reformatted README

README.md

@@ -1,8 +1,8 @@
-REQUIREMENTS:
+## REQUIREMENTS:
 MATLAB 2015a or newer (for native python support)
 MatConvNet beta19 http://www.vlfeat.org/matconvnet/
 
-SETUP INSTRUCTIONS:
+## SETUP INSTRUCTIONS:
 1. Create a data directory
 2. Setup directory paths as specified in globals.m. Relevant tarballs specified in comments
 3. Clone the VQA API into the data directory and setup annotations 
@@ -11,19 +11,19 @@ SETUP INSTRUCTIONS:
 6. Create results directory to store model snapshots from training
 7. Download and extract text feature caches to top level directory (wget http://xor.cs.illinois.edu/~kevin/wtl_cache_feats/word2vec_cache_utils.tar.gz)
 
-MAIN FUNCTIONS:
+## MAIN FUNCTIONS:
 word_and_vision_regions_inner_network.m : running this should initialize training. Results stored in opts.train.expDir
 word_and_vision_regions_inner_network_init.m: constructs the network
 mcqMaxMarginLossLayer.m: Loss layer implementation
 regionsProjectInnerLayer2.m: region selection layer implementation
 determiner_list.m: list of removed stopwords removed from questions
 globals.m: contains global paths to where cached features are stored.
 
-VISUALIZATION EXAMPLE:
+## VISUALIZATION EXAMPLE:
 run visualize_on_held_out.m to visualize results on the held-out set. The held out set comprises 10% of the training data from the train set.
 Our test model can be downloaded from:  http://xor.cs.illinois.edu/~kevin/wtl_cache_feats/wtl_trainval_model.mat
 
-DIRECTORIES:
+## DIRECTORIES:
 word2vec_cache_utils: directory that holds caches of pre-processed question and answers
 utils: misc utility functions