Python pixel manipulation returning grey image instead of inverted
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I'm doing some prototype code for a project. I'm using Pillow to open the image and other minor things, but I want to invert the image manually using its pixel values. I used two's complement in hopes of inverting it. However, when I display the final image, it's a solid grey square instead of inverted colors. I just used a picture of a possum, 275 pixels by 183 pixels. Any idea why it displays grey block and not an inverted image?
#importing Image module
from PIL import Image
import numpy
#sets numpy to print out full array
numpy.set_printoptions(threshold=numpy.inf)
def twos_comp(val, bits):
"""compute the 2's complement of int value val"""
if (val & (1 << (bits - 1))) != 0: # if sign bit is set e.g., 8bit: 128-255
val = val - (1 << bits) # compute negative value
return val
im = Image.open('possum.jpg')
#im.show()
data = numpy.asarray(im)
#print(data)
#print("FINISHED PRINTING")
#print('NOW PRINTING BINARY')
data_binary = numpy.unpackbits(data)
data_binary.ravel()
#print(data_binary)
#print('FINISHED PRINTING')
#getting string of binary array
binaryString = numpy.array2string(data_binary)
binaryString = ''.join(binaryString.split())
binaryString = binaryString[:-1]
binaryString = binaryString[1:]
#print("Binary String: " + binaryString)
out = twos_comp(int(binaryString,2), len(binaryString))
#print('Now printing twos:')
#print(out)
#formatting non-binary two's comp as binary
outBinary = "{0:b}".format(out)
#print('Now printing binary twos: ' + outBinary)
outBinary = outBinary.encode('utf-8')
a_pil_image = Image.frombytes('RGB', (275, 183), outBinary)
a_pil_image.show()
python image numpy python-imaging-library pixel
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I'm doing some prototype code for a project. I'm using Pillow to open the image and other minor things, but I want to invert the image manually using its pixel values. I used two's complement in hopes of inverting it. However, when I display the final image, it's a solid grey square instead of inverted colors. I just used a picture of a possum, 275 pixels by 183 pixels. Any idea why it displays grey block and not an inverted image?
#importing Image module
from PIL import Image
import numpy
#sets numpy to print out full array
numpy.set_printoptions(threshold=numpy.inf)
def twos_comp(val, bits):
"""compute the 2's complement of int value val"""
if (val & (1 << (bits - 1))) != 0: # if sign bit is set e.g., 8bit: 128-255
val = val - (1 << bits) # compute negative value
return val
im = Image.open('possum.jpg')
#im.show()
data = numpy.asarray(im)
#print(data)
#print("FINISHED PRINTING")
#print('NOW PRINTING BINARY')
data_binary = numpy.unpackbits(data)
data_binary.ravel()
#print(data_binary)
#print('FINISHED PRINTING')
#getting string of binary array
binaryString = numpy.array2string(data_binary)
binaryString = ''.join(binaryString.split())
binaryString = binaryString[:-1]
binaryString = binaryString[1:]
#print("Binary String: " + binaryString)
out = twos_comp(int(binaryString,2), len(binaryString))
#print('Now printing twos:')
#print(out)
#formatting non-binary two's comp as binary
outBinary = "{0:b}".format(out)
#print('Now printing binary twos: ' + outBinary)
outBinary = outBinary.encode('utf-8')
a_pil_image = Image.frombytes('RGB', (275, 183), outBinary)
a_pil_image.show()
python image numpy python-imaging-library pixel
add a comment |
up vote
0
down vote
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up vote
0
down vote
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I'm doing some prototype code for a project. I'm using Pillow to open the image and other minor things, but I want to invert the image manually using its pixel values. I used two's complement in hopes of inverting it. However, when I display the final image, it's a solid grey square instead of inverted colors. I just used a picture of a possum, 275 pixels by 183 pixels. Any idea why it displays grey block and not an inverted image?
#importing Image module
from PIL import Image
import numpy
#sets numpy to print out full array
numpy.set_printoptions(threshold=numpy.inf)
def twos_comp(val, bits):
"""compute the 2's complement of int value val"""
if (val & (1 << (bits - 1))) != 0: # if sign bit is set e.g., 8bit: 128-255
val = val - (1 << bits) # compute negative value
return val
im = Image.open('possum.jpg')
#im.show()
data = numpy.asarray(im)
#print(data)
#print("FINISHED PRINTING")
#print('NOW PRINTING BINARY')
data_binary = numpy.unpackbits(data)
data_binary.ravel()
#print(data_binary)
#print('FINISHED PRINTING')
#getting string of binary array
binaryString = numpy.array2string(data_binary)
binaryString = ''.join(binaryString.split())
binaryString = binaryString[:-1]
binaryString = binaryString[1:]
#print("Binary String: " + binaryString)
out = twos_comp(int(binaryString,2), len(binaryString))
#print('Now printing twos:')
#print(out)
#formatting non-binary two's comp as binary
outBinary = "{0:b}".format(out)
#print('Now printing binary twos: ' + outBinary)
outBinary = outBinary.encode('utf-8')
a_pil_image = Image.frombytes('RGB', (275, 183), outBinary)
a_pil_image.show()
python image numpy python-imaging-library pixel
I'm doing some prototype code for a project. I'm using Pillow to open the image and other minor things, but I want to invert the image manually using its pixel values. I used two's complement in hopes of inverting it. However, when I display the final image, it's a solid grey square instead of inverted colors. I just used a picture of a possum, 275 pixels by 183 pixels. Any idea why it displays grey block and not an inverted image?
