Download eval/coco_caption/pycocoevalcap/eval.py from datnguyentien204/BLIP_ImagesCaptioning: direct link, hf CLI and curl.
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- Download file 3.34 kB
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https://huggingface.co/datasets/datnguyentien204/BLIP_ImagesCaptioning/resolve/main/eval/coco_caption/pycocoevalcap/eval.py
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hf download hf://datasets/datnguyentien204/BLIP_ImagesCaptioning/eval/coco_caption/pycocoevalcap/eval.py
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curl -L -o eval.py https://huggingface.co/datasets/datnguyentien204/BLIP_ImagesCaptioning/resolve/main/eval/coco_caption/pycocoevalcap/eval.py
3.34 kB
| from __future__ import absolute_import | |
| from __future__ import division | |
| from __future__ import print_function | |
| __author__ = 'tylin' | |
| from .bleu.bleu import Bleu | |
| # from .meteor.meteor import Meteor | |
| # from .rouge.rouge import Rouge | |
| from .cider.cider import Cider | |
| # from .spice.spice import Spice | |
| from .wmd.wmd import WMD | |
| class COCOEvalCap: | |
| def __init__(self, coco, cocoRes, language='vi'): | |
| self.evalImgs = [] | |
| self.eval = {} | |
| self.imgToEval = {} | |
| self.coco = coco | |
| self.cocoRes = cocoRes | |
| self.params = {'image_id': coco.getImgIds()} | |
| # self.Spice = Spice() | |
| self.language = language | |
| def evaluate(self): | |
| imgIds = self.params['image_id'] | |
| # imgIds = self.coco.getImgIds() | |
| gts = {} | |
| res = {} | |
| for imgId in imgIds: | |
| gts[imgId] = self.coco.imgToAnns[imgId] | |
| res[imgId] = self.cocoRes.imgToAnns[imgId] | |
| # ================================================= | |
| # Set up scorers | |
| # ================================================= | |
| print('tokenization...') | |
| if self.language == 'en': | |
| print('using en tokenizer') | |
| from .tokenizer.ptbtokenizer import PTBTokenizer | |
| tokenizer = PTBTokenizer() | |
| elif self.language == 'vi': | |
| print('Using Vietnamese tokenizer from pyvi') | |
| from .tokenizer.vitokenizer import VITokenizer | |
| tokenizer = VITokenizer() | |
| else: | |
| raise(f'Language "{self.language}" is not supported!') | |
| gts = tokenizer.tokenize(gts) | |
| res = tokenizer.tokenize(res) | |
| # ================================================= | |
| # Set up scorers | |
| # ================================================= | |
| print('setting up scorers...') | |
| scorers = [ | |
| (Bleu(4), ["Bleu_1", "Bleu_2", "Bleu_3", "Bleu_4"]), | |
| # (Meteor(),"METEOR"), | |
| # (Rouge(), "ROUGE_L"), | |
| (Cider(), "CIDEr"), | |
| # (self.Spice, "SPICE"), | |
| # (WMD(), "WMD"), | |
| ] | |
| # ================================================= | |
| # Compute scores | |
| # ================================================= | |
| for scorer, method in scorers: | |
| print('computing %s score...'%(scorer.method())) | |
| score, scores = scorer.compute_score(gts, res) | |
| if type(method) == list: | |
| for sc, scs, m in zip(score, scores, method): | |
| self.setEval(sc, m) | |
| self.setImgToEvalImgs(scs, list(gts.keys()), m) | |
| print("%s: %0.3f"%(m, sc)) | |
| else: | |
| self.setEval(score, method) | |
| self.setImgToEvalImgs(scores, list(gts.keys()), method) | |
| print("%s: %0.3f"%(method, score)) | |
| self.setEvalImgs() | |
| def setEval(self, score, method): | |
| self.eval[method] = score | |
| def setImgToEvalImgs(self, scores, imgIds, method): | |
| for imgId, score in zip(imgIds, scores): | |
| if not imgId in self.imgToEval: | |
| self.imgToEval[imgId] = {} | |
| self.imgToEval[imgId]["image_id"] = imgId | |
| self.imgToEval[imgId][method] = score | |
| def setEvalImgs(self): | |
| self.evalImgs = [eval for imgId, eval in list(self.imgToEval.items())] | |