a py3 lib for NLP & image-caption metrics : BLEU METEOR CIDEr ROUGE SPICE WMD

Features below:

• python3 support
• add new metric WMD

• java 1.8+

• python 3 (Python2 has not been tested)

  • gensim

• Stanford CoreNLP 3.6.0(download)

  • add stanford-corenlp-3.6.0.jar to pycocoevalcap/spice/lib/
  • add stanford-corenlp-3.6.0-models.jar to pycocoevalcap/spice/lib/

• google_word2vec_model for WMD(download)

  • unzip it and add GoogleNews-vectors-negative300.bin to pycocoevalcap/wmd/data

See in demo.py

• Note that the input format must be the same as the file in examples/gts.json and examples/res.json
• It seems can't run in windows(error about java), run it on Linux

import pycocoevalcap.eval as E

with open('examples/gts.json', 'r') as f: 
    gts = json.load(f)
with open('examples/res.json', 'r') as f:
    res = json.load(f)
    
ans = E.eval(gts,tes)
print(ans)
bleu = E.get_bleu(gts,res)
print(bleu)
cider = E.get_cider(gts,res)
print(cider)

• WMD metric from https://github.com/mtanti/coco-caption
• main code from https://github.com/wangleihitcs/CaptionMetrics