#importing Image module
from PIL import Image
import numpy
#sets numpy to print out full array
numpy.set_printoptions(threshold=numpy.inf)
def twos_comp(val, bits):
"""compute the 2's complement of int value val"""
if (val & (1 << (bits - 1))) != 0: # if sign bit is set e.g., 8bit: 128-255
val = val - (1 << bits) # compute negative value
return val
im = Image.open('possum.jpg')
#im.show()
data = numpy.asarray(im)
#print(data)
#print("FINISHED PRINTING")
#print('NOW PRINTING BINARY')
data_binary = numpy.unpackbits(data)
data_binary.ravel()
#print(data_binary)
#print('FINISHED PRINTING')
#getting string of binary array
binaryString = numpy.array2string(data_binary)
binaryString = ''.join(binaryString.split())
binaryString = binaryString[:-1]
binaryString = binaryString[1:]
#print("Binary String: " + binaryString)
out = twos_comp(int(binaryString,2), len(binaryString))
#print('Now printing twos:')
#print(out)
#formatting non-binary two's comp as binary
outBinary = "{0:b}".format(out)
#print('Now printing binary twos: ' + outBinary)
outBinary = outBinary.encode('utf-8')
a_pil_image = Image.frombytes('RGB', (275, 183), outBinary)
a_pil_image.show()
python image numpy python-imaging-library pixel
python image numpy python-imaging-library pixel
asked Nov 18 at 22:39
Braydon Rekart
34
34
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You can invert quite simply with PIL/Pillow:
from PIL import Image, ImageChops
# Load image from disk and ensure RGB
im = Image.open('lena.png').convert('RGB')
# Invert image and save to disk
res = ImageChops.invert(im)
res.save('result.png')
Turns Lena into negated Lena:
Or, if you want to be more mathematical about it:
from PIL import Image
import numpy as np
im = Image.open('lena.png').convert('RGB')
# Make Numpy array
imnp = np.array(im)
# Invert
imnp = 255 - imnp
# Save
Image.fromarray(imnp).save('result.png')
If you imagine a black image is represented by (0,0,0) and a white image by (255,255,255), it is hopefully not hard to see that inversion of colours is achieved by subtracting from 255 rather than using two's complement.
I can't do this. As I said in the post, I want to convert them manually using the image's pixels themselves and modifying them on my own, not use the library to do all the work.
– Braydon Rekart
Nov 21 at 21:30
Sorry, I didn't see in your question where you said you couldn't use a library. Just use the second piece of code I supplied - that doesn't use a library and it mathematically subtracts each pixel itself from 255.
– Mark Setchell
Nov 21 at 22:08
I could probably have been clearer in my question. Thank you.
– Braydon Rekart
Nov 22 at 5:27
add a comment |
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1 Answer
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oldest
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1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
0
down vote
You can invert quite simply with PIL/Pillow:
from PIL import Image, ImageChops
# Load image from disk and ensure RGB
im = Image.open('lena.png').convert('RGB')
# Invert image and save to disk
res = ImageChops.invert(im)
res.save('result.png')
Turns Lena into negated Lena:
Or, if you want to be more mathematical about it:
from PIL import Image
import numpy as np
im = Image.open('lena.png').convert('RGB')
# Make Numpy array
imnp = np.array(im)
# Invert
imnp = 255 - imnp
# Save
Image.fromarray(imnp).save('result.png')
If you imagine a black image is represented by (0,0,0) and a white image by (255,255,255), it is hopefully not hard to see that inversion of colours is achieved by subtracting from 255 rather than using two's complement.
I can't do this. As I said in the post, I want to convert them manually using the image's pixels themselves and modifying them on my own, not use the library to do all the work.
– Braydon Rekart
Nov 21 at 21:30
Sorry, I didn't see in your question where you said you couldn't use a library. Just use the second piece of code I supplied - that doesn't use a library and it mathematically subtracts each pixel itself from 255.
– Mark Setchell
Nov 21 at 22:08
I could probably have been clearer in my question. Thank you.
