License under BSD

Caffe is henceforth BSD licensed and welcomes community contributions!
include intro, license, and citing in README
include install notes
Do snapshot after computing loss and test accuracy
Merge pull request #51 from sguada/solver_test

Do snapshot after computing loss and test accuracy
default power_wrapper batch size to 10 (aeca741a69 cont'd)

default command line arg and function arg to 10
remove global BATCH_SIZE in favor of arg
give batch size efficiency advice
ignore distribute dir
python lint
groom power_wrapper flags
generalize power_wrapper to different networks and inputs

generalize from the imagenet reference to other detection networks:
- refactor to configure for a given net and data source
- determine dimensions of net input and output automatically from blobs
note power_wrapper TODOs
groom power_wrapper flags (cont'd)
promote power_wrapper to 'detection' submodule
Merge pull request #56 from shelhamer/detection-wrapper

Make detection module for python wrapper
document power_wrapper -> detector in detection notebook
automagically set detection batch size from network
fix ImageNet solver max iteration typo

max iteration no. is 450,000 (= 90 epochs)

caught by @SWu
https://github.com/BVLC/caffe/pull/33#issuecomment-33175810
replace magic numbers with variable names in comments
detect by window list

Do window detection on a list of predefined windows by adding a
crop_mode `list` that accepts a path to a text file of format:

    image_filename xmin ymin xmax ymax