Easiest way to find first top left pixel that is not transparent in an image?
-1
What is the easiest way to find the first nontransparent pixel in a png image and output the location of the pixel? I tried using opencv to find the contours, but because the image is transparent it was difficult.
python opencv image-processing
asked Nov 15 '18 at 16:25
Lauren LederLauren Leder
465
add a comment |
-1
What is the easiest way to find the first nontransparent pixel in a png image and output the location of the pixel? I tried using opencv to find the contours, but because the image is transparent it was difficult.
python opencv image-processing
asked Nov 15 '18 at 16:25
Lauren LederLauren Leder
465
2
first non-transparent pixel on the x-axis, on the y-axis or first given the euclidian distance / the manhattan distance?
– quant
Nov 15 '18 at 16:29
1
Shorter @quant: define top left.
– Steven Rumbalski
Nov 15 '18 at 16:34
1
@StevenRumbalski - oh, you are right, I totally forgot to mention the Chebyshev distance and other less often used distance measurements ;)
– quant
Nov 15 '18 at 16:40
add a comment |
-1
-1
-1
What is the easiest way to find the first nontransparent pixel in a png image and output the location of the pixel? I tried using opencv to find the contours, but because the image is transparent it was difficult.
python opencv image-processing
asked Nov 15 '18 at 16:25
Lauren LederLauren Leder
465
What is the easiest way to find the first nontransparent pixel in a png image and output the location of the pixel? I tried using opencv to find the contours, but because the image is transparent it was difficult.
python opencv image-processing
python opencv image-processing
asked Nov 15 '18 at 16:25
Lauren LederLauren Leder
465
asked Nov 15 '18 at 16:25
Lauren LederLauren Leder
465
asked Nov 15 '18 at 16:25
Lauren LederLauren Leder
465
asked Nov 15 '18 at 16:25
Lauren LederLauren Leder
465
asked Nov 15 '18 at 16:25
Lauren LederLauren Leder
465
465
2
first non-transparent pixel on the x-axis, on the y-axis or first given the euclidian distance / the manhattan distance?
– quant
Nov 15 '18 at 16:29
1
Shorter @quant: define top left.
– Steven Rumbalski
Nov 15 '18 at 16:34
1
@StevenRumbalski - oh, you are right, I totally forgot to mention the Chebyshev distance and other less often used distance measurements ;)
– quant
Nov 15 '18 at 16:40
add a comment |
2
first non-transparent pixel on the x-axis, on the y-axis or first given the euclidian distance / the manhattan distance?
– quant
Nov 15 '18 at 16:29
1
Shorter @quant: define top left.
– Steven Rumbalski
Nov 15 '18 at 16:34
1
@StevenRumbalski - oh, you are right, I totally forgot to mention the Chebyshev distance and other less often used distance measurements ;)
– quant
Nov 15 '18 at 16:40
2
2
first non-transparent pixel on the x-axis, on the y-axis or first given the euclidian distance / the manhattan distance?
– quant
Nov 15 '18 at 16:29
first non-transparent pixel on the x-axis, on the y-axis or first given the euclidian distance / the manhattan distance?
– quant
Nov 15 '18 at 16:29
1
1
Shorter @quant: define top left.
– Steven Rumbalski
Nov 15 '18 at 16:34
Shorter @quant: define top left.
– Steven Rumbalski
Nov 15 '18 at 16:34
1
1
@StevenRumbalski - oh, you are right, I totally forgot to mention the Chebyshev distance and other less often used distance measurements ;)
– quant
Nov 15 '18 at 16:40
@StevenRumbalski - oh, you are right, I totally forgot to mention the Chebyshev distance and other less often used distance measurements ;)
– quant
Nov 15 '18 at 16:40
add a comment |
1 Answer
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you can read image using the alpha channel and find zero values in alpha channel
img = cv2.imread('flower.png', cv2.IMREAD_UNCHANGED)
alpha = (img[:,:,3] == 0)
indices = np.nonzero(alpha)
print(indices)
you can use np.array(indices).sort() to sort the indices
answered Nov 15 '18 at 17:05
user8190410user8190410
533139
how would i sort to find the top left pixel? indices is a 2xn array correct? so would you just find the min y val and then it's corresponding x coord (would that be the top left corner)?
– Lauren Leder
Nov 16 '18 at 19:14
indices is tuple of arrays, you can convert it to 2xn array usingindices = np.array(indices)and useindices.sort(axis=0)to sort along row
– user8190410
Nov 17 '18 at 13:14
Note that it will be sorted row wise not distance wise, if you want distance wise then compute the distance of each index point with (0,0) and then sort it
– user8190410
Nov 18 '18 at 16:19
add a comment |
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1 Answer
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1 Answer
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active
oldest
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oldest
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oldest
votes
0
you can read image using the alpha channel and find zero values in alpha channel
img = cv2.imread('flower.png', cv2.IMREAD_UNCHANGED)
alpha = (img[:,:,3] == 0)
indices = np.nonzero(alpha)
print(indices)
you can use np.array(indices).sort() to sort the indices
answered Nov 15 '18 at 17:05
user8190410user8190410
533139
how would i sort to find the top left pixel? indices is a 2xn array correct? so would you just find the min y val and then it's corresponding x coord (would that be the top left corner)?
