Python bleu.bleu.Bleu() Examples
The following are 17
code examples of bleu.bleu.Bleu().
You can vote up the ones you like or vote down the ones you don't like,
and go to the original project or source file by following the links above each example.
You may also want to check out all available functions/classes of the module
bleu.bleu
, or try the search function
.
.
Example #1
| Source File: tester.py From deep-summarization with MIT License | 6 votes |
|
def score(ref, hypo):
"""
ref, dictionary of reference sentences (id, sentence)
hypo, dictionary of hypothesis sentences (id, sentence)
score, dictionary of scores
"""
scorers = [
(Bleu(4), ["Bleu_1", "Bleu_2", "Bleu_3", "Bleu_4"]),
(Rouge(), "ROUGE_L"),
]
final_scores = {}
for scorer, method in scorers:
score, scores = scorer.compute_score(ref, hypo)
if type(score) == list:
for m, s in zip(method, score):
final_scores[m] = s
else:
final_scores[method] = score
return final_scores
Example #2
| Source File: eval.py From unilm with MIT License | 6 votes |
|
def evaluate(self):
output = []
scorers = [
(Bleu(4), ["Bleu_1", "Bleu_2", "Bleu_3", "Bleu_4"]),
(Meteor(), "METEOR"),
(Rouge(), "ROUGE_L"),
# (Cider(), "CIDEr")
]
# =================================================
# Compute scores
# =================================================
for scorer, method in scorers:
# print 'computing %s score...'%(scorer.method())
score, scores = scorer.compute_score(self.gts, self.res)
if type(method) == list:
for sc, scs, m in zip(score, scores, method):
print("%s: %0.5f" % (m, sc))
output.append(sc)
else:
print("%s: %0.5f" % (method, score))
output.append(score)
return output
Example #3
| Source File: eval_on_unilm_tokenized_ref.py From unilm with MIT License | 6 votes |
|
def evaluate(self):
output = []
scorers = [
(Bleu(4), ["Bleu_1", "Bleu_2", "Bleu_3", "Bleu_4"]),
(Meteor(), "METEOR"),
(Rouge(), "ROUGE_L"),
# (Cider(), "CIDEr")
]
# =================================================
# Compute scores
# =================================================
for scorer, method in scorers:
# print 'computing %s score...'%(scorer.method())
score, scores = scorer.compute_score(self.gts, self.res)
if type(method) == list:
for sc, scs, m in zip(score, scores, method):
print("%s: %0.5f" % (m, sc))
output.append(sc)
else:
print("%s: %0.5f" % (method, score))
output.append(score)
return output
Example #4
| Source File: eval.py From NQG_ASs2s with MIT License | 6 votes |
|
def evaluate(self):
output = []
scorers = [
(Bleu(4), ["Bleu_1", "Bleu_2", "Bleu_3", "Bleu_4"]),
(Meteor(),"METEOR"),
(Rouge(), "ROUGE_L"),
# (Cider(), "CIDEr")
]
# =================================================
# Compute scores
# =================================================
for scorer, method in scorers:
# print 'computing %s score...'%(scorer.method())
score, scores = scorer.compute_score(self.gts, self.res)
if type(method) == list:
for sc, scs, m in zip(score, scores, method):
print "%s: %0.5f"%(m, sc)
output.append(sc)
else:
print "%s: %0.5f"%(method, score)
output.append(score)
return output
Example #5
| Source File: eval.py From neural-question-generation with MIT License | 6 votes |
|
def evaluate(self):
output = []
scorers = [
(Bleu(4), ["Bleu_1", "Bleu_2", "Bleu_3", "Bleu_4"]),
# (Meteor(),"METEOR"),
# (Rouge(), "ROUGE_L"),
# (Cider(), "CIDEr")
]
# =================================================
# Compute scores
# =================================================
for scorer, method in scorers:
# print 'computing %s score...'%(scorer.method())
score, scores = scorer.compute_score(self.gts, self.res)
if type(method) == list:
for sc, scs, m in zip(score, scores, method):
print "%s: %0.5f"%(m, sc)
output.append(sc)
else:
print "%s: %0.5f"%(method, score)
output.append(score)
return output
Example #6
| Source File: eval.py From Zeroshot-QuestionGeneration with MIT License | 5 votes |
|
def evaluate(self):
# imgIds = self.coco.getImgIds()
gts = dict(zip(range(0, len(self.predicted_list)), self.predicted_list))
res = dict(zip(range(0, len(self.label_list)), self.label_list))
# =================================================
# Set up scorers
# =================================================
print 'tokenization...'
