File size: 16,815 Bytes
7111e1a | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 | # bridge.py
# ============================================================
# BRIDGE β connects the three algorithms
#
# CRNN+CTC (Irish) β field dict from field_extractor.py
# MNB (Princess) β classifies form type
# spacyNER (Shane) β extracts + assembles fields
#
# DROP THIS FILE in the ROOT of your project:
#
# LCR-Document-Digitization-System/
# βββ CRNN+CTC/
# βββ MNB/
# βββ spacyNER/
# βββ bridge.py β HERE
# βββ pipeline.py
#
# NOTE: nationality = citizenship (same field, different label per form)
# The _get() helper handles both names automatically.
# ============================================================
import sys
import os
from pathlib import Path
# ββ Make all three algorithm folders importable ββββββββββββββ
_ROOT = Path(__file__).resolve().parent
for folder in ["CRNN+CTC", "MNB", "spacyNER"]:
p = str(_ROOT / folder)
if p not in sys.path:
sys.path.insert(0, p)
if str(_ROOT) not in sys.path:
sys.path.insert(0, str(_ROOT))
# ββ Imports ββββββββββββββββββββββββββββββββββββββββββββββββββ
from spacyNER.extractor import CivilRegistryNER
from spacyNER.autofill import AutoFillEngine
from MNB.classifier import MNBClassifier
# ββ Default paths ββββββββββββββββββββββββββββββββββββββββββββ
NER_MODEL_PATH = str(_ROOT / "spacyNER" / "models" / "civil_registry_model" / "model-best")
MNB_MODEL_DIR = str(_ROOT / "MNB" / "models")
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# HELPER β nationality/citizenship alias
# Tries multiple key names, returns first non-empty value.
# nationality = citizenship β same field, different label per form.
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
def _get(f: dict, *keys, default='') -> str:
for k in keys:
v = f.get(k, '')
if v and str(v).strip():
return str(v).strip()
return default
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# CRNN FIELD DICT β TEXT CONVERTERS
# Turns Irish's field dict into readable text that NER can read.
# Handles both old field names and new dynamic_field_extractor names.
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
def crnn_birth_to_text(f: dict) -> str:
"""Form 102 β Form 1A text.
Fields needed:
Registry Number, Date of Registration,
Name of Child, Sex, Date of Birth, Place of Birth,
Name of Mother, Nationality/Citizenship of Mother,
Name of Father, Nationality/Citizenship of Father,
Date of Marriage of Parents, Place of Marriage of Parents
"""
return (
f"Registry No.: {_get(f, 'registry_number', 'registry_no')}\n"
f"Date of Registration: {_get(f, 'date_of_registration')}\n"
f"1. NAME (First): {_get(f, 'child_first_name')} "
f"(Middle): {_get(f, 'child_middle_name')} "
f"(Last): {_get(f, 'child_last_name')}\n"
f"2. SEX: {_get(f, 'sex')}\n"
f"3. DATE OF BIRTH: {_get(f, 'dob_month')} {_get(f, 'dob_day')}, {_get(f, 'dob_year')}\n"
f"4. PLACE OF BIRTH: {_get(f, 'place_birth_hospital')} "
f"{_get(f, 'place_birth_city')} {_get(f, 'place_birth_province')}\n"
f"MOTHER:\n"
f"7. MAIDEN NAME (First): {_get(f, 'mother_first_name')} "
f"(Middle): {_get(f, 'mother_middle_name')} "
f"(Last): {_get(f, 'mother_last_name')}\n"
f"8. CITIZENSHIP/NATIONALITY: "
f"{_get(f, 'nationality_of_mother', 'mother_citizenship', 'mother_nationality')}\n"
f"FATHER:\n"
f"14. NAME (First): {_get(f, 'father_first_name')} "
f"(Middle): {_get(f, 'father_middle_name')} "
f"(Last): {_get(f, 'father_last_name')}\n"
f"15. CITIZENSHIP/NATIONALITY: "
f"{_get(f, 'nationality_of_father', 'father_citizenship', 'father_nationality')}\n"
f"MARRIAGE OF PARENTS:\n"
f"20a. DATE: {_get(f, 'parents_marriage_month')} "
f"{_get(f, 'parents_marriage_day')}, {_get(f, 'parents_marriage_year')}\n"
f"20b. PLACE: {_get(f, 'parents_marriage_city')} "
f"{_get(f, 'parents_marriage_province')}\n"
)
def crnn_death_to_text(f: dict) -> str:
"""Form 103 β Form 2A text.
