ignore caffe generated files and stop ignoring examples

- ignore models and snapshots, means, and input databases
- excluding exceptions to commits is easier than including exhaustively
set examples paths relative to root
Merge pull request #1003 from shelhamer/examples-from-root

Standardize examples
[example] finetuning CaffeNet on Flickr Style data
[example] edit fine-tuning and train on ~2000 images, 1557 / 382 split

- further detail merits of fine-tuning: less starving for itme and data
- set random seed for reproducing the tutorial
- 1557 train / 382 test split is more indicative of training quality
  than splits of 200 images
Merge pull request #970 from sergeyk/dev

Fine-tuning tutorial: adapt CaffeNet to Flickr Style data
Create base data layer and base prefetching data layer
Extract common data layer functionalities out of the DataLayer
Remove duplicate codes from the ImageDataLayer
Simplify the WindowDataLayer using the base class
The BasePrefetchingDataLayer shouldn't join the thread
Implement Forward_gpu in the base prefetching data layer
Add utility function to convert OpenCV image into Datum and Blob
Add transformer to the memory data layer
Remove pthread which has been replaced with boost thread
Move transform param one level up in the proto to reduce redundancy