move imagenet splits + synsets to data
add imagenet mean file
file mnist
Make tools/ for core binaries, stow scripts/ in tools/extra

Collect core Caffe tools like train_net, device_query, etc. together in
tools/ and include helper scripts under tools/extra.
fix mnist comments in cifar example
file models
explain ignore, and ignore data, models, and examples

Data, models, and examples should not be versioned by default. Reference
versions of these are not to be casually committed.

Plus this makes for a better playground in examples without having to
worry about data, intermediate files, or experiments being accidentally
tracked.
swap ilsvrc data with fetch script
fetch caffe_reference_imagenet_model
include model checksum, you never know these days
everything in its right place
TODO cifar example
fix mnist, add deploy net example
harmonize imagenet example, name caffe reference model CaffeNet
fix + rename lenet training script
bring mnist docs back to reality
bring imagenet docs back to reality

- fix paths
- replace shell command blocks with scripts
- file ipython notebooks in examples
- proofread
Merge pull request #142 from shelhamer/data-aux

Sort out models, data, examples, and tools
Add and test Net::HasBlob and GetBlob to simplify feature extraction

Inspired by @kencoken's commit f36e715
https://github.com/kencoken/caffe/commit/f36e71569455c9fbb4bf8a63c2d53224e32a4e7b

Related issues:
#20: Extract the middle features
#112: pythonic export of features and params for wrapper
#139: About dump_network.cpp
Add and test Net::HasLayer and GetLayerByName