In Python, the shape of an image with a single channel is a problem
I took a 256x256 RGB image and switched it to YCbCr,
I created code to import only the Y channel
Here is my code:
from PIL import Image
import numpy as np
im = Image.open ('test.bmp')
img = im.convert ('YCbCr')
arr_img = np.asarray (img)
arr_img = arr_img [:,:, 0]
img = Image.fromarray (arr_img)
img.show ()
After doing this, I created an image with the Y channel I wanted.
I was happy
But the problem is from here.
I ran this code
print (np.shape (arr_img))
Here, what I want is (256, 256, 1).
However, the above code output (256, 256).
So I changed "arr_img = arr_img [:,:, 0]" to "arr_img = arr_img [:, :, :1]".
However, it did not run because of an error.
I made the RGB image into an image with three channels of YCbCr,
I thought it would be the size (256, 256, 1) when I imported only the first channel, "Y"
How can I get the shape of (256, 256, 1)?
python image python-imaging-library
asked Nov 13 '18 at 9:56
ddjfjfj djfiejdnddjfjfj djfiejdn
444
add a comment |
I took a 256x256 RGB image and switched it to YCbCr,
I created code to import only the Y channel
Here is my code:
from PIL import Image
import numpy as np
im = Image.open ('test.bmp')
img = im.convert ('YCbCr')
arr_img = np.asarray (img)
arr_img = arr_img [:,:, 0]
img = Image.fromarray (arr_img)
img.show ()
After doing this, I created an image with the Y channel I wanted.
I was happy
But the problem is from here.
I ran this code
print (np.shape (arr_img))
Here, what I want is (256, 256, 1).
However, the above code output (256, 256).
So I changed "arr_img = arr_img [:,:, 0]" to "arr_img = arr_img [:, :, :1]".
However, it did not run because of an error.
I made the RGB image into an image with three channels of YCbCr,
I thought it would be the size (256, 256, 1) when I imported only the first channel, "Y"
How can I get the shape of (256, 256, 1)?
python image python-imaging-library
asked Nov 13 '18 at 9:56
ddjfjfj djfiejdnddjfjfj djfiejdn
444
add a comment |
I took a 256x256 RGB image and switched it to YCbCr,
I created code to import only the Y channel
Here is my code:
from PIL import Image
import numpy as np
im = Image.open ('test.bmp')
img = im.convert ('YCbCr')
arr_img = np.asarray (img)
arr_img = arr_img [:,:, 0]
img = Image.fromarray (arr_img)
img.show ()
After doing this, I created an image with the Y channel I wanted.
I was happy
But the problem is from here.
I ran this code
print (np.shape (arr_img))
Here, what I want is (256, 256, 1).
However, the above code output (256, 256).
So I changed "arr_img = arr_img [:,:, 0]" to "arr_img = arr_img [:, :, :1]".
However, it did not run because of an error.
I made the RGB image into an image with three channels of YCbCr,
I thought it would be the size (256, 256, 1) when I imported only the first channel, "Y"
How can I get the shape of (256, 256, 1)?
python image python-imaging-library
asked Nov 13 '18 at 9:56
ddjfjfj djfiejdnddjfjfj djfiejdn
444
I took a 256x256 RGB image and switched it to YCbCr,
I created code to import only the Y channel
Here is my code:
from PIL import Image
import numpy as np
im = Image.open ('test.bmp')
img = im.convert ('YCbCr')
arr_img = np.asarray (img)
arr_img = arr_img [:,:, 0]
img = Image.fromarray (arr_img)
img.show ()
After doing this, I created an image with the Y channel I wanted.
I was happy
But the problem is from here.
I ran this code
print (np.shape (arr_img))
Here, what I want is (256, 256, 1).
However, the above code output (256, 256).
So I changed "arr_img = arr_img [:,:, 0]" to "arr_img = arr_img [:, :, :1]".
However, it did not run because of an error.
I made the RGB image into an image with three channels of YCbCr,
I thought it would be the size (256, 256, 1) when I imported only the first channel, "Y"
How can I get the shape of (256, 256, 1)?
python image python-imaging-library
python image python-imaging-library
asked Nov 13 '18 at 9:56
ddjfjfj djfiejdnddjfjfj djfiejdn
444
asked Nov 13 '18 at 9:56
ddjfjfj djfiejdnddjfjfj djfiejdn
444
asked Nov 13 '18 at 9:56
ddjfjfj djfiejdnddjfjfj djfiejdn
444
asked Nov 13 '18 at 9:56
ddjfjfj djfiejdnddjfjfj djfiejdn
444
asked Nov 13 '18 at 9:56
ddjfjfj djfiejdnddjfjfj djfiejdn
444
444
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
A possibility is to add by hand the missing dimension:
arr_img = np.zeros( [256,256] )
arr_img = arr_img.reshape( * arr_img.shape, 1 )
answered Nov 13 '18 at 10:36
N.GN.G
18217
Thank you for the details.
– ddjfjfj djfiejdn
Nov 14 '18 at 9:09
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
A possibility is to add by hand the missing dimension:
arr_img = np.zeros( [256,256] )
arr_img = arr_img.reshape( * arr_img.shape, 1 )
answered Nov 13 '18 at 10:36
N.GN.G
18217
Thank you for the details.
– ddjfjfj djfiejdn
Nov 14 '18 at 9:09
add a comment |
A possibility is to add by hand the missing dimension:
arr_img = np.zeros( [256,256] )
arr_img = arr_img.reshape( * arr_img.shape, 1 )
answered Nov 13 '18 at 10:36
N.GN.G
18217
Thank you for the details.
– ddjfjfj djfiejdn
Nov 14 '18 at 9:09
add a comment |
A possibility is to add by hand the missing dimension:
arr_img = np.zeros( [256,256] )
arr_img = arr_img.reshape( * arr_img.shape, 1 )
answered Nov 13 '18 at 10:36
N.GN.G
18217
A possibility is to add by hand the missing dimension:
arr_img = np.zeros( [256,256] )
arr_img = arr_img.reshape( * arr_img.shape, 1 )
answered Nov 13 '18 at 10:36
N.GN.G
18217
answered Nov 13 '18 at 10:36
N.GN.G
18217
answered Nov 13 '18 at 10:36
N.GN.G
18217
answered Nov 13 '18 at 10:36
N.GN.G
18217
18217
Thank you for the details.
– ddjfjfj djfiejdn
Nov 14 '18 at 9:09
add a comment |
Thank you for the details.
– ddjfjfj djfiejdn
Nov 14 '18 at 9:09
Thank you for the details.
– ddjfjfj djfiejdn
Nov 14 '18 at 9:09
Thank you for the details.
– ddjfjfj djfiejdn
Nov 14 '18 at 9:09
add a comment |
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