#!/usr/bin/env python
# coding: utf-8

# > This is one of the 100 recipes of the [IPython Cookbook](http://ipython-books.github.io/), the definitive guide to high-performance scientific computing and data science in Python.
# 

# # 11.4. Finding points of interest in an image

# You need to download the *Child* dataset on the book's website. (http://ipython-books.github.io)

# 1. Let's import the packages.

# In[ ]:


import numpy as np
import matplotlib.pyplot as plt
import skimage
import skimage.feature as sf
import matplotlib as mpl
get_ipython().run_line_magic('matplotlib', 'inline')


# 2. We create a function to display a colored or grayscale image.

# In[ ]:


def show(img, cmap=None):
    cmap = cmap or plt.cm.gray
    plt.figure(figsize=(4,2));
    plt.imshow(img, cmap=cmap);
    plt.axis('off');


# 3. We load an image.

# In[ ]:


img = plt.imread('data/pic2.jpg')


# In[ ]:


show(img)


# 4. We find salient points in the image with the Harris corner method. The first step consists in computing the **Harris corner measure response image** with the `corner_harris` function (we will explain this measure in *How it works...*).

# In[ ]:


corners = sf.corner_harris(img[:,:,0])


# In[ ]:


show(corners)


# We see that the patterns in the child's coat are particularly well detected by this algorithm.

# 5. The next step consists in detecting corners from this measure image, using the `corner_peaks` function.

# In[ ]:


peaks = sf.corner_peaks(corners)


# In[ ]:


show(img)
plt.plot(peaks[:,1], peaks[:,0], 'or', ms=4);


# 6. Finally, we create a box around the corner points to define our region of interest.

# In[ ]:


ymin, xmin = peaks.min(axis=0)
ymax, xmax = peaks.max(axis=0)
w, h = xmax-xmin, ymax-ymin


# In[ ]:


k = .25
xmin -= k*w
xmax += k*w
ymin -= k*h
ymax += k*h


# In[ ]:


show(img[ymin:ymax,xmin:xmax])


# > You'll find all the explanations, figures, references, and much more in the book (to be released later this summer).
# 
# > [IPython Cookbook](http://ipython-books.github.io/), by [Cyrille Rossant](http://cyrille.rossant.net), Packt Publishing, 2014 (500 pages).