胭脂

用于 ROUGE 指标的完整 Python 库（论文）。

免责声明

此实现独立于“官方”ROUGE 脚本（又名。ROUGE-155）。
结果可能略有不同，请参阅#2 中的讨论。

快速开始

克隆和安装

git clone https://github.com/pltrdy/rouge
cd rouge
python setup.py install
# or
pip install -U .

或从点子：

pip install rouge

从外壳使用它（JSON 输出）

$rouge -h
usage: rouge [-h] [-f] [-a] hypothesis reference

Rouge Metric Calculator

positional arguments:
  hypothesis  Text of file path
  reference   Text or file path

optional arguments:
  -h, --help  show this help message and exit
  -f, --file  File mode
  -a, --avg   Average mode

例如

# Single Sentence
rouge "transcript is a written version of each day 's cnn student" \
      "this page includes the show transcript use the transcript to help students with"

# Scoring using two files (line by line)
rouge -f ./tests/hyp.txt ./ref.txt

# Avg scoring - 2 files
rouge -f ./tests/hyp.txt ./ref.txt --avg

作为图书馆

给1句

from rouge import Rouge 

hypothesis = "the #### transcript is a written version of each day 's cnn student news program use this transcript to he    lp students with reading comprehension and vocabulary use the weekly newsquiz to test your knowledge of storie s you     saw on cnn student news"

reference = "this page includes the show transcript use the transcript to help students with reading comprehension and     vocabulary at the bottom of the page , comment for a chance to be mentioned on cnn student news . you must be a teac    her or a student age # # or older to request a mention on the cnn student news roll call . the weekly newsquiz tests     students ' knowledge of even ts in the news"

rouge = Rouge()
scores = rouge.get_scores(hypothesis, reference)

输出：

[
  {
    "rouge-1": {
      "f": 0.4786324739396596,
      "p": 0.6363636363636364,
      "r": 0.3835616438356164
    },
    "rouge-2": {
      "f": 0.2608695605353498,
      "p": 0.3488372093023256,
      "r": 0.20833333333333334
    },
    "rouge-l": {
      "f": 0.44705881864636676,
      "p": 0.5277777777777778,
      "r": 0.3877551020408163
    }
  }
]

注意：“f”代表f1_score，“p”代表精度，“r”代表召回。

给多个句子打分

import json
from rouge import Rouge

# Load some sentences
with open('./tests/data.json') as f:
  data = json.load(f)

hyps, refs = map(list, zip(*[[d['hyp'], d['ref']] for d in data]))
rouge = Rouge()
scores = rouge.get_scores(hyps, refs)
# or
scores = rouge.get_scores(hyps, refs, avg=True)

输出（avg=False）：字典列表n：

{"rouge-1": {"f": _, "p": _, "r": _}, "rouge-2" : { .. }, "rouge-l": { ... }}

输出（avg=True）：具有平均值的单个字典：

{"rouge-1": {"f": _, "p": _, "r": _}, "rouge-2" : { ..     }, "rouge-l": { ... }}

对两个文件进行评分（逐行）

给定两个具有相同行数 ( ) 的文件hyp_path，计算每一行的得分，或整个文件的平均值。ref_pathn

from rouge import FilesRouge

files_rouge = FilesRouge()
scores = files_rouge.get_scores(hyp_path, ref_path)
# or
scores = files_rouge.get_scores(hyp_path, ref_path, avg=True)