This paper presents a system to automatically generate natural language description from images that explots both statistics gleaned from parsing large quantities of text data and recognition algorithms from computer vision.

The file flickr.py is an implementation of the section 5.2 from the above paper.

• Around 5000 flickr image descriptions were collected based on each of the PASCAL 2010 object categories.
• Each sentence from this description set is parsed by Stanford dependency parser to generate the parse tree and dependency list for the sentense.
• Collected statistics about the occurance of each attribute and object pair using the adjectival modifier dependency amod(attribute,object)
• Counts for synonyms of object and attribute terms are merged together.