Mixing
How to swap blue and green channel in an image using OpenCV
I am facing a little bit of problem in swapping the channels (specifically red and blue) of an image. I am using Opencv 3.0.0 and Python 2.7.12. Following is my code for swapping the channels
import cv2
img = cv2.imread("input/car1.jpg")
#The obvious approach
Cimg = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
#Manual Approach
red = img[:,:,2]
blue = img[:,:,0]
img[:,:,0] = red
img[:,:,2] = blue
cv2.imshow("frame",Cimg)
cv2.imshow("frame2", img)
cv2.waitKey(0)
cv2.destroyAllWindows()
I am unable to figure out why the same image undergoing through the same(probably) operation is giving two different outputs. Can someone throw some light on what's going wrong?
Thanks!
Original Image
Manual Operation
COLOR_BGR2RGB
python opencv
asked Jul 23 '16 at 6:37
Shashwat VermaShashwat Verma
8018
add a comment |
I am facing a little bit of problem in swapping the channels (specifically red and blue) of an image. I am using Opencv 3.0.0 and Python 2.7.12. Following is my code for swapping the channels
import cv2
img = cv2.imread("input/car1.jpg")
#The obvious approach
Cimg = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
#Manual Approach
red = img[:,:,2]
blue = img[:,:,0]
img[:,:,0] = red
img[:,:,2] = blue
cv2.imshow("frame",Cimg)
cv2.imshow("frame2", img)
cv2.waitKey(0)
cv2.destroyAllWindows()
I am unable to figure out why the same image undergoing through the same(probably) operation is giving two different outputs. Can someone throw some light on what's going wrong?
Thanks!
Original Image
Manual Operation
COLOR_BGR2RGB
python opencv
asked Jul 23 '16 at 6:37
Shashwat VermaShashwat Verma
8018
add a comment |
I am facing a little bit of problem in swapping the channels (specifically red and blue) of an image. I am using Opencv 3.0.0 and Python 2.7.12. Following is my code for swapping the channels
import cv2
img = cv2.imread("input/car1.jpg")
#The obvious approach
Cimg = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
#Manual Approach
red = img[:,:,2]
blue = img[:,:,0]
img[:,:,0] = red
img[:,:,2] = blue
cv2.imshow("frame",Cimg)
cv2.imshow("frame2", img)
cv2.waitKey(0)
cv2.destroyAllWindows()
I am unable to figure out why the same image undergoing through the same(probably) operation is giving two different outputs. Can someone throw some light on what's going wrong?
Thanks!
Original Image
Manual Operation
COLOR_BGR2RGB
python opencv
asked Jul 23 '16 at 6:37
Shashwat VermaShashwat Verma
8018
I am facing a little bit of problem in swapping the channels (specifically red and blue) of an image. I am using Opencv 3.0.0 and Python 2.7.12. Following is my code for swapping the channels
import cv2
img = cv2.imread("input/car1.jpg")
#The obvious approach
Cimg = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
#Manual Approach
red = img[:,:,2]
blue = img[:,:,0]
img[:,:,0] = red
img[:,:,2] = blue
cv2.imshow("frame",Cimg)
cv2.imshow("frame2", img)
cv2.waitKey(0)
cv2.destroyAllWindows()
I am unable to figure out why the same image undergoing through the same(probably) operation is giving two different outputs. Can someone throw some light on what's going wrong?
Thanks!
Original Image
Manual Operation
COLOR_BGR2RGB
python opencv
python opencv
asked Jul 23 '16 at 6:37
Shashwat VermaShashwat Verma
8018
asked Jul 23 '16 at 6:37
Shashwat VermaShashwat Verma
8018
asked Jul 23 '16 at 6:37
Shashwat VermaShashwat Verma
8018
asked Jul 23 '16 at 6:37
Shashwat VermaShashwat Verma
8018
asked Jul 23 '16 at 6:37
Shashwat VermaShashwat Verma
8018
8018
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
red and blue are just views of your image. When you do img[:,:,0] = red this changes img but also blue which is just a view (basically just a reference to the sub-array img[:,:,0]) not a copy, so you loose the original blue channel values. Basically what you assume is a temp copy just is not. Add .copy() and it will work.
