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
Save the last batch of data in image set conversion
Merge pull request #61 from kloudkl/master

Save the last batch of data in image set conversion

+ comment and output edits
align detector comments to reality