./pycocoevalcap: The folder where all evaluation codes are stored.
evals.py: The file includes COCOEavlCap class that can be used to evaluate results on COCO.
tokenizer: Python wrapper of Stanford CoreNLP PTBTokenizer
bleu: Bleu evalutation codes
meteor: Meteor evaluation codes
rouge: Rouge-L evaluation codes
cider: CIDEr evaluation codes
spice: SPICE evaluation codes
Setup
You will first need to download the Stanford CoreNLP 3.6.0 code and models for use by SPICE. To do this, run:
./get_stanford_models.sh
Note: SPICE will try to create a cache of parsed sentences in ./pycocoevalcap/spice/cache/. This dramatically speeds up repeated evaluations. The cache directory can be moved by setting 'CACHE_DIR' in ./pycocoevalcap/spice. In the same file, caching can be turned off by removing the '-cache' argument to 'spice_cmd'.
Meteor: Project page with related publications. We use the latest version (1.5) of the Code. Changes have been made to the source code to properly aggreate the statistics for the entire corpus.
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