img = np.arange(27).reshape((3,3,3))
red = img[:,:,2].copy()
blue = img[:,:,0].copy()
img[:,:,0] = red
img[:,:,2] = blue
print("with copy:n", img)
img = np.arange(27).reshape((3,3,3))
red = img[:,:,2]
blue = img[:,:,0]
img[:,:,0] = red
img[:,:,2] = blue
print("without copy:n",img)
results:
with copy:
[[[ 2 1 0]
[ 5 4 3]
[ 8 7 6]]
[[11 10 9]
[14 13 12]
[17 16 15]]
[[20 19 18]
[23 22 21]
[26 25 24]]]
without copy:
[[[ 2 1 2]
[ 5 4 5]
[ 8 7 8]]
[[11 10 11]
[14 13 14]
[17 16 17]]
[[20 19 20]
[23 22 23]
[26 25 26]]]
Note: you actually only need 1 temp copy of 1 channel.
Or you could also simply do img[:,:,::-1] this will create a view again but with swapped channels, img will stay unchanged, unless you reassign it:
img = np.arange(27).reshape((3,3,3))
print(img[:,:,::-1])
print(img)
img = img[:,:,::-1]
print(img)
results:
[[[ 2 1 0]
[ 5 4 3]
[ 8 7 6]]
[[11 10 9]
[14 13 12]
[17 16 15]]
[[20 19 18]
[23 22 21]
[26 25 24]]]
[[[ 0 1 2]
[ 3 4 5]
[ 6 7 8]]
[[ 9 10 11]
[12 13 14]
[15 16 17]]
[[18 19 20]
[21 22 23]
[24 25 26]]]
[[[ 2 1 0]
[ 5 4 3]
[ 8 7 6]]
[[11 10 9]
[14 13 12]
[17 16 15]]
[[20 19 18]
[23 22 21]
[26 25 24]]]
answered Jul 23 '16 at 6:50
JulienJulien
7,70831637
Worked! Thanks :)
– Shashwat Verma
Jul 23 '16 at 18:09
add a comment |
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1 Answer
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red and blue are just views of your image. When you do img[:,:,0] = red this changes img but also blue which is just a view (basically just a reference to the sub-array img[:,:,0]) not a copy, so you loose the original blue channel values. Basically what you assume is a temp copy just is not. Add .copy() and it will work.
img = np.arange(27).reshape((3,3,3))
red = img[:,:,2].copy()
blue = img[:,:,0].copy()
img[:,:,0] = red
img[:,:,2] = blue
print("with copy:n", img)
img = np.arange(27).reshape((3,3,3))
red = img[:,:,2]
blue = img[:,:,0]
img[:,:,0] = red
img[:,:,2] = blue
print("without copy:n",img)
results:
with copy:
[[[ 2 1 0]
[ 5 4 3]
[ 8 7 6]]
[[11 10 9]
[14 13 12]
[17 16 15]]
[[20 19 18]
[23 22 21]
[26 25 24]]]
without copy:
[[[ 2 1 2]
[ 5 4 5]
[ 8 7 8]]
[[11 10 11]
[14 13 14]
[17 16 17]]
[[20 19 20]
[23 22 23]
[26 25 26]]]
Note: you actually only need 1 temp copy of 1 channel.
