File size: 4,493 Bytes
e4b9a7b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 | # -*- coding: utf-8 -*-
# SPDX-FileCopyrightText: 2016-2025 PyThaiNLP Project
# SPDX-FileCopyrightText: Copyright 2019 Ponrawee Prasertsom
# SPDX-License-Identifier: Apache-2.0
"""
🪿 Han-solo: Thai syllable segmenter
GitHub: https://github.com/PyThaiNLP/Han-solo
"""
from typing import List
from pythainlp.corpus import path_pythainlp_corpus
try:
import pycrfsuite
except ImportError:
raise ImportError(
"ImportError; Install pycrfsuite by pip install python-crfsuite"
)
tagger = pycrfsuite.Tagger()
tagger.open(path_pythainlp_corpus("han_solo.crfsuite"))
class Featurizer:
# This class from ssg at https://github.com/ponrawee/ssg.
def __init__(self, N=2, sequence_size=1, delimiter=None):
self.N = N
self.delimiter = delimiter
self.radius = N + sequence_size
def pad(self, sentence, padder="#"):
return padder * (self.radius) + sentence + padder * (self.radius)
def featurize(
self, sentence, padding=True, indiv_char=True, return_type="list"
):
if padding:
sentence = self.pad(sentence)
all_features = []
all_labels = []
skip_next = False
for current_position in range(
self.radius, len(sentence) - self.radius + 1
):
if skip_next:
skip_next = False
continue
features = {}
if return_type == "list":
features = []
cut = 0
char = sentence[current_position]
if char == self.delimiter:
cut = 1
skip_next = True
counter = 0
chars_left = ""
chars_right = ""
chars = ""
abs_index_left = current_position # left start at -1
abs_index_right = current_position - 1 # right start at 0
while counter < self.radius:
abs_index_left -= (
1 # สมมุติตำแหน่งที่ 0 จะได้ -1, -2, -3, -4, -5 (radius = 5)
)
char_left = sentence[abs_index_left]
while char_left == self.delimiter:
abs_index_left -= 1
char_left = sentence[abs_index_left]
relative_index_left = -counter - 1
# เก็บตัวหนังสือ
chars_left = char_left + chars_left
# ใส่ลง feature
if indiv_char:
left_key = "|".join([str(relative_index_left), char_left])
if return_type == "dict":
features[left_key] = 1
else:
features.append(left_key)
abs_index_right += (
1 # สมมุติคือตำแหน่งที่ 0 จะได้ 0, 1, 2, 3, 4 (radius = 5)
)
char_right = sentence[abs_index_right]
while char_right == self.delimiter:
abs_index_right += 1
char_right = sentence[abs_index_right]
relative_index_right = counter
chars_right += char_right
if indiv_char:
right_key = "|".join(
[str(relative_index_right), char_right]
)
if return_type == "dict":
features[right_key] = 1
else:
features.append(right_key)
counter += 1
chars = chars_left + chars_right
for i in range(0, len(chars) - self.N + 1):
ngram = chars[i : i + self.N]
ngram_key = "|".join([str(i - self.radius), ngram])
if return_type == "dict":
features[ngram_key] = 1
else:
features.append(ngram_key)
all_features.append(features)
if return_type == "list":
cut = str(cut)
all_labels.append(cut)
return {"X": all_features, "Y": all_labels}
_to_feature = Featurizer()
def segment(text: str) -> List[str]:
x = _to_feature.featurize(text)["X"]
y_pred = tagger.tag(x)
list_cut = []
for j, k in zip(list(text), y_pred):
if k == "1":
list_cut.append(j)
else:
list_cut[-1] += j
return list_cut
|