| # Filename: cider.py | |
| # | |
| # Description: Describes the class to compute the CIDEr (Consensus-Based Image Description Evaluation) Metric | |
| # by Vedantam, Zitnick, and Parikh (http://arxiv.org/abs/1411.5726) | |
| # | |
| # Creation Date: Sun Feb 8 14:16:54 2015 | |
| # | |
| # Authors: Ramakrishna Vedantam <[email protected]> and Tsung-Yi Lin <[email protected]> | |
| from cider_scorer import CiderScorer | |
| import pdb | |
| class Cider: | |
| """ | |
| Main Class to compute the CIDEr metric | |
| """ | |
| def __init__(self, test=None, refs=None, n=4, sigma=6.0): | |
| # set cider to sum over 1 to 4-grams | |
| self._n = n | |
| # set the standard deviation parameter for gaussian penalty | |
| self._sigma = sigma | |
| def compute_score(self, gts, res): | |
| """ | |
| Main function to compute CIDEr score | |
| :param hypo_for_image (dict) : dictionary with key <image> and value <tokenized hypothesis / candidate sentence> | |
| ref_for_image (dict) : dictionary with key <image> and value <tokenized reference sentence> | |
| :return: cider (float) : computed CIDEr score for the corpus | |
| """ | |
| assert(gts.keys() == res.keys()) | |
| imgIds = gts.keys() | |
| cider_scorer = CiderScorer(n=self._n, sigma=self._sigma) | |
| for id in imgIds: | |
| hypo = res[id] | |
| ref = gts[id] | |
| # Sanity check. | |
| assert(type(hypo) is list) | |
| assert(len(hypo) == 1) | |
| assert(type(ref) is list) | |
| assert(len(ref) > 0) | |
| cider_scorer += (hypo[0], ref) | |
| (score, scores) = cider_scorer.compute_score() | |
| return score, scores | |
| def method(self): | |
| return "CIDEr" |