– Braydon Rekart
Nov 22 at 5:27
add a comment |
up vote
0
down vote
You can invert quite simply with PIL/Pillow:
from PIL import Image, ImageChops
# Load image from disk and ensure RGB
im = Image.open('lena.png').convert('RGB')
# Invert image and save to disk
res = ImageChops.invert(im)
res.save('result.png')
Turns Lena into negated Lena:
Or, if you want to be more mathematical about it:
from PIL import Image
import numpy as np
im = Image.open('lena.png').convert('RGB')
# Make Numpy array
imnp = np.array(im)
# Invert
imnp = 255 - imnp
# Save
Image.fromarray(imnp).save('result.png')
If you imagine a black image is represented by (0,0,0) and a white image by (255,255,255), it is hopefully not hard to see that inversion of colours is achieved by subtracting from 255 rather than using two's complement.
I can't do this. As I said in the post, I want to convert them manually using the image's pixels themselves and modifying them on my own, not use the library to do all the work.
– Braydon Rekart
Nov 21 at 21:30
Sorry, I didn't see in your question where you said you couldn't use a library. Just use the second piece of code I supplied - that doesn't use a library and it mathematically subtracts each pixel itself from 255.
– Mark Setchell
Nov 21 at 22:08
I could probably have been clearer in my question. Thank you.
– Braydon Rekart
Nov 22 at 5:27
add a comment |
up vote
0
down vote
up vote
0
down vote
You can invert quite simply with PIL/Pillow:
from PIL import Image, ImageChops
# Load image from disk and ensure RGB
im = Image.open('lena.png').convert('RGB')
# Invert image and save to disk
res = ImageChops.invert(im)
res.save('result.png')
Turns Lena into negated Lena:
Or, if you want to be more mathematical about it:
from PIL import Image
import numpy as np
im = Image.open('lena.png').convert('RGB')
# Make Numpy array
imnp = np.array(im)
# Invert
imnp = 255 - imnp
# Save
Image.fromarray(imnp).save('result.png')
If you imagine a black image is represented by (0,0,0) and a white image by (255,255,255), it is hopefully not hard to see that inversion of colours is achieved by subtracting from 255 rather than using two's complement.
You can invert quite simply with PIL/Pillow:
from PIL import Image, ImageChops
# Load image from disk and ensure RGB
im = Image.open('lena.png').convert('RGB')
# Invert image and save to disk
res = ImageChops.invert(im)
res.save('result.png')
Turns Lena into negated Lena:
Or, if you want to be more mathematical about it:
from PIL import Image
import numpy as np
im = Image.open('lena.png').convert('RGB')
# Make Numpy array
imnp = np.array(im)
# Invert
imnp = 255 - imnp
# Save
Image.fromarray(imnp).save('result.png')
If you imagine a black image is represented by (0,0,0) and a white image by (255,255,255), it is hopefully not hard to see that inversion of colours is achieved by subtracting from 255 rather than using two's complement.
edited Nov 19 at 18:55
answered Nov 19 at 18:19
Mark Setchell
85.4k673172
85.4k673172
I can't do this. As I said in the post, I want to convert them manually using the image's pixels themselves and modifying them on my own, not use the library to do all the work.
– Braydon Rekart
Nov 21 at 21:30
Sorry, I didn't see in your question where you said you couldn't use a library. Just use the second piece of code I supplied - that doesn't use a library and it mathematically subtracts each pixel itself from 255.
– Mark Setchell
Nov 21 at 22:08
I could probably have been clearer in my question. Thank you.
– Braydon Rekart
Nov 22 at 5:27
add a comment |
I can't do this. As I said in the post, I want to convert them manually using the image's pixels themselves and modifying them on my own, not use the library to do all the work.
– Braydon Rekart
Nov 21 at 21:30
Sorry, I didn't see in your question where you said you couldn't use a library. Just use the second piece of code I supplied - that doesn't use a library and it mathematically subtracts each pixel itself from 255.
– Mark Setchell
Nov 21 at 22:08
I could probably have been clearer in my question. Thank you.
– Braydon Rekart
Nov 22 at 5:27
I can't do this. As I said in the post, I want to convert them manually using the image's pixels themselves and modifying them on my own, not use the library to do all the work.
– Braydon Rekart
Nov 21 at 21:30
I can't do this. As I said in the post, I want to convert them manually using the image's pixels themselves and modifying them on my own, not use the library to do all the work.
– Braydon Rekart
Nov 21 at 21:30
Sorry, I didn't see in your question where you said you couldn't use a library. Just use the second piece of code I supplied - that doesn't use a library and it mathematically subtracts each pixel itself from 255.
– Mark Setchell
Nov 21 at 22:08
Sorry, I didn't see in your question where you said you couldn't use a library. Just use the second piece of code I supplied - that doesn't use a library and it mathematically subtracts each pixel itself from 255.
– Mark Setchell
Nov 21 at 22:08
I could probably have been clearer in my question. Thank you.
– Braydon Rekart
Nov 22 at 5:27
I could probably have been clearer in my question. Thank you.
– Braydon Rekart
Nov 22 at 5:27
add a comment |
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