%%javascript
$.getScript('../ipython_notebook_toc.js');
%matplotlib inline
import sys
sys.path.insert(0,'..')
from IPython.display import HTML
from helpers import header
HTML(header())
Most of the samples given in this course use python and numpy package, an example is given below where the gray level histogram is computed for an image using standard histogram
numpy function.
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
from skimage.data import camera
plt.style.use('ggplot')
plt.figure(figsize=[10,5])
ima = camera() #use a test image provided by the skimage library
hist,bins = np.histogram(ima.flatten(),range(256)) # histogram is computed on a 1D distribution --> flatten()
norm_hist = 1.*hist/np.sum(hist) # normalized histogram
# display the results
plt.subplot(1,2,1)
plt.imshow(camera(),cmap=cm.gray)
plt.subplot(1,2,2)
plt.plot(norm_hist)
plt.xlabel('gray level');