How to make Image data to 2-D distribution plot?
How to make Image data to 2-D distribution plot ?
I want to visualize image date to 2-dimensional distribution.
Is this possible ?
Image like MNIST : enter image description here
2D distribution like this :enter image description here
deep-learning
asked Nov 17 '18 at 13:51
NazzzzNazzzz
54
add a comment |
How to make Image data to 2-D distribution plot ?
I want to visualize image date to 2-dimensional distribution.
Is this possible ?
Image like MNIST : enter image description here
2D distribution like this :enter image description here
deep-learning
asked Nov 17 '18 at 13:51
NazzzzNazzzz
54
what is exactlyP(x)andQ(x)?
– M. Doosti Lakhani
Nov 17 '18 at 14:36
@M.DoostiLakhani That image is just show 2-d distribution. P(x) or Q(x) doesn't matter.I just want to plot MNIST data to 2D dist.
– Nazzzz
Nov 18 '18 at 1:05
add a comment |
How to make Image data to 2-D distribution plot ?
I want to visualize image date to 2-dimensional distribution.
Is this possible ?
Image like MNIST : enter image description here
2D distribution like this :enter image description here
deep-learning
asked Nov 17 '18 at 13:51
NazzzzNazzzz
54
How to make Image data to 2-D distribution plot ?
I want to visualize image date to 2-dimensional distribution.
Is this possible ?
Image like MNIST : enter image description here
2D distribution like this :enter image description here
deep-learning
deep-learning
asked Nov 17 '18 at 13:51
NazzzzNazzzz
54
asked Nov 17 '18 at 13:51
NazzzzNazzzz
54
asked Nov 17 '18 at 13:51
NazzzzNazzzz
54
asked Nov 17 '18 at 13:51
NazzzzNazzzz
54
asked Nov 17 '18 at 13:51
NazzzzNazzzz
54
54
what is exactlyP(x)andQ(x)?
– M. Doosti Lakhani
Nov 17 '18 at 14:36
@M.DoostiLakhani That image is just show 2-d distribution. P(x) or Q(x) doesn't matter.I just want to plot MNIST data to 2D dist.
– Nazzzz
Nov 18 '18 at 1:05
add a comment |
what is exactlyP(x)andQ(x)?
– M. Doosti Lakhani
Nov 17 '18 at 14:36
@M.DoostiLakhani That image is just show 2-d distribution. P(x) or Q(x) doesn't matter.I just want to plot MNIST data to 2D dist.
– Nazzzz
Nov 18 '18 at 1:05
what is exactly
P(x) and Q(x)?– M. Doosti Lakhani
Nov 17 '18 at 14:36
what is exactly
P(x) and Q(x)?– M. Doosti Lakhani
Nov 17 '18 at 14:36
@M.DoostiLakhani That image is just show 2-d distribution. P(x) or Q(x) doesn't matter.I just want to plot MNIST data to 2D dist.
– Nazzzz
Nov 18 '18 at 1:05
@M.DoostiLakhani That image is just show 2-d distribution. P(x) or Q(x) doesn't matter.I just want to plot MNIST data to 2D dist.
– Nazzzz
Nov 18 '18 at 1:05
add a comment |
1 Answer
1
active
oldest
votes
About mnist, it does not mean anything I think. Because you have one channel of binary image so you have only zero or one. So you cannot have any plot like that.
But if you have grayscale image or colored image, you can do this:
source image:
import cv2
from matplotlib import pyplot as plt
img = cv2.imread('img.jpg', -1)
cv2.imshow('image',img)
color = ('b','g','r')
for channel,col in enumerate(color):
histr = cv2.calcHist([img],[channel],None,[256],[0,256])
plt.plot(histr,color = col)
plt.xlim([0,256])
plt.title('Histogram for color scale picture')
plt.show()
cv2.destroyAllWindows()
And if your image is grayscale:
# 1 channel image - grayscale
import cv2
from matplotlib import pyplot as plt
gray_img = cv2.imread('mnist.png')
cv2.imshow('image',gray_img)
hist = cv2.calcHist([gray_img],[0],None,[256],[0,256])
plt.hist(gray_img.ravel(),256,[0,256])
plt.title('Histogram for gray scale picture')
plt.show()
cv2.destroyAllWindows()
And the matplotlib way is:
import matplotlib.image as mpimg
from matplotlib import pyplot as plt
img=mpimg.imread('img.jpg')
imgplot = plt.imshow(img)
plt.hist(img.ravel(), bins=256, fc='k', ec='k')
answered Nov 18 '18 at 9:47
M. Doosti LakhaniM. Doosti Lakhani
334417
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
About mnist, it does not mean anything I think. Because you have one channel of binary image so you have only zero or one. So you cannot have any plot like that.
But if you have grayscale image or colored image, you can do this:
source image:
import cv2
from matplotlib import pyplot as plt
img = cv2.imread('img.jpg', -1)
cv2.imshow('image',img)
color = ('b','g','r')
for channel,col in enumerate(color):
histr = cv2.calcHist([img],[channel],None,[256],[0,256])
plt.plot(histr,color = col)
plt.xlim([0,256])
plt.title('Histogram for color scale picture')
plt.show()
cv2.destroyAllWindows()
And if your image is grayscale:
# 1 channel image - grayscale
import cv2
from matplotlib import pyplot as plt
gray_img = cv2.imread('mnist.png')
cv2.imshow('image',gray_img)
hist = cv2.calcHist([gray_img],[0],None,[256],[0,256])
plt.hist(gray_img.ravel(),256,[0,256])
plt.title('Histogram for gray scale picture')
plt.show()
cv2.destroyAllWindows()
And the matplotlib way is:
import matplotlib.image as mpimg
from matplotlib import pyplot as plt
img=mpimg.imread('img.jpg')
imgplot = plt.imshow(img)
plt.hist(img.ravel(), bins=256, fc='k', ec='k')
answered Nov 18 '18 at 9:47
M. Doosti LakhaniM. Doosti Lakhani
334417
add a comment |
About mnist, it does not mean anything I think. Because you have one channel of binary image so you have only zero or one. So you cannot have any plot like that.