tokenizer = PTBTokenizer()
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")
]
# =================================================
# 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.set_textid_to_eval(scs, gts.keys(), m)
print "%s: %0.3f"%(m, sc)
else:
self.setEval(score, method)
self.set_textid_to_eval(scores, gts.keys(), method)
print "%s: %0.3f"%(method, score)
self.set_eval()
Example #7
| Source File: eval.py From QG-Net with MIT License | 5 votes |
|
def evaluate(self):
output = []
scorers = [
(Bleu(4), ["Bleu_1", "Bleu_2", "Bleu_3", "Bleu_4"]),
(Meteor(),"METEOR"),
(Rouge(), "ROUGE_L"),
# (Cider(), "CIDEr")
]
# =================================================
# Compute scores
# =================================================
for scorer, method in scorers:
# print 'computing %s score...'%(scorer.method())
score, scores = scorer.compute_score(self.gts, self.res)
# set_trace()
if type(method) == list:
for sc, scs, m in zip(score, scores, method):
print "%s: %0.5f"%(m, sc)
output.append(sc)
else:
print "%s: %0.5f"%(method, score)
output.append(score)
return output
Example #8
| Source File: album_eval.py From AREL with MIT License | 5 votes |
|
def evaluate(self, album_to_Gts, album_to_Res):
self.album_to_Res = album_to_Res
self.album_to_Gts = album_to_Gts
# =================================================
# Set up scorers
# =================================================
print 'setting up scorers...'
scorers = []
scorers = [
(Bleu(4), ["Bleu_1", "Bleu_2", "Bleu_3", "Bleu_4"]),
(Meteor(), "METEOR"),
(Rouge(), "ROUGE_L"),
(Cider(), "CIDEr") # df='VIST/VIST-train-words'
]
# =================================================
# Compute scores
# =================================================
for scorer, method in scorers:
print 'computing %s score ...' % (scorer.method())
score, scores = scorer.compute_score(self.album_to_Gts, self.album_to_Res)
if type(method) == list:
for sc, scs, m in zip(score, scores, method):
self.setEval(sc, m)
self.setAlbumToEval(scs, self.album_to_Gts.keys(), m)
print '%s: %.3f' % (m, sc)
else:
self.setEval(score, method)
self.setAlbumToEval(scores, self.album_to_Gts.keys(), method)
print '%s: %.3f' % (method, score)
self.setEvalAlbums()
Example #9
| Source File: eval.py From image_captioning with MIT License | 4 votes |
|
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...'
tokenizer = PTBTokenizer()
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")
]
# =================================================
# 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, gts.keys(), m)
print "%s: %0.3f"%(m, sc)
else:
self.setEval(score, method)
self.setImgToEvalImgs(scores, gts.keys(), method)
print "%s: %0.3f"%(method, score)
self.setEvalImgs()
Example #10
| Source File: eval.py From CommonSenseMultiHopQA with MIT License | 4 votes |
|
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...'
tokenizer = PTBTokenizer()
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")
]
# =================================================
# 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, gts.keys(), m)
print "%s: %0.3f"%(m, sc)
else:
self.setEval(score, method)
self.setImgToEvalImgs(scores, gts.keys(), method)
print "%s: %0.3f"%(method, score)
self.setEvalImgs()
Example #11
| Source File: eval.py From neural-image-captioning with MIT License | 4 votes |
|
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...'
tokenizer = PTBTokenizer()
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")
]
# =================================================
# Compute scores
# =================================================
eval = {}
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, imgIds, m)
print "%s: %0.3f"%(m, sc)
else:
self.setEval(score, method)
self.setImgToEvalImgs(scores, imgIds, method)
print "%s: %0.3f"%(method, score)
self.setEvalImgs()
Example #12
| Source File: eval.py From captionGAN with MIT License | 4 votes |
|
def evaluate(self):
imgIds = self.params[self.imgidStr]
# 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...'
tokenizer = PTBTokenizer()
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"),
(Spice(), "SPICE")
]
# =================================================
# Compute scores
# =================================================
eval = {}
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, gts.keys(), m)
print "%s: %0.3f"%(m, sc)
else:
self.setEval(score, method)
self.setImgToEvalImgs(scores, gts.keys(), method)
print "%s: %0.3f"%(method, score)
self.setEvalImgs()
Example #13
| Source File: eval.py From deepQuest with BSD 3-Clause "New" or "Revised" License | 4 votes |
|
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...'