– Lauren Leder
Nov 16 '18 at 19:14
indices is tuple of arrays, you can convert it to 2xn array usingindices = np.array(indices)and useindices.sort(axis=0)to sort along row
– user8190410
Nov 17 '18 at 13:14
Note that it will be sorted row wise not distance wise, if you want distance wise then compute the distance of each index point with (0,0) and then sort it
– user8190410
Nov 18 '18 at 16:19
add a comment |
0
you can read image using the alpha channel and find zero values in alpha channel
img = cv2.imread('flower.png', cv2.IMREAD_UNCHANGED)
alpha = (img[:,:,3] == 0)
indices = np.nonzero(alpha)
print(indices)
you can use np.array(indices).sort() to sort the indices
answered Nov 15 '18 at 17:05
user8190410user8190410
533139
how would i sort to find the top left pixel? indices is a 2xn array correct? so would you just find the min y val and then it's corresponding x coord (would that be the top left corner)?
– Lauren Leder
Nov 16 '18 at 19:14
indices is tuple of arrays, you can convert it to 2xn array usingindices = np.array(indices)and useindices.sort(axis=0)to sort along row
– user8190410
Nov 17 '18 at 13:14
Note that it will be sorted row wise not distance wise, if you want distance wise then compute the distance of each index point with (0,0) and then sort it
– user8190410
Nov 18 '18 at 16:19
add a comment |
0
0
0
you can read image using the alpha channel and find zero values in alpha channel
img = cv2.imread('flower.png', cv2.IMREAD_UNCHANGED)
alpha = (img[:,:,3] == 0)
indices = np.nonzero(alpha)
print(indices)
you can use np.array(indices).sort() to sort the indices
answered Nov 15 '18 at 17:05
user8190410user8190410
533139
you can read image using the alpha channel and find zero values in alpha channel
img = cv2.imread('flower.png', cv2.IMREAD_UNCHANGED)
alpha = (img[:,:,3] == 0)
indices = np.nonzero(alpha)
print(indices)
you can use np.array(indices).sort() to sort the indices
answered Nov 15 '18 at 17:05
user8190410user8190410
533139
edited Nov 17 '18 at 13:03
answered Nov 15 '18 at 17:05
user8190410user8190410
533139
answered Nov 15 '18 at 17:05
user8190410user8190410
533139
answered Nov 15 '18 at 17:05
user8190410user8190410
533139
533139
how would i sort to find the top left pixel? indices is a 2xn array correct? so would you just find the min y val and then it's corresponding x coord (would that be the top left corner)?
– Lauren Leder
Nov 16 '18 at 19:14
indices is tuple of arrays, you can convert it to 2xn array usingindices = np.array(indices)and useindices.sort(axis=0)to sort along row
– user8190410
Nov 17 '18 at 13:14
Note that it will be sorted row wise not distance wise, if you want distance wise then compute the distance of each index point with (0,0) and then sort it
– user8190410
Nov 18 '18 at 16:19
add a comment |
how would i sort to find the top left pixel? indices is a 2xn array correct? so would you just find the min y val and then it's corresponding x coord (would that be the top left corner)?
– Lauren Leder
Nov 16 '18 at 19:14
indices is tuple of arrays, you can convert it to 2xn array usingindices = np.array(indices)and useindices.sort(axis=0)to sort along row
– user8190410
Nov 17 '18 at 13:14
Note that it will be sorted row wise not distance wise, if you want distance wise then compute the distance of each index point with (0,0) and then sort it
– user8190410
Nov 18 '18 at 16:19
how would i sort to find the top left pixel? indices is a 2xn array correct? so would you just find the min y val and then it's corresponding x coord (would that be the top left corner)?
– Lauren Leder
Nov 16 '18 at 19:14
how would i sort to find the top left pixel? indices is a 2xn array correct? so would you just find the min y val and then it's corresponding x coord (would that be the top left corner)?
– Lauren Leder
Nov 16 '18 at 19:14
indices is tuple of arrays, you can convert it to 2xn array using
indices = np.array(indices) and use indices.sort(axis=0) to sort along row– user8190410
Nov 17 '18 at 13:14
indices is tuple of arrays, you can convert it to 2xn array using
indices = np.array(indices) and use indices.sort(axis=0) to sort along row– user8190410
Nov 17 '18 at 13:14
Note that it will be sorted row wise not distance wise, if you want distance wise then compute the distance of each index point with (0,0) and then sort it
– user8190410
Nov 18 '18 at 16:19
Note that it will be sorted row wise not distance wise, if you want distance wise then compute the distance of each index point with (0,0) and then sort it
– user8190410
Nov 18 '18 at 16:19
add a comment |
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2
first non-transparent pixel on the x-axis, on the y-axis or first given the euclidian distance / the manhattan distance?
– quant
Nov 15 '18 at 16:29
1
Shorter @quant: define top left.
– Steven Rumbalski
Nov 15 '18 at 16:34
1
@StevenRumbalski - oh, you are right, I totally forgot to mention the Chebyshev distance and other less often used distance measurements ;)
– quant
Nov 15 '18 at 16:40