Fields needed:
Registry Number, Date of Registration,
Name of Deceased, Sex, Age, Civil Status,
Nationality/Citizenship, Date of Death, Place of Death,
Cause of Death
"""
return (
f"Registry No.: {_get(f, 'registry_number', 'registry_no')}\n"
f"Date of Registration: {_get(f, 'date_of_registration')}\n"
f"1. NAME (First): {_get(f, 'deceased_first_name')} "
f"(Middle): {_get(f, 'deceased_middle_name')} "
f"(Last): {_get(f, 'deceased_last_name')}\n"
f"2. SEX: {_get(f, 'sex')}\n"
f"4. AGE: {_get(f, 'age', 'age_years')}\n"
f"9. CIVIL STATUS: {_get(f, 'civil_status')}\n"
f"7. CITIZENSHIP/NATIONALITY: {_get(f, 'nationality', 'citizenship')}\n"
f"6. DATE OF DEATH: {_get(f, 'dod_month')} {_get(f, 'dod_day')}, {_get(f, 'dod_year')}\n"
f"5. PLACE OF DEATH: {_get(f, 'place_death_hospital')} "
f"{_get(f, 'place_death_city')} {_get(f, 'place_death_province')}\n"
f"17. CAUSE OF DEATH: {_get(f, 'cause_of_death', 'cause_immediate')}\n"
f"Antecedent cause: {_get(f, 'cause_antecedent')}\n"
f"Underlying cause: {_get(f, 'cause_underlying')}\n"
)
def crnn_marriage_to_text(f: dict) -> str:
"""Form 97 β Form 3A text.
Fields needed (both husband and wife):
Name, Age, Nationality/Citizenship,
Name of Mother, Nationality/Citizenship of Mother,
Name of Father, Nationality/Citizenship of Father,
Registry Number, Date of Registration,
Date of Marriage, Place of Marriage
"""
return (
f"Registry No.: {_get(f, 'registry_number', 'registry_no')}\n"
f"Date of Registration: {_get(f, 'date_of_registration')}\n"
f"HUSBAND:\n"
f"1. NAME (First): {_get(f, 'husband_first_name')} "
f"(Middle): {_get(f, 'husband_middle_name')} "
f"(Last): {_get(f, 'husband_last_name')}\n"
f"2b. AGE: {_get(f, 'husband_age')}\n"
f"4b. CITIZENSHIP/NATIONALITY: "
f"{_get(f, 'husband_nationality', 'husband_citizenship')}\n"
f"8. NAME OF FATHER (First): {_get(f, 'husband_father_first')} "
f"(Middle): {_get(f, 'husband_father_middle')} "
f"(Last): {_get(f, 'husband_father_last')}\n"
f"8b. FATHER CITIZENSHIP/NATIONALITY: "
f"{_get(f, 'husband_father_nationality', 'husband_father_citizenship')}\n"
f"10. NAME OF MOTHER (First): {_get(f, 'husband_mother_first')} "
f"(Middle): {_get(f, 'husband_mother_middle')} "
f"(Last): {_get(f, 'husband_mother_last')}\n"
f"10b. MOTHER CITIZENSHIP/NATIONALITY: "
f"{_get(f, 'husband_mother_nationality', 'husband_mother_citizenship')}\n"
f"WIFE:\n"
f"1. NAME (First): {_get(f, 'wife_first_name')} "
f"(Middle): {_get(f, 'wife_middle_name')} "
f"(Last): {_get(f, 'wife_last_name')}\n"
f"2b. AGE: {_get(f, 'wife_age')}\n"
f"4b. CITIZENSHIP/NATIONALITY: "
f"{_get(f, 'wife_nationality', 'wife_citizenship')}\n"
f"8. NAME OF FATHER (First): {_get(f, 'wife_father_first')} "
f"(Middle): {_get(f, 'wife_father_middle')} "
f"(Last): {_get(f, 'wife_father_last')}\n"
f"8b. FATHER CITIZENSHIP/NATIONALITY: "
f"{_get(f, 'wife_father_nationality', 'wife_father_citizenship')}\n"
f"10. NAME OF MOTHER (First): {_get(f, 'wife_mother_first')} "
f"(Middle): {_get(f, 'wife_mother_middle')} "
f"(Last): {_get(f, 'wife_mother_last')}\n"
f"10b. MOTHER CITIZENSHIP/NATIONALITY: "
f"{_get(f, 'wife_mother_nationality', 'wife_mother_citizenship')}\n"
f"15. PLACE OF MARRIAGE: "
f"{_get(f, 'place_marriage_city')} {_get(f, 'place_marriage_province')}\n"
f"16. DATE OF MARRIAGE: {_get(f, 'date_marriage_month')} "
f"{_get(f, 'date_marriage_day')}, {_get(f, 'date_marriage_year')}\n"
)
def crnn_birth_to_form90_text(f: dict, role: str = 'groom') -> str:
"""Birth cert of groom or bride β Form 90 text.