But if you have grayscale image or colored image, you can do this:
source image:
import cv2
from matplotlib import pyplot as plt
img = cv2.imread('img.jpg', -1)
cv2.imshow('image',img)
color = ('b','g','r')
for channel,col in enumerate(color):
histr = cv2.calcHist([img],[channel],None,[256],[0,256])
plt.plot(histr,color = col)
plt.xlim([0,256])
plt.title('Histogram for color scale picture')
plt.show()
cv2.destroyAllWindows()
And if your image is grayscale:
# 1 channel image - grayscale
import cv2
from matplotlib import pyplot as plt
gray_img = cv2.imread('mnist.png')
cv2.imshow('image',gray_img)
hist = cv2.calcHist([gray_img],[0],None,[256],[0,256])
plt.hist(gray_img.ravel(),256,[0,256])
plt.title('Histogram for gray scale picture')
plt.show()
cv2.destroyAllWindows()
And the matplotlib way is:
import matplotlib.image as mpimg
from matplotlib import pyplot as plt
img=mpimg.imread('img.jpg')
imgplot = plt.imshow(img)
plt.hist(img.ravel(), bins=256, fc='k', ec='k')
answered Nov 18 '18 at 9:47
M. Doosti LakhaniM. Doosti Lakhani
334417
add a comment |
About mnist, it does not mean anything I think. Because you have one channel of binary image so you have only zero or one. So you cannot have any plot like that.
But if you have grayscale image or colored image, you can do this:
source image:
import cv2
from matplotlib import pyplot as plt
img = cv2.imread('img.jpg', -1)
cv2.imshow('image',img)
color = ('b','g','r')
for channel,col in enumerate(color):
histr = cv2.calcHist([img],[channel],None,[256],[0,256])
plt.plot(histr,color = col)
plt.xlim([0,256])
plt.title('Histogram for color scale picture')
plt.show()
cv2.destroyAllWindows()
And if your image is grayscale:
# 1 channel image - grayscale
import cv2
from matplotlib import pyplot as plt
gray_img = cv2.imread('mnist.png')
cv2.imshow('image',gray_img)
hist = cv2.calcHist([gray_img],[0],None,[256],[0,256])
plt.hist(gray_img.ravel(),256,[0,256])
plt.title('Histogram for gray scale picture')
plt.show()
cv2.destroyAllWindows()
And the matplotlib way is:
import matplotlib.image as mpimg
from matplotlib import pyplot as plt
img=mpimg.imread('img.jpg')
imgplot = plt.imshow(img)
plt.hist(img.ravel(), bins=256, fc='k', ec='k')
answered Nov 18 '18 at 9:47
M. Doosti LakhaniM. Doosti Lakhani
334417
About mnist, it does not mean anything I think. Because you have one channel of binary image so you have only zero or one. So you cannot have any plot like that.
But if you have grayscale image or colored image, you can do this:
source image:
import cv2
from matplotlib import pyplot as plt
img = cv2.imread('img.jpg', -1)
cv2.imshow('image',img)
color = ('b','g','r')
for channel,col in enumerate(color):
histr = cv2.calcHist([img],[channel],None,[256],[0,256])
plt.plot(histr,color = col)
plt.xlim([0,256])
plt.title('Histogram for color scale picture')
plt.show()
cv2.destroyAllWindows()
And if your image is grayscale:
# 1 channel image - grayscale
import cv2
from matplotlib import pyplot as plt
gray_img = cv2.imread('mnist.png')
cv2.imshow('image',gray_img)
hist = cv2.calcHist([gray_img],[0],None,[256],[0,256])
plt.hist(gray_img.ravel(),256,[0,256])
plt.title('Histogram for gray scale picture')
plt.show()
cv2.destroyAllWindows()
And the matplotlib way is:
import matplotlib.image as mpimg
from matplotlib import pyplot as plt
img=mpimg.imread('img.jpg')
imgplot = plt.imshow(img)
plt.hist(img.ravel(), bins=256, fc='k', ec='k')
answered Nov 18 '18 at 9:47
M. Doosti LakhaniM. Doosti Lakhani
334417
answered Nov 18 '18 at 9:47
M. Doosti LakhaniM. Doosti Lakhani
334417
answered Nov 18 '18 at 9:47
M. Doosti LakhaniM. Doosti Lakhani
334417
answered Nov 18 '18 at 9:47
M. Doosti LakhaniM. Doosti Lakhani
334417
334417
add a comment |
add a comment |
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what is exactly
P(x)andQ(x)?– M. Doosti Lakhani
Nov 17 '18 at 14:36
@M.DoostiLakhani That image is just show 2-d distribution. P(x) or Q(x) doesn't matter.I just want to plot MNIST data to 2D dist.
– Nazzzz
Nov 18 '18 at 1:05