feat: 实现多 OCR 提供商架构和完整设置页面
## 主要变更 ### OCR 架构 - 新增多提供商 OCR 系统 (Tesseract.js, Baidu OCR, RapidOCR) - 添加 Provider 基类接口和工厂模式 - 支持 provider 自动选择和降级处理 - 新增 RapidOCR Python HTTP 服务 (端口 8080) ### 路径修复 - 修复 Windows 平台路径解析问题 - 统一路径处理工具 (lib/path.ts) - 修复 uploads 目录定位问题 ### 设置页面重构 - 三个标签页：API 配置、OCR 配置、AI 配置 - API 服务器地址配置 - OCR 服务商配置（Tesseract.js, RapidOCR, 百度 OCR） - AI 服务商配置（智谱 GLM, MiniMax, DeepSeek, Kimi, OpenAI, Anthropic） ### 端口配置 - 前端端口: 13056 - 后端端口: 13057 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
锦麟 王
+19
-1
@@ -13,9 +13,27 @@ NODE_ENV="development"
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CORS_ORIGIN="http://localhost:3000"
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# OCR
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OCR_PROVIDER="local"
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# OCR Provider: tesseract | baidu | rapidocr | auto
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# - tesseract: 本地轻量，需要安装 tesseract.js
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# - baidu: 云端准确，需要配置 API Key (有免费额度)
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# - rapidocr: 本地快速准确，需要启动 RapidOCR 服务
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# - auto: 自动选择可用的 provider
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OCR_PROVIDER="auto"
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OCR_CONFIDENCE_THRESHOLD="0.3"
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# Tesseract.js (本地 OCR，无需额外配置)
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# 安装: npm install tesseract.js
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# Baidu OCR (云端 OCR，需要申请密钥)
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# 获取地址: https://cloud.baidu.com/product/ocr
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BAIDU_OCR_API_KEY=""
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BAIDU_OCR_SECRET_KEY=""
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# RapidOCR (本地快速 OCR，需要启动服务)
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# Docker: docker run -d -p 8080:8080 cshgg/rapidocr
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# 或参考: https://github.com/RapidAI/RapidOCR
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RAPIDOCR_API_URL="http://localhost:8080"
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# AI (GLM)
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GLM_API_KEY=""
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GLM_API_URL="https://open.bigmodel.cn/api/paas/v4/chat/completions"
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Generated
+93
@@ -16,6 +16,7 @@
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"express": "^4.21.2",
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"jsonwebtoken": "^9.0.2",
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"multer": "^1.4.5-lts.1",
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"tesseract.js": "^5.1.1",
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"winston": "^3.17.0"
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},
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"devDependencies": {
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@@ -37,6 +38,9 @@
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"ts-jest": "^29.2.5",
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"tsx": "^4.19.2",
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"typescript": "^5.7.2"
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},
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"optionalDependencies": {
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"tesseract.js": "^5.1.1"
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}
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},
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"node_modules/@babel/code-frame": {
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@@ -2777,6 +2781,13 @@
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"node": ">= 10.0.0"
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}
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},
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"node_modules/bmp-js": {
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"version": "0.1.0",
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"resolved": "https://registry.npmmirror.com/bmp-js/-/bmp-js-0.1.0.tgz",
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"integrity": "sha512-vHdS19CnY3hwiNdkaqk93DvjVLfbEcI8mys4UjuWrlX1haDmroo8o4xCzh4wD6DGV6HxRCyauwhHRqMTfERtjw==",
|
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"license": "MIT",
|
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"optional": true
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},
|
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"node_modules/body-parser": {
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"version": "1.20.4",
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"resolved": "https://registry.npmjs.org/body-parser/-/body-parser-1.20.4.tgz",
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@@ -4617,6 +4628,13 @@
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"node": ">=0.10.0"
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}
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},
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"node_modules/idb-keyval": {
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"version": "6.2.2",
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"resolved": "https://registry.npmmirror.com/idb-keyval/-/idb-keyval-6.2.2.tgz",
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"integrity": "sha512-yjD9nARJ/jb1g+CvD0tlhUHOrJ9Sy0P8T9MF3YaLlHnSRpwPfpTX0XIvpmw3gAJUmEu3FiICLBDPXVwyEvrleg==",
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"license": "Apache-2.0",
|
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"optional": true
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},
|
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"node_modules/ignore": {
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"version": "7.0.5",
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"resolved": "https://registry.npmjs.org/ignore/-/ignore-7.0.5.tgz",
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@@ -4723,6 +4741,13 @@
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"url": "https://github.com/sponsors/ljharb"
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}
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},
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"node_modules/is-electron": {
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"version": "2.2.2",
|
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"resolved": "https://registry.npmmirror.com/is-electron/-/is-electron-2.2.2.tgz",
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"integrity": "sha512-FO/Rhvz5tuw4MCWkpMzHFKWD2LsfHzIb7i6MdPYZ/KW7AlxawyLkqdy+jPZP1WubqEADE3O4FUENlJHDfQASRg==",
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"license": "MIT",
|
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"optional": true
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},
|
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"node_modules/is-extglob": {
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"version": "2.1.1",
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"resolved": "https://registry.npmjs.org/is-extglob/-/is-extglob-2.1.1.tgz",
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@@ -4787,6 +4812,13 @@
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"url": "https://github.com/sponsors/sindresorhus"
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}
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},
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"node_modules/is-url": {
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"version": "1.2.4",
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"resolved": "https://registry.npmmirror.com/is-url/-/is-url-1.2.4.tgz",
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"integrity": "sha512-ITvGim8FhRiYe4IQ5uHSkj7pVaPDrCTkNd3yq3cV7iZAcJdHTUMPMEHcqSOy9xZ9qFenQCvi+2wjH9a1nXqHww==",
|
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"license": "MIT",
|
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"optional": true
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},
|
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"node_modules/isarray": {
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"version": "1.0.0",
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"resolved": "https://registry.npmjs.org/isarray/-/isarray-1.0.0.tgz",
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@@ -6167,6 +6199,16 @@
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"url": "https://github.com/sponsors/sindresorhus"
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}
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},
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"node_modules/opencollective-postinstall": {
