Q:

Python: plotting sift points returns points off the pictures

I'm using the sift implementation along with code found in the "Programming Computer Vision with Python".   
While using the plotMatches function in vision.py (equivalent to the plot_matches() function to the book), some of the points plotted aren't even on the image: 

As you can see, most of the points aren't on either of the image.   
This may be the result of a change I had to make to my plotMatches() function:
        for i, m in enumerate(matchscores):
            if i > 0:
                 lab.plot([locs1[i][1], locs2[i][1] + cols1],
                 [locs1[i][0], locs2[i][0]], 'c')

The original code:
        for i, m in enumerate(matchscores):
            if i > 0:
                lab.plot([locs1[i][1], locs2[m][1] + cols1],
                [locs1[i][0], locs2[m][0]], 'c')

Would throw the following error:
    Traceback (most recent call last):
    File "/home/peter-brown/AI/Markus/ImageRecognition.py", line 37,     in <module>
     sch.plotMatches(image, image2, l1, l2, matches, show_below=False)
     File "/home/peter-brown/AI/Markus/vision.py", line 199, in    plotMatches
     lab.plot([locs1[i][1], locs2[m][1] + cols1],
     IndexError: index 1 is out of bounds for axis 0 with size 1

By changing any 'm' used in the code, the program would work, but it would output incorrectly. 
Why does the output not correspond to the image, and how can i change the plotMatches function to work? 

A:

In matplotlib, the x and y coordinates are flipped.  From your image it looks like you are interpreting all x coordinates as y coordinates and vice-versa.  From your function, this is a simple change: 
for i, m in enumerate(matchscores):
        if i > 0:
             lab.plot([locs1[i][0], locs2[i][0] + cols1],
             [locs1[i][1], locs2[i][1]], 'c')