Or you could also simply do img[:,:,::-1] this will create a view again but with swapped channels, img will stay unchanged, unless you reassign it:
img = np.arange(27).reshape((3,3,3))
print(img[:,:,::-1])
print(img)
img = img[:,:,::-1]
print(img)
results:
[[[ 2 1 0]
[ 5 4 3]
[ 8 7 6]]
[[11 10 9]
[14 13 12]
[17 16 15]]
[[20 19 18]
[23 22 21]
[26 25 24]]]
[[[ 0 1 2]
[ 3 4 5]
[ 6 7 8]]
[[ 9 10 11]
[12 13 14]
[15 16 17]]
[[18 19 20]
[21 22 23]
[24 25 26]]]
[[[ 2 1 0]
[ 5 4 3]
[ 8 7 6]]
[[11 10 9]
[14 13 12]
[17 16 15]]
[[20 19 18]
[23 22 21]
[26 25 24]]]
answered Jul 23 '16 at 6:50
JulienJulien
7,70831637
Worked! Thanks :)
– Shashwat Verma
Jul 23 '16 at 18:09
add a comment |
red and blue are just views of your image. When you do img[:,:,0] = red this changes img but also blue which is just a view (basically just a reference to the sub-array img[:,:,0]) not a copy, so you loose the original blue channel values. Basically what you assume is a temp copy just is not. Add .copy() and it will work.
img = np.arange(27).reshape((3,3,3))
red = img[:,:,2].copy()
blue = img[:,:,0].copy()
img[:,:,0] = red
img[:,:,2] = blue
print("with copy:n", img)
img = np.arange(27).reshape((3,3,3))
red = img[:,:,2]
blue = img[:,:,0]
img[:,:,0] = red
img[:,:,2] = blue
print("without copy:n",img)
results:
with copy:
[[[ 2 1 0]
[ 5 4 3]
[ 8 7 6]]
[[11 10 9]
[14 13 12]
[17 16 15]]
[[20 19 18]
[23 22 21]
[26 25 24]]]
without copy:
[[[ 2 1 2]
[ 5 4 5]
[ 8 7 8]]
[[11 10 11]
[14 13 14]
[17 16 17]]
[[20 19 20]
[23 22 23]
[26 25 26]]]
Note: you actually only need 1 temp copy of 1 channel.
Or you could also simply do img[:,:,::-1] this will create a view again but with swapped channels, img will stay unchanged, unless you reassign it:
img = np.arange(27).reshape((3,3,3))
print(img[:,:,::-1])
print(img)
img = img[:,:,::-1]
print(img)
results:
[[[ 2 1 0]
[ 5 4 3]
[ 8 7 6]]
[[11 10 9]
[14 13 12]
[17 16 15]]
[[20 19 18]
[23 22 21]
[26 25 24]]]
[[[ 0 1 2]
[ 3 4 5]
[ 6 7 8]]
[[ 9 10 11]
[12 13 14]
[15 16 17]]
[[18 19 20]
[21 22 23]
[24 25 26]]]
[[[ 2 1 0]
[ 5 4 3]
[ 8 7 6]]
[[11 10 9]
[14 13 12]
[17 16 15]]
[[20 19 18]
[23 22 21]
[26 25 24]]]
answered Jul 23 '16 at 6:50
JulienJulien
7,70831637
Worked! Thanks :)
– Shashwat Verma
Jul 23 '16 at 18:09
add a comment |
red and blue are just views of your image. When you do img[:,:,0] = red this changes img but also blue which is just a view (basically just a reference to the sub-array img[:,:,0]) not a copy, so you loose the original blue channel values. Basically what you assume is a temp copy just is not. Add .copy() and it will work.
img = np.arange(27).reshape((3,3,3))
red = img[:,:,2].copy()
blue = img[:,:,0].copy()
img[:,:,0] = red
img[:,:,2] = blue
print("with copy:n", img)
img = np.arange(27).reshape((3,3,3))
red = img[:,:,2]
blue = img[:,:,0]
img[:,:,0] = red
img[:,:,2] = blue
print("without copy:n",img)
results:
with copy:
[[[ 2 1 0]
[ 5 4 3]
[ 8 7 6]]
[[11 10 9]
[14 13 12]
[17 16 15]]
[[20 19 18]
[23 22 21]
[26 25 24]]]
without copy:
[[[ 2 1 2]
[ 5 4 5]
[ 8 7 8]]
[[11 10 11]
[14 13 14]
[17 16 17]]
[[20 19 20]
[23 22 23]
[26 25 26]]]
Note: you actually only need 1 temp copy of 1 channel.