Fields needed:
Name, Date of Birth, Place of Birth, Sex,
Citizenship/Nationality,
Name of Father, Citizenship of Father,
Name of Mother, Citizenship of Mother
role: 'groom' or 'bride'
"""
return (
f"{role.upper()}:\n"
f"1. NAME (First): {_get(f, 'first_name', 'child_first_name')} "
f"(Middle): {_get(f, 'middle_name', 'child_middle_name')} "
f"(Last): {_get(f, 'last_name', 'child_last_name')}\n"
f"2. DATE OF BIRTH: {_get(f, 'dob_month')} {_get(f, 'dob_day')}, {_get(f, 'dob_year')}\n"
f"3. PLACE OF BIRTH: {_get(f, 'place_birth_hospital')} "
f"{_get(f, 'place_birth_city')} {_get(f, 'place_birth_province')}\n"
f"4. SEX: {_get(f, 'sex')}\n"
f"5. CITIZENSHIP/NATIONALITY: "
f"{_get(f, 'citizenship', 'nationality', 'nationality_of_mother', 'mother_citizenship')}\n"
f"NAME OF FATHER (First): {_get(f, 'father_first_name')} "
f"(Middle): {_get(f, 'father_middle_name')} "
f"(Last): {_get(f, 'father_last_name')}\n"
f"FATHER CITIZENSHIP/NATIONALITY: "
f"{_get(f, 'father_citizenship', 'father_nationality')}\n"
f"NAME OF MOTHER (First): {_get(f, 'mother_first_name')} "
f"(Middle): {_get(f, 'mother_middle_name')} "
f"(Last): {_get(f, 'mother_last_name')}\n"
f"MOTHER CITIZENSHIP/NATIONALITY: "
f"{_get(f, 'mother_citizenship', 'mother_nationality')}\n"
)
# ββ Auto-detect form type from CRNN field keys βββββββββββββββ
_BIRTH_KEYS = {'child_first_name', 'mother_first_name', 'dob_day',
'registry_number', 'nationality_of_mother'}
_DEATH_KEYS = {'deceased_first_name', 'cause_of_death', 'dod_day',
'cause_immediate', 'nationality'}
_MARRIAGE_KEYS = {'husband_first_name', 'wife_first_name', 'date_marriage_day',
'husband_nationality', 'wife_nationality'}
_CONVERTERS = {
'birth': crnn_birth_to_text,
'death': crnn_death_to_text,
'marriage': crnn_marriage_to_text,
}
def _detect_form_type(fields: dict) -> str:
keys = set(fields.keys())
if keys & _BIRTH_KEYS: return 'birth'
if keys & _DEATH_KEYS: return 'death'
if keys & _MARRIAGE_KEYS: return 'marriage'
return 'birth'
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# BRIDGE CLASS
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
class CivilRegistryBridge:
"""
The single connection point between the three algorithms.
