that is turning an image into greyscale and then removing a specific shade of grey. I can do this by converting first to rgb and then removing the grey, but I'd like to only be in greyscale.

color = [149, 149, 149]
white = [255, 255, 255]
im2 = Image.open('example-files/step1.jpg')
im = im2.convert('RGB')
data = np.array(im)
rgb = data[:, :, :3]
mask = np.all(rgb == color, axis=-1)
data[mask] = white
new_im = Image.fromarray(data).convert('L')
new_im.save('example-files/step3.png')

This works, except I don't ever want to .convert('RGB'), I always want to remain in greyscale, as I want to make this as fast as possible and I found that that extra convert add about .04 seconds. I tried using the data[mask] method while in greyscale and it doesn't work:

color = [149]
white = [255]
im = Image.open('example-files/step1.jpg').convert('L')
data = np.array(im)
mask = np.all(data == color, axis=-1)
data[mask] = white
new_im = Image.fromarray(data)
new_im.save('example-files/step6.png')

What can I do to either remove that color of grey as fast as possible or get it to remove while remaining in greyscale?

python numpy python-imaging-library

share|improve this question

asked Mar 8 at 4:23

EricEric

1116

add a comment | 

0

I have a python PIL script that is turning an image into greyscale and then removing a specific shade of grey. I can do this by converting first to rgb and then removing the grey, but I'd like to only be in greyscale.

color = [149, 149, 149]
white = [255, 255, 255]
im2 = Image.open('example-files/step1.jpg')
im = im2.convert('RGB')
data = np.array(im)
rgb = data[:, :, :3]
mask = np.all(rgb == color, axis=-1)
data[mask] = white
new_im = Image.fromarray(data).convert('L')
new_im.save('example-files/step3.png')

This works, except I don't ever want to .convert('RGB'), I always want to remain in greyscale, as I want to make this as fast as possible and I found that that extra convert add about .04 seconds. I tried using the data[mask] method while in greyscale and it doesn't work:

color = [149]
white = [255]
im = Image.open('example-files/step1.jpg').convert('L')
data = np.array(im)
mask = np.all(data == color, axis=-1)
data[mask] = white
new_im = Image.fromarray(data)
new_im.save('example-files/step6.png')

What can I do to either remove that color of grey as fast as possible or get it to remove while remaining in greyscale?

python numpy python-imaging-library

share|improve this question

asked Mar 8 at 4:23

EricEric

1116

add a comment | 

I have a python PIL script that is turning an image into greyscale and then removing a specific shade of grey. I can do this by converting first to rgb and then removing the grey, but I'd like to only be in greyscale.

color = [149, 149, 149]
white = [255, 255, 255]
im2 = Image.open('example-files/step1.jpg')
im = im2.convert('RGB')
data = np.array(im)
rgb = data[:, :, :3]
mask = np.all(rgb == color, axis=-1)
data[mask] = white
new_im = Image.fromarray(data).convert('L')
new_im.save('example-files/step3.png')

This works, except I don't ever want to .convert('RGB'), I always want to remain in greyscale, as I want to make this as fast as possible and I found that that extra convert add about .04 seconds. I tried using the data[mask] method while in greyscale and it doesn't work:

color = [149]
white = [255]
im = Image.open('example-files/step1.jpg').convert('L')
data = np.array(im)
mask = np.all(data == color, axis=-1)
data[mask] = white
new_im = Image.fromarray(data)
new_im.save('example-files/step6.png')

What can I do to either remove that color of grey as fast as possible or get it to remove while remaining in greyscale?

python numpy python-imaging-library

share|improve this question

asked Mar 8 at 4:23

EricEric

1116

color = [149, 149, 149]
white = [255, 255, 255]
im2 = Image.open('example-files/step1.jpg')
im = im2.convert('RGB')
data = np.array(im)
rgb = data[:, :, :3]
mask = np.all(rgb == color, axis=-1)
data[mask] = white
new_im = Image.fromarray(data).convert('L')
new_im.save('example-files/step3.png')

color = [149]
white = [255]
im = Image.open('example-files/step1.jpg').convert('L')
data = np.array(im)
mask = np.all(data == color, axis=-1)
data[mask] = white
new_im = Image.fromarray(data)
new_im.save('example-files/step6.png')

share|improve this question

asked Mar 8 at 4:23

EricEric

1116

share|improve this question

asked Mar 8 at 4:23

EricEric

1116

asked Mar 8 at 4:23

EricEric

1116

asked Mar 8 at 4:23

EricEric

1116