python image recognition [closed]

A typical python tool chain would be:

• read your images with with PIL
• transform them into Numpy arrays
• use Scipy’s image filters (linear and rank, morphological) to implement your solution

As far differentiating the shapes, I would obtain its silhouette by looking at the shape of the background. I would then detect the number of corners using a corner detection algorithm (e.g. Harris). A triangle has 3 corners, a square 4, and a smiley none.
Here’s a python implementation of the Harris corner detection with Scipy.

Edit:

As you mention in the comments, the blog post didn’t present the function that produces a gaussian kernel needed in the algorithm. Here’s an example of a such a function from the Scipy Cookbook (great resource btw):

def gauss_kern(size, sizey=None):
    """ Returns a normalized 2D gauss kernel array for convolutions """
        size = int(size)
        if not sizey:
            sizey = size
        else:
            sizey = int(sizey)
        x, y = mgrid[-size:size+1, -sizey:sizey+1]
        g = exp(-(x**2/float(size)+y**2/float(sizey)))
        return g / g.sum()