tokenizer = PTBTokenizer()
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")
]
# =================================================
# 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, gts.keys(), m)
print "%s: %0.3f" % (m, sc)
else:
self.setEval(score, method)
self.setImgToEvalImgs(scores, gts.keys(), method)
print "%s: %0.3f" % (method, score)
self.setEvalImgs()
Example #14
| Source File: eval.py From DialoGPT with MIT License | 4 votes |
|
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...')
tokenizer = PTBTokenizer()
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")
]
# =================================================
# 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, gts.keys(), m)
print("%s: %0.3f"%(m, sc))
else:
self.setEval(score, method)
self.setImgToEvalImgs(scores, gts.keys(), method)
print("%s: %0.3f"%(method, score))
self.setEvalImgs()
Example #15
| Source File: eval.py From TGIF-Release with BSD 3-Clause "New" or "Revised" License | 4 votes |
|
def main():
import sys
res_path = sys.argv[1]
gt_path = osp.join(this_dir, 'tgif-v1.0.tsv')
test_list_path = osp.join(this_dir, 'splits', 'test.txt')
test_keys = load_list(test_list_path)
all_sents = load_sentences(gt_path)
res = load_sentences(res_path)
# make sure res has and only has single sentence
# for all testing keys
gts = {}
for key in test_keys:
gts[key] = all_sents[key]
if key in res:
res[key] = [res[key][0]]
else:
res[key] = [""]
# =================================================
# Convert to COCO format
# =================================================
gts = to_coco(gts, res.keys())
res = to_coco(res, res.keys())
# =================================================
# Set up scorers
# =================================================
print 'tokenization...'
tokenizer = PTBTokenizer()
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")
]
# =================================================
# Compute scores
# =================================================
eval = {}
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):
print "%s: %0.3f"%(m, sc)
else:
print "%s: %0.3f"%(method, score)
Example #16
| Source File: eval.py From densecap-tensorflow with MIT License | 4 votes |
|
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...'
tokenizer = PTBTokenizer()
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")
]
# =================================================
# Compute scores
# =================================================
eval = {}
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, imgIds, m)
print "%s: %0.3f"%(m, sc)
else:
self.setEval(score, method)
self.setImgToEvalImgs(scores, imgIds, method)
print "%s: %0.3f"%(method, score)
self.setEvalImgs()
Example #17
| Source File: tester.py From deep-summarization with MIT License | 4 votes |
|
def main():
# Feed in the directory where the hypothesis summary and true summary is stored
hyp_file = glob.glob('metrics/hypothesis/*')
ref_file = glob.glob('metrics/reference/*')
BLEU_1 = 0.
BLEU_2 = 0.
BLEU_3 = 0.
BLEU_4 = 0.
ROUGE_L = 0.
num_files = 0
for reference_file, hypothesis_file in zip(ref_file, hyp_file):
num_files += 1
with open(reference_file) as rf:
reference = rf.readlines()
with open(hypothesis_file) as hf:
hypothesis = hf.readlines()
ref, hypo = load_textfiles(reference, hypothesis)
score_map = score(ref, hypo)
BLEU_1 += score_map['Bleu_1']
BLEU_2 += score_map['Bleu_2']
BLEU_3 += score_map['Bleu_3']
BLEU_4 += score_map['Bleu_4']
ROUGE_L += score_map['ROUGE_L']
BLEU_1 = BLEU_1/num_files
BLEU_2 = BLEU_2/num_files
BLEU_3 = BLEU_3/num_files
BLEU_4 = BLEU_4/num_files
ROUGE_L = ROUGE_L/num_files
print 'Average Metric Score for All Review Summary Pairs:'
print 'Bleu - 1gram:', BLEU_1
print 'Bleu - 2gram:', BLEU_2
print 'Bleu - 3gram:', BLEU_3
print 'Bleu - 4gram:', BLEU_4
print 'Rouge:', ROUGE_L
return BLEU_1,BLEU_2,BLEU_3, BLEU_4, ROUGE_L