Or you could also simply do img[:,:,::-1] this will create a view again but with swapped channels, img will stay unchanged, unless you reassign it:
img = np.arange(27).reshape((3,3,3))
print(img[:,:,::-1])
print(img)
img = img[:,:,::-1]
print(img)
results:
[[[ 2 1 0]
[ 5 4 3]
[ 8 7 6]]
[[11 10 9]
[14 13 12]
[17 16 15]]
[[20 19 18]
[23 22 21]
[26 25 24]]]
[[[ 0 1 2]
[ 3 4 5]
[ 6 7 8]]
[[ 9 10 11]
[12 13 14]
[15 16 17]]
[[18 19 20]
[21 22 23]
[24 25 26]]]
[[[ 2 1 0]
[ 5 4 3]
[ 8 7 6]]
[[11 10 9]
[14 13 12]
[17 16 15]]
[[20 19 18]
[23 22 21]
[26 25 24]]]
answered Jul 23 '16 at 6:50
JulienJulien
7,70831637
red and blue are just views of your image. When you do img[:,:,0] = red this changes img but also blue which is just a view (basically just a reference to the sub-array img[:,:,0]) not a copy, so you loose the original blue channel values. Basically what you assume is a temp copy just is not. Add .copy() and it will work.
img = np.arange(27).reshape((3,3,3))
red = img[:,:,2].copy()
blue = img[:,:,0].copy()
img[:,:,0] = red
img[:,:,2] = blue
print("with copy:n", img)
img = np.arange(27).reshape((3,3,3))
red = img[:,:,2]
blue = img[:,:,0]
img[:,:,0] = red
img[:,:,2] = blue
print("without copy:n",img)
results:
with copy:
[[[ 2 1 0]
[ 5 4 3]
[ 8 7 6]]
[[11 10 9]
[14 13 12]
[17 16 15]]
[[20 19 18]
[23 22 21]
[26 25 24]]]
without copy:
[[[ 2 1 2]
[ 5 4 5]
[ 8 7 8]]
[[11 10 11]
[14 13 14]
[17 16 17]]
[[20 19 20]
[23 22 23]
[26 25 26]]]
Note: you actually only need 1 temp copy of 1 channel.
Or you could also simply do img[:,:,::-1] this will create a view again but with swapped channels, img will stay unchanged, unless you reassign it:
img = np.arange(27).reshape((3,3,3))
print(img[:,:,::-1])
print(img)
img = img[:,:,::-1]
print(img)
results:
[[[ 2 1 0]
[ 5 4 3]
[ 8 7 6]]
[[11 10 9]
[14 13 12]
[17 16 15]]
[[20 19 18]
[23 22 21]
[26 25 24]]]
[[[ 0 1 2]
[ 3 4 5]
[ 6 7 8]]
[[ 9 10 11]
[12 13 14]
[15 16 17]]
[[18 19 20]
[21 22 23]
[24 25 26]]]
[[[ 2 1 0]
[ 5 4 3]
[ 8 7 6]]
[[11 10 9]
[14 13 12]
[17 16 15]]
[[20 19 18]
[23 22 21]
[26 25 24]]]
answered Jul 23 '16 at 6:50
JulienJulien
7,70831637
edited Jan 1 at 22:58
answered Jul 23 '16 at 6:50
JulienJulien
7,70831637
answered Jul 23 '16 at 6:50
JulienJulien
7,70831637
answered Jul 23 '16 at 6:50
JulienJulien
7,70831637
7,70831637
Worked! Thanks :)
– Shashwat Verma
Jul 23 '16 at 18:09
add a comment |
Worked! Thanks :)
– Shashwat Verma
Jul 23 '16 at 18:09
Worked! Thanks :)
– Shashwat Verma
Jul 23 '16 at 18:09
Worked! Thanks :)
– Shashwat Verma
Jul 23 '16 at 18:09
add a comment |
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