Usage:
from bridge import CivilRegistryBridge
bridge = CivilRegistryBridge()
# Path A β birth / death / marriage cert
form = bridge.process(crnn_fields, form_hint="birth")
print(form.to_dict())
# Path B β Form 90 (two birth certs)
form90 = bridge.process_marriage_license(
groom_crnn_fields,
bride_crnn_fields
)
"""
def __init__(self,
ner_model_path: str = NER_MODEL_PATH,
mnb_model_dir: str = MNB_MODEL_DIR):
# Princess's MNB classifier
self.mnb = MNBClassifier(model_dir=mnb_model_dir)
# Shane's NER extractor
self.extractor = CivilRegistryNER(model_path=ner_model_path)
self.filler = AutoFillEngine(self.extractor)
# ββ Path A β single cert (birth / death / marriage) ββββββ
def process(self, crnn_fields: dict, form_hint: str = None):
"""
Parameters
----------
crnn_fields : dict
Output from Irish's run_crnn_ocr() / dynamic_field_extractor
form_hint : str, optional
'birth' | 'death' | 'marriage'
Auto-detected from field keys if not given.
Returns
-------
Form1A | Form2A | Form3A with all fields populated
"""
form_type = form_hint or _detect_form_type(crnn_fields)
ocr_text = _CONVERTERS.get(form_type, crnn_birth_to_text)(crnn_fields)
mnb_label = self.mnb.classify_form_type(ocr_text)
print(f" [Bridge] hint={form_type!r} MNB={mnb_label} NERβrunning...")
# Use MNB classification result to pick the correct form filler
if mnb_label == 'form2a':
return self.filler.fill_form_2a(ocr_text)
elif mnb_label == 'form3a':
return self.filler.fill_form_3a(ocr_text)
elif mnb_label == 'form90':
return self.filler.fill_form_90(ocr_text, ocr_text)
else:
return self.filler.fill_form_1a(ocr_text)
# ββ Path B β Form 90 (two birth certs) βββββββββββββββββββ
def process_marriage_license(self,
groom_crnn_fields: dict,
bride_crnn_fields: dict):
"""
Parameters
----------
groom_crnn_fields : dict CRNN output for groom's birth cert
bride_crnn_fields : dict CRNN output for bride's birth cert
Returns
-------
Form90 with groom.* and bride.* fields populated
"""
groom_text = crnn_birth_to_form90_text(groom_crnn_fields, role='groom')
bride_text = crnn_birth_to_form90_text(bride_crnn_fields, role='bride')
groom_sex = self.mnb.classify_sex(groom_text)
bride_sex = self.mnb.classify_sex(bride_text)
print(f" [Bridge] Form90 groom_sex={groom_sex} bride_sex={bride_sex}")
return self.filler.fill_form_90(groom_text, bride_text)
# ββ Quick test β run: python bridge.py βββββββββββββββββββββββ
if __name__ == "__main__":
SAMPLE_BIRTH = {
"registry_number": "2024-001",
"date_of_registration": "June 12, 1998",
"child_first_name": "TASLIAH",
"child_middle_name": "ABOBACAR",
"child_last_name": "GOMONSANG",
"sex": "FEMALE",
"dob_day": "12",
"dob_month": "JUNE",
"dob_year": "1998",
"place_birth_hospital": "CAMP JAS BLISS",
"place_birth_city": "MALABANG",
"place_birth_province": "LANAO DEL SUR",
"mother_first_name": "H. ASLIAH",
"mother_middle_name": "SANTICAN",
"mother_last_name": "ABOBACAR",
"nationality_of_mother": "FILIPINO", # nationality = citizenship
"father_first_name": "H. NAEEF",
"father_middle_name": "MUDAG",
"father_last_name": "GOMONSANG",
"nationality_of_father": "FILIPINO", # nationality = citizenship
"parents_marriage_month": "JANUARY",
"parents_marriage_day": "5",
"parents_marriage_year": "1990",
"parents_marriage_city": "CAMP JAS BLISS MALABANG",
"parents_marriage_province": "LANAO DEL SUR",
}
print("=" * 55)
print(" BRIDGE TEST")
print("=" * 55)
bridge = CivilRegistryBridge()
form = bridge.process(SAMPLE_BIRTH, form_hint="birth")
print(f"\n name_of_child β {form.name_of_child!r}")
print(f" name_of_mother β {form.name_of_mother!r}")
print(f" name_of_father β {form.name_of_father!r}")
print(f" date_of_birth β {form.date_of_birth!r}")
print("\n Full result:")
for k, v in form.to_dict().items():
if v:
print(f" {k:<35} {v}")
|