{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "7b051011",
   "metadata": {},
   "outputs": [],
   "source": [
    "from presidio_analyzer import AnalyzerEngine\n",
    "from presidio_analyzer.nlp_engine import TransformersNlpEngine\n",
    "from presidio_anonymizer import AnonymizerEngine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a4739691",
   "metadata": {},
   "outputs": [],
   "source": [
    "text = \"私は田中太郎。住所は279-0031 千葉県浦安市舞浜1−1。電話番号は03-999-9999。マイナンバーは123456789012。\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b3bfd6d5",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Some weights of the model checkpoint at H:\\BERT_Models\\dslim\\bert-base-NER were not used when initializing BertForTokenClassification: ['bert.pooler.dense.bias', 'bert.pooler.dense.weight']\n",
      "- This IS expected if you are initializing BertForTokenClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
      "- This IS NOT expected if you are initializing BertForTokenClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
      "Device set to use cpu\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[type: PHONE_NUMBER, start: 36, end: 47, score: 0.4]\n",
      "text: 私は田中太郎。住所は279-0031 千葉県浦安市舞浜１−１。電話番号は<PHONE_NUMBER>。マイナンバーは123456789012。\n",
      "items:\n",
      "[\n",
      "    {'start': 36, 'end': 50, 'entity_type': 'PHONE_NUMBER', 'text': '<PHONE_NUMBER>', 'operator': 'replace'}\n",
      "]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "model_config = [{\"lang_code\": \"en\", \"model_name\": {\n",
    "    \"spacy\": \"en_core_web_sm\",  # use a small spaCy model for lemmas, tokens etc.\n",
    "    \"transformers\": r\"H:\\BERT_Models\\dslim\\bert-base-NER\"\n",
    "    }\n",
    "}]\n",
    "\n",
    "nlp_engine = TransformersNlpEngine(models=model_config)\n",
    "analyzer = AnalyzerEngine(nlp_engine=nlp_engine)\n",
    "\n",
    "results = analyzer.analyze(text=text, language='en')\n",
    "print(results)\n",
    "\n",
    "anonymizer = AnonymizerEngine()\n",
    "anonymized_text = anonymizer.anonymize(text=text, analyzer_results=results)\n",
    "\n",
    "print(anonymized_text)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "42e143ce",
   "metadata": {},
   "source": [
    "NERモデルを日本語対応のものに変えてみる"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "7a0e34a9",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Device set to use cpu\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[type: LOCATION, start: 19, end: 21, score: 0.9985260963439941]\n",
      "text: 私は田中太郎。住所は279-0031 <LOCATION>県浦安市舞浜１−１。電話番号は03-999-9999。マイナンバーは123456789012。\n",
      "items:\n",
      "[\n",
      "    {'start': 19, 'end': 29, 'entity_type': 'LOCATION', 'text': '<LOCATION>', 'operator': 'replace'}\n",
      "]\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\ProgramData\\anaconda3\\envs\\presidio_20260831\\Lib\\site-packages\\transformers\\pipelines\\token_classification.py:490: UserWarning: Tokenizer does not support real words, using fallback heuristic\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "model_config = [{\"lang_code\": \"ja\", \"model_name\": {\n",
    "    \"spacy\": \"ja_core_news_sm\",  # use a small spaCy model for lemmas, tokens etc.\n",
    "    \"transformers\": r\"H:\\BERT_Models\\tsmatz\\xlm-roberta-ner-japanese\"\n",
    "    }\n",
    "}]\n",
    "\n",
    "nlp_engine = TransformersNlpEngine(models=model_config)\n",
    "analyzer = AnalyzerEngine(nlp_engine=nlp_engine)\n",
    "\n",
    "results = analyzer.analyze(text=text, language='ja')\n",
    "print(results)\n",
    "\n",
    "anonymizer = AnonymizerEngine()\n",
    "anonymized_text = anonymizer.anonymize(text=text, analyzer_results=results)\n",
    "\n",
    "print(anonymized_text)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3830ac01",
   "metadata": {},
   "source": [
    "ginza+日本語対応NERモデル"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f6fe9f22",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Device set to use cpu\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[type: LOCATION, start: 19, end: 27, score: 0.9985260963439941]\n",
      "text: 私は田中太郎。住所は279-0031 <LOCATION>１−１。電話番号は03-999-9999。マイナンバーは123456789012。\n",
      "items:\n",
      "[\n",
      "    {'start': 19, 'end': 29, 'entity_type': 'LOCATION', 'text': '<LOCATION>', 'operator': 'replace'}\n",
      "]\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\ProgramData\\anaconda3\\envs\\presidio_20260831\\Lib\\site-packages\\transformers\\pipelines\\token_classification.py:490: UserWarning: Tokenizer does not support real words, using fallback heuristic\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "import spacy\n",
    "import ginza  # ← spacy.load の前に必須(compound_splitter等のfactory登録のため)\n",
    "\n",
    "# GiNZAのcompound_splitterはsplit_mode未指定だとエラーになるため、\n",
    "# spacy.load を一時的にラップしてconfigを注入する\n",
    "_original_spacy_load = spacy.load\n",
    "\n",
    "def _patched_spacy_load(name, *args, **kwargs):\n",
    "    if name == \"ja_ginza\" and \"config\" not in kwargs:\n",
    "        kwargs[\"config\"] = {\"components\": {\"compound_splitter\": {\"split_mode\": \"A\"}}}\n",
    "    return _original_spacy_load(name, *args, **kwargs)\n",
    "\n",
    "spacy.load = _patched_spacy_load\n",
    "\n",
    "\n",
    "from presidio_analyzer import AnalyzerEngine\n",
    "from presidio_analyzer.nlp_engine import TransformersNlpEngine\n",
    "from presidio_anonymizer import AnonymizerEngine\n",
    "\n",
    "model_config = [{\"lang_code\": \"ja\", \"model_name\": {\n",
    "    \"spacy\": \"ja_ginza\",  # ← ja_core_news_sm から変更\n",
    "    \"transformers\": r\"H:\\BERT_Models\\tsmatz\\xlm-roberta-ner-japanese\"\n",
    "    }\n",
    "}]\n",
    "\n",
    "nlp_engine = TransformersNlpEngine(models=model_config)\n",
    "analyzer = AnalyzerEngine(nlp_engine=nlp_engine)\n",
    "\n",
    "results = analyzer.analyze(text=text, language='ja')\n",
    "print(results)\n",
    "\n",
    "anonymizer = AnonymizerEngine()\n",
    "anonymized_text = anonymizer.anonymize(text=text, analyzer_results=results)\n",
    "\n",
    "print(anonymized_text)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "add0b200",
   "metadata": {},
   "source": [
    "カスタムパターンを追加"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "283124a1",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Device set to use cpu\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[type: PERSON, start: 2, end: 6, score: 0.999563992023468, type: LOCATION, start: 10, end: 30, score: 0.998464047908783, type: JP_POSTAL_CODE, start: 39, end: 47, score: 0.85, type: JP_MY_NUMBER, start: 55, end: 67, score: 0.6499999999999999, type: PHONE_NUMBER, start: 36, end: 47, score: 0.4]\n",
      "text: 私は<PERSON>。住所は<LOCATION>。電話番号は<PHONE_NUMBER>。マイナンバーは<JP_MY_NUMBER>。\n",
      "items:\n",
      "[\n",
      "    {'start': 52, 'end': 66, 'entity_type': 'JP_MY_NUMBER', 'text': '<JP_MY_NUMBER>', 'operator': 'replace'},\n",
      "    {'start': 30, 'end': 44, 'entity_type': 'PHONE_NUMBER', 'text': '<PHONE_NUMBER>', 'operator': 'replace'},\n",
      "    {'start': 14, 'end': 24, 'entity_type': 'LOCATION', 'text': '<LOCATION>', 'operator': 'replace'},\n",
      "    {'start': 2, 'end': 10, 'entity_type': 'PERSON', 'text': '<PERSON>', 'operator': 'replace'}\n",
      "]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import spacy\n",
    "import ginza\n",
    "\n",
    "if not getattr(spacy.load, \"_ja_ginza_patched\", False):\n",
    "    _original_spacy_load = spacy.load\n",
    "\n",
    "    def _make_patched_load(original_load):\n",
    "        def _patched(name, *args, **kwargs):\n",
    "            if name == \"ja_ginza\":\n",
    "                # \"disable\" は生成はするが実行しないだけなので、\n",
    "                # compound_splitter の split_mode 検証エラーを避けられない。\n",
    "                # \"exclude\" ならコンポーネント自体を生成しないため、この問題を回避できる。\n",
    "                exclude = list(kwargs.get(\"exclude\", []))\n",
    "                for comp in (\"compound_splitter\", \"bunsetu_recognizer\"):\n",
    "                    if comp not in exclude:\n",
    "                        exclude.append(comp)\n",
    "                kwargs[\"exclude\"] = exclude\n",
    "                kwargs.pop(\"config\", None)\n",
    "            return original_load(name, *args, **kwargs)\n",
    "        _patched._ja_ginza_patched = True\n",
    "        return _patched\n",
    "\n",
    "    spacy.load = _make_patched_load(_original_spacy_load)\n",
    "\n",
    "from presidio_analyzer import AnalyzerEngine, Pattern, PatternRecognizer, RecognizerRegistry\n",
    "from presidio_analyzer.nlp_engine import TransformersNlpEngine, NerModelConfiguration\n",
    "from presidio_anonymizer import AnonymizerEngine\n",
    "\n",
    "\n",
    "# ============================================================\n",
    "# NLPエンジン設定(GiNZA + xlm-roberta-ner-japanese)\n",
    "# ============================================================\n",
    "model_config = [{\"lang_code\": \"ja\", \"model_name\": {\n",
    "    \"spacy\": \"ja_ginza\",\n",
    "    \"transformers\": r\"H:\\BERT_Models\\tsmatz\\xlm-roberta-ner-japanese\"\n",
    "    }\n",
    "}]\n",
    "\n",
    "ner_model_configuration = NerModelConfiguration(\n",
    "    model_to_presidio_entity_mapping={\n",
    "        \"PER\": \"PERSON\",\n",
    "        \"PERSON\": \"PERSON\",\n",
    "        \"LOC\": \"LOCATION\",\n",
    "        \"GPE\": \"LOCATION\",\n",
    "        \"ORG\": \"ORGANIZATION\",\n",
    "        \"DAT\": \"DATE_TIME\",\n",
    "        \"DATE\": \"DATE_TIME\",\n",
    "        \"TIM\": \"DATE_TIME\",\n",
    "        \"TIME\": \"DATE_TIME\",\n",
    "        \"MONEY\": \"MONEY\",\n",
    "        \"PERCENT\": \"PERCENT\",\n",
    "    },\n",
    "    low_confidence_score_multiplier=0.4,\n",
    "    low_score_entity_names=[\"ORGANIZATION\"],\n",
    "    alignment_mode=\"expand\",\n",
    "    aggregation_strategy=\"simple\",  # 日本語(スペース無し)では\"average\"等だと、空白ベースのフォールバック判定が誤動作するため\"simple\"を使う\n",
    ")\n",
    "\n",
    "nlp_engine = TransformersNlpEngine(\n",
    "    models=model_config,\n",
    "    ner_model_configuration=ner_model_configuration,\n",
    ")\n",
    "nlp_engine.load()\n",
    "\n",
    "\n",
    "# ============================================================\n",
    "# カスタムレコグナイザー: 郵便番号・マイナンバー\n",
    "# ============================================================\n",
    "postal_recognizer = PatternRecognizer(\n",
    "    supported_entity=\"JP_POSTAL_CODE\",\n",
    "    patterns=[Pattern(name=\"jp_postal_code\", regex=r\"\\b\\d{3}-\\d{4}\\b\", score=0.85)],\n",
    "    context=[\"郵便番号\", \"〒\"],\n",
    "    supported_language=\"ja\",\n",
    ")\n",
    "\n",
    "my_number_recognizer = PatternRecognizer(\n",
    "    supported_entity=\"JP_MY_NUMBER\",\n",
    "    patterns=[Pattern(name=\"jp_my_number\", regex=r\"(?<!\\d)\\d{12}(?!\\d)\", score=0.3)],\n",
    "    context=[\"マイナンバー\", \"個人番号\"],\n",
    "    supported_language=\"ja\",\n",
    ")\n",
    "\n",
    "\n",
    "# ============================================================\n",
    "# レジストリ構築(既定 + カスタムを統合)\n",
    "# ============================================================\n",
    "registry = RecognizerRegistry(supported_languages=[\"ja\"])\n",
    "registry.load_predefined_recognizers(nlp_engine=nlp_engine, languages=[\"ja\"])\n",
    "registry.add_recognizer(postal_recognizer)\n",
    "registry.add_recognizer(my_number_recognizer)\n",
    "\n",
    "analyzer = AnalyzerEngine(\n",
    "    nlp_engine=nlp_engine,\n",
    "    registry=registry,\n",
    "    supported_languages=[\"ja\"],\n",
    ")\n",
    "\n",
    "\n",
    "# ============================================================\n",
    "# 実行\n",
    "# ============================================================\n",
    "results = analyzer.analyze(text=text, language='ja')\n",
    "print(results)\n",
    "\n",
    "anonymizer = AnonymizerEngine()\n",
    "anonymized_text = anonymizer.anonymize(text=text, analyzer_results=results)\n",
    "\n",
    "print(anonymized_text)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e854bd55",
   "metadata": {},
   "source": [
    "# 画像のマスク"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1432e9cf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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B3fjXxPrKeJNL8IeFzBHq9/G1xNdTpvW1gXPzbe5JBAz6e+RS03X/ABR4W8baf4c8WX9vqlpqyP8AYdRitxAyyryY3Ucc5GPqPfEWn/P+0hqvmclNBURZ9PMjzj8SaPi18us+AnT/AFw8QQBfXBIz/SgDr/FX/CVtZRp4U/spbliRK+ol8IMcFQoOT9eKwfhB4j1bxT4GGo61dfabv7VJH5gjVPlGMDCgDvXe15d8Af8Akmg/6/pv6UAa+rRfELWtevLbS7uz8PaVbELDdPCtzLdHGchTwq9uefr2h8FeKddbxZqng7xQbabU7KFbmG8tl2LcQkgZK9iCy9Pf0ye8nnitoJJ55FjhjUu7ucBVAyST2FeZfDxZfFXjzX/HxjePT5kGnabvGDJEpG58ehKj8yO1AHqNFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFef8AhL/kr3xF/wC4Z/6TtXoFef8AhL/kr3xF/wC4Z/6TtQB6BRRRQAUUUUAef+Lf+SvfDr/uJ/8ApOtegV5/4t/5K98Ov+4n/wCk616BQAUUUUAFY/ibwzpni3Q59J1WASQSDKsPvRN2dT2I/wDrHg1sUUAeXfDa91bwxq83w81q1Z/scRn0+/hhxHNBn+LHAOT1PfIPOCfUaMc570UAFeZ/EgE/EH4dEKxA1CUkgdP9XXplFABTJZFhheVgxVFLEIpYkD0A5J9hT6KAPH4xqPxe8VWdzNYT2Pg3SLjzUW5Ta99OpwPl7KOR9MjqePYKKKACvPte8YeNV1q60jw74IlmeJtq6heTBbdgRkMOm4c9A2R0xmvQaKAPMdP+GWpa9qMOrfEPVxq00R3Q6ZANtpCfccbvyGe+6vTERI41jjVVRQAqqMAAdgKdRQB518S9M1zxXf6R4Ts7SePRruQT6nfj7ojQ5Ef1OM899vvXoMEEVrbxW8EaxwxIERFGAqgYAH4VJRQBh+MtDXxJ4O1bSCoZrm2ZY89pByh/BgDVH4btqv8Awr/R4tbtJrW/gh8l45hhsKdqk/VQvXnNdVRQAUUUUAFeRfHfT7q8tPDLWkhikk1E2XmD+Hz0K/yBr12kIBxkA45GaAPK/iLaWum6r4W/tXT7m68GWSPHcQwRtIkcgUCJpFXkqMcfj64PKTaL4c+IPj7SU8D2k2l6fZQzSXmq2FqbULIVxEFyByGHtkE+lfQFFAHL+FP+Eo03QLuLxSYr25s3cQT2oy93EFBDFezHkY9vxPmXi3xPqev+LvCWr23gbxbHBo1xJLOsmmMGcNsxtxkZ+U9cV7rRQBzEHjCa48IXmvJ4a1yOWAsqadPalLmUjGNqDJwSevsfSvKNA17Vj4pm8V+KvBPi2+1cZjsoYNLbyLKL0Tccljk8kevrXv1FAHJWviTWvEPhPUL3RtCu9N1WJjHb22twmHzCApzgdsEgH1FYT/EfxQtobX/hXOt/2xt2gBQbXf6+aONuf/1969KooA898A/Di20nwTFpviawsdQu5bl72WKeFJUhkcAYXII6KMkd81j/ABa8BaWPA7/8I74Utf7Q+0xY/s/T183bn5vuLnHrXrVFAHMazZ6j4c8OhfA+iaZ5sc4keyCiBZE/j27cAOcDk/r0rkNc8Y+K/Eui3OhaP4F1iyv72M28lzfqI4IFYYZg/wDFxnHT8eh9WooA821b4ZyH4Uaf4Z025UalpTJdWk7cKbhSWJ9gSzgemR6Vm654k8X+LfDM/hiDwVqdjqt7H9murq5AW0iU8OyyZ+bjOAPXv39booAz9C0qPQvD+n6TE29LO3jgDkY3bVAz+OM1w/wq02/ttR8ZX+o2N1ayX2sySR/aIWjLx5JUjcOV+Y4PSvSKKAPP/HGka1aeLdE8ZaJYnU20+OS3urFXCu8Tj7yZ4yMnjqeKwvF91rXxP0uHw1p/hXV9Mt5p0e7vtWgWFYUU5OwZJY/T+uR67RQBzXinXNY8Ow2U2meHrjWbXJW6FtJ++jGPlKpj5+etcfJFrvxN8R6Q19oN5ovhvSrgXjpqC7JrqZfuLs7KOc+xPtXqtFAHnPjXSNY0nxrpfjnQtPk1JoIGstQsoTiSSEkkMg7kE9PYe+KdvDrPxC8e6PrF7od9o+haHumij1BPLmuJ2xg7OwXAOfb349SooA5nxP4wfw1dQQp4b17VvNQv5mmWfnKnOMMcjBrzv4P6zqXhzRbXw3qPhDxLFNPeMxum09lgjDkYLM2MAY54r2qigDxL4ja7r+v+IT4fbwz4mHhe3lxdyafYO8l8VP3VbgCPPcE56+grsfC3jUXV5YaFbeBvEmk2gXy45bqwMUEKqpIBOeOmPqRXeUUAeVy2vhrVtZ8UT+Mr4RX9ldMtuJrtoTa2wRTG8IBGCck7hkk8V2vgi51C88EaPcaoZDeyWqtI0gwzejMPUjBPua0rzRtL1G4iuL7TbO5nh/1Uk8Cuyf7pIyPwq7QAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABXn/hL/kr3xF/7hn/pO1egV5/4S/5K98Rf+4Z/6TtQB6BRRRQAUUUUAeb+O7+z0z4pfD28v7uC0tY/7S3zTyCNFzAoGWPAySB+NdR/wnfg/wD6GvQ//BjD/wDFVoanoWj635X9raVY3/k58v7XbpLszjONwOM4HT0FZ/8Awgng/wD6FTQ//BdD/wDE0AH/AAnfg/8A6GvQ/wDwYw//ABVH/Cd+D/8Aoa9D/wDBjD/8VR/wgng//oVND/8ABdD/APE0f8IJ4P8A+hU0P/wXQ/8AxNAB/wAJ34P/AOhr0P8A8GMP/wAVR/wnfg//AKGvQ/8AwYw//FUf8IJ4P/6FTQ//AAXQ/wDxNH/CCeD/APoVND/8F0P/AMTQAf8ACd+D/wDoa9D/APBjD/8AFUf8J34P/wChr0P/AMGMP/xVH/CCeD/+hU0P/wAF0P8A8TR/wgng/wD6FTQ//BdD/wDE0AH/AAnfg/8A6GvQ/wDwYw//ABVH/Cd+D/8Aoa9D/wDBjD/8VR/wgng//oVND/8ABdD/APE0f8IJ4P8A+hU0P/wXQ/8AxNAB/wAJ34P/AOhr0P8A8GMP/wAVR/wnfg//AKGvQ/8AwYw//FUf8IJ4P/6FTQ//AAXQ/wDxNH/CCeD/APoVND/8F0P/AMTQAf8ACd+D/wDoa9D/APBjD/8AFUf8J34P/wChr0P/AMGMP/xVH/CCeD/+hU0P/wAF0P8A8TR/wgng/wD6FTQ//BdD/wDE0AH/AAnfg/8A6GvQ/wDwYw//ABVH/Cd+D/8Aoa9D/wDBjD/8VR/wgng//oVND/8ABdD/APE0f8IJ4P8A+hU0P/wXQ/8AxNAB/wAJ34P/AOhr0P8A8GMP/wAVR/wnfg//AKGvQ/8AwYw//FUf8IJ4P/6FTQ//AAXQ/wDxNH/CCeD/APoVND/8F0P/AMTQAf8ACd+D/wDoa9D/APBjD/8AFUf8J34P/wChr0P/AMGMP/xVH/CCeD/+hU0P/wAF0P8A8TR/wgng/wD6FTQ//BdD/wDE0AH/AAnfg/8A6GvQ/wDwYw//ABVH/Cd+D/8Aoa9D/wDBjD/8VR/wgng//oVND/8ABdD/APE0f8IJ4P8A+hU0P/wXQ/8AxNAB/wAJ34P/AOhr0P8A8GMP/wAVR/wnfg//AKGvQ/8AwYw//FUf8IJ4P/6FTQ//AAXQ/wDxNH/CCeD/APoVND/8F0P/AMTQAf8ACd+D/wDoa9D/APBjD/8AFUf8J34P/wChr0P/AMGMP/xVH/CCeD/+hU0P/wAF0P8A8TR/wgng/wD6FTQ//BdD/wDE0AH/AAnfg/8A6GvQ/wDwYw//ABVH/Cd+D/8Aoa9D/wDBjD/8VR/wgng//oVND/8ABdD/APE0f8IJ4P8A+hU0P/wXQ/8AxNAB/wAJ34P/AOhr0P8A8GMP/wAVR/wnfg//AKGvQ/8AwYw//FUf8IJ4P/6FTQ//AAXQ/wDxNH/CCeD/APoVND/8F0P/AMTQAf8ACd+D/wDoa9D/APBjD/8AFUf8J34P/wChr0P/AMGMP/xVH/CCeD/+hU0P/wAF0P8A8TR/wgng/wD6FTQ//BdD/wDE0AH/AAnfg/8A6GvQ/wDwYw//ABVH/Cd+D/8Aoa9D/wDBjD/8VR/wgng//oVND/8ABdD/APE0f8IJ4P8A+hU0P/wXQ/8AxNAB/wAJ34P/AOhr0P8A8GMP/wAVR/wnfg//AKGvQ/8AwYw//FUf8IJ4P/6FTQ//AAXQ/wDxNH/CCeD/APoVND/8F0P/AMTQAf8ACd+D/wDoa9D/APBjD/8AFUf8J34P/wChr0P/AMGMP/xVH/CCeD/+hU0P/wAF0P8A8TR/wgng/wD6FTQ//BdD/wDE0AH/AAnfg/8A6GvQ/wDwYw//ABVH/Cd+D/8Aoa9D/wDBjD/8VR/wgng//oVND/8ABdD/APE0f8IJ4P8A+hU0P/wXQ/8AxNAB/wAJ34P/AOhr0P8A8GMP/wAVR/wnfg//AKGvQ/8AwYw//FUf8IJ4P/6FTQ//AAXQ/wDxNH/CCeD/APoVND/8F0P/AMTQAf8ACd+D/wDoa9D/APBjD/8AFUf8J34P/wChr0P/AMGMP/xVH/CCeD/+hU0P/wAF0P8A8TR/wgng/wD6FTQ//BdD/wDE0AH/AAnfg/8A6GvQ/wDwYw//ABVH/Cd+D/8Aoa9D/wDBjD/8VR/wgng//oVND/8ABdD/APE0f8IJ4P8A+hU0P/wXQ/8AxNAB/wAJ34P/AOhr0P8A8GMP/wAVR/wnfg//AKGvQ/8AwYw//FUf8IJ4P/6FTQ//AAXQ/wDxNH/CCeD/APoVND/8F0P/AMTQAf8ACd+D/wDoa9D/APBjD/8AFUf8J34P/wChr0P/AMGMP/xVH/CCeD/+hU0P/wAF0P8A8TR/wgng/wD6FTQ//BdD/wDE0AH/AAnfg/8A6GvQ/wDwYw//ABVH/Cd+D/8Aoa9D/wDBjD/8VR/wgng//oVND/8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",
      "text/plain": [
       "<PIL.PngImagePlugin.PngImageFile image mode=RGB size=607x380>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=607x380>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pytesseract\n",
    "from presidio_image_redactor import ImageRedactorEngine\n",
    "from PIL import Image\n",
    "\n",
    "pytesseract.pytesseract.tesseract_cmd = r\"C:\\Program Files\\Tesseract-OCR\\tesseract.exe\"\n",
    "\n",
    "image = Image.open(r\"D:\\Workspace\\Python\\Presidio\\pii_test_document.png\")\n",
    "\n",
    "redactor = ImageRedactorEngine()\n",
    "redacted_image = redactor.redact(image=image, ocr_kwargs={\"lang\": \"jpn\"})\n",
    "\n",
    "# オリジナル表示\n",
    "display(image)\n",
    "display(redacted_image)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "32c84eef",
   "metadata": {},
   "source": [
    "カスタムレコグナイザーあり"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "64d5fc0e",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Device set to use cpu\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=607x380>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import spacy\n",
    "import ginza  # noqa: F401\n",
    "\n",
    "if not getattr(spacy.load, \"_ja_ginza_patched\", False):\n",
    "    _original_spacy_load = spacy.load\n",
    "\n",
    "    def _make_patched_load(original_load):\n",
    "        def _patched(name, *args, **kwargs):\n",
    "            if name == \"ja_ginza\":\n",
    "                exclude = list(kwargs.get(\"exclude\", []))\n",
    "                for comp in (\"compound_splitter\", \"bunsetu_recognizer\"):\n",
    "                    if comp not in exclude:\n",
    "                        exclude.append(comp)\n",
    "                kwargs[\"exclude\"] = exclude\n",
    "                kwargs.pop(\"config\", None)\n",
    "            return original_load(name, *args, **kwargs)\n",
    "        _patched._ja_ginza_patched = True\n",
    "        return _patched\n",
    "\n",
    "    spacy.load = _make_patched_load(_original_spacy_load)\n",
    "\n",
    "\n",
    "from presidio_analyzer import AnalyzerEngine, Pattern, PatternRecognizer, RecognizerRegistry\n",
    "from presidio_analyzer.nlp_engine import TransformersNlpEngine, NerModelConfiguration\n",
    "from presidio_image_redactor import ImageRedactorEngine, ImageAnalyzerEngine\n",
    "import pytesseract\n",
    "from PIL import Image\n",
    "\n",
    "pytesseract.pytesseract.tesseract_cmd = r\"C:\\Program Files\\Tesseract-OCR\\tesseract.exe\"\n",
    "\n",
    "\n",
    "# ============================================================\n",
    "# 日本語NLPエンジン(GiNZA + xlm-roberta-ner-japanese)\n",
    "# ============================================================\n",
    "model_config = [{\"lang_code\": \"ja\", \"model_name\": {\n",
    "    \"spacy\": \"ja_ginza\",\n",
    "    \"transformers\": r\"H:\\BERT_Models\\tsmatz\\xlm-roberta-ner-japanese\"\n",
    "    }\n",
    "}]\n",
    "\n",
    "ner_model_configuration = NerModelConfiguration(\n",
    "    model_to_presidio_entity_mapping={\n",
    "        \"PER\": \"PERSON\", \"PERSON\": \"PERSON\",\n",
    "        \"LOC\": \"LOCATION\", \"GPE\": \"LOCATION\",\n",
    "        \"ORG\": \"ORGANIZATION\",\n",
    "        \"DAT\": \"DATE_TIME\", \"DATE\": \"DATE_TIME\",\n",
    "        \"TIM\": \"DATE_TIME\", \"TIME\": \"DATE_TIME\",\n",
    "        \"MONEY\": \"MONEY\", \"PERCENT\": \"PERCENT\",\n",
    "    },\n",
    "    low_confidence_score_multiplier=0.4,\n",
    "    low_score_entity_names=[\"ORGANIZATION\"],\n",
    "    alignment_mode=\"expand\",\n",
    "    aggregation_strategy=\"simple\",\n",
    ")\n",
    "\n",
    "nlp_engine = TransformersNlpEngine(models=model_config, ner_model_configuration=ner_model_configuration)\n",
    "nlp_engine.load()\n",
    "\n",
    "\n",
    "# ============================================================\n",
    "# カスタムレコグナイザー(郵便番号・マイナンバー)\n",
    "# ============================================================\n",
    "postal_recognizer = PatternRecognizer(\n",
    "    supported_entity=\"JP_POSTAL_CODE\",\n",
    "    patterns=[Pattern(name=\"jp_postal_code\", regex=r\"\\b\\d{3}-\\d{4}\\b\", score=0.85)],\n",
    "    context=[\"郵便番号\", \"〒\"],\n",
    "    supported_language=\"ja\",\n",
    ")\n",
    "my_number_recognizer = PatternRecognizer(\n",
    "    supported_entity=\"JP_MY_NUMBER\",\n",
    "    patterns=[Pattern(name=\"jp_my_number\", regex=r\"(?<!\\d)\\d{12}(?!\\d)\", score=0.3)],\n",
    "    context=[\"マイナンバー\", \"個人番号\"],\n",
    "    supported_language=\"ja\",\n",
    ")\n",
    "\n",
    "registry = RecognizerRegistry(supported_languages=[\"ja\"])\n",
    "registry.load_predefined_recognizers(nlp_engine=nlp_engine, languages=[\"ja\"])\n",
    "registry.add_recognizer(postal_recognizer)\n",
    "registry.add_recognizer(my_number_recognizer)\n",
    "\n",
    "analyzer = AnalyzerEngine(nlp_engine=nlp_engine, registry=registry, supported_languages=[\"ja\"])\n",
    "\n",
    "\n",
    "# ============================================================\n",
    "# 画像レダクター: 日本語analyzerを明示的に組み込む\n",
    "# ============================================================\n",
    "image_analyzer_engine = ImageAnalyzerEngine(analyzer_engine=analyzer)\n",
    "redactor = ImageRedactorEngine(image_analyzer_engine=image_analyzer_engine)\n",
    "\n",
    "image = Image.open(r\"D:\\Workspace\\Python\\Presidio\\pii_test_document.png\")\n",
    "\n",
    "redacted_image = redactor.redact(\n",
    "    image=image,\n",
    "    ocr_kwargs={\"lang\": \"jpn\"},\n",
    "    language=\"ja\",  # ← ここが重要: analyzeに language='ja' を渡す\n",
    ")\n",
    "\n",
    "redacted_image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "411bae27",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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