add demo of batch processing via concurrent.futures

[grlee77]

I thought the following demo for processing a set of images in parallel might be of interest. I made this while testing the GIL release implemented in #188 and just cleaned it up a bit for use as a demo.

The demo does require concurrent.futures which is part Python 3. A user on Python 2.6 or 2.7 will receive an error message to first pip install futures if it is not already installed.

Output for an older dual-socket workstation is:

Sequential Case
        Elapsed time: 516.67 ms

Multithreaded Case
        Number of concurrent workers: 16
        Elapsed time: 77.43 ms

Relative speedup with concurrent = 6.6723611214598755

On a 4-core OS X laptop I observed a speedup of 3.34.

[codecov-io]

Current coverage is 86.53% (diff: 100%)

Merging #230 into master will not change coverage

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[rgommers]

For a standalone demo I think the extra dependency on futures is no problem at all.

[rgommers]

I get a similar speedup - just under 50%, also with fewer cores (1 thread per physical core). Images are a bit small to get more I guess.

Example looks clear, no comments.

[rgommers]

Okay, good as is so merging. Thanks @grlee77!