How to create surface plot from greyscale image with Matplotlib?

Question

Let's say I have a greyscale image (size: 550x150 px). I load the image with matplolib

import matplotlib.pyplot as plt
import matplotlib.image as mp_img
image = mp_img.imread("my-cat.png")
plt.imshow(image)
plt.show()

Now, plt.imshow displays the image on the screen. But what I want is a surface plot of the greyscale values, something like this:

.Colour is not really a necessity, but it would be helpful for the height lines. I know, that I need a function of the form f(x,y) -> z to create the surface plot. So, I want to use the greyscale value at (x_pixel,y_pixel) in my image to get the value of f. This leads to my problem:

I'd like to do some interpolation (e.g. smoothing) of my image values during plotting. This depends also on the size of my meshgrid, so how do I control this? And,
how do I make a surface plot of the greyscale values from my image?

hitzg · Accepted Answer · 2015-08-04 10:30:58Z

30

So this is pretty straightforward. Load the data, build the plot:

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

# generate some sample data
import scipy.misc
lena = scipy.misc.lena()

# downscaling has a "smoothing" effect
lena = scipy.misc.imresize(lena, 0.15, interp='cubic')

# create the x and y coordinate arrays (here we just use pixel indices)
xx, yy = np.mgrid[0:lena.shape[0], 0:lena.shape[1]]

# create the figure
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.plot_surface(xx, yy, lena ,rstride=1, cstride=1, cmap=plt.cm.gray,
        linewidth=0)

# show it
plt.show()

Result:

answered Aug 4, 2015 at 10:30

hitzg

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5 Comments

BlueLemon Over a year ago

150 * 0.15 ~ 22 mesh points it would be nice if I could resolve structures in more detail. I know it is a quite general statement but I'm looking for a smoothing filter which preserves detail despite high contrasts and strongly varying gradients. Anyway, I'll accept your answer if you add a bilateral filter or something similar.

hitzg Over a year ago

Accept it or not, as you wish. This is not a coding service, where you get to demand what you want. Show what you have tried and describe where you get stuck.

Peter Hanley Over a year ago

What's confusing for me is when I try to move away from examples using the sample data (e.g. img = scipy.misc.lena()) to real data (e.g. img = imread('20141007225851_145162701.png)) I get ValueError: shape mismatch: two or more arrays have incompatible dimensions on axis 1 There's an obvious difference between the two (the np array is nested one level deeper when it comes from imread instead of misc.data) but I'm not exactly sure why, but using img[0] doesn't work, event though the data format looks the same. I realize it's just something dumb that I'm missing, annoying tho

Peter Hanley Over a year ago

I figured it out - you have to make sure that xx.shape, yy.shape, lena.shape are all the same; in my case the img I was reading in was actually an rgb file, so I had to add from skimage.color import rgb2gray; gray_img = rgb2gray(img) and after that ax.plot_surface(xx, yy, img_sm ...) worked fine.

romain gal Over a year ago

Up 2023 : If you've got this message : TypeError: gca() got an unexpected keyword argument 'projection', ax = fig.add_subplot(projection = '3d') will solve the error.

Community · Accepted Answer · 2020-06-20 09:12:55Z

3

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import cv2

# generate some sample data
import scipy.misc
lena = cv2.imread("./data/lena.png", 0)

# downscaling has a "smoothing" effect
lena = cv2.resize(lena, (100,100))

# create the x and y coordinate arrays (here we just use pixel indices)
xx, yy = np.mgrid[0:lena.shape[0], 0:lena.shape[1]]

# create the figure
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.plot_surface(xx, yy, lena ,rstride=1, cstride=1, cmap=plt.cm.jet,
                linewidth=0)

# show it
plt.show()

If you want to get color plot, change the code to: "cmap=plt.cm.jet". So you can get something like this: color plot

edited Jun 20, 2020 at 9:12

CommunityBot

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answered Jun 7, 2019 at 6:11

Trinh Nguyen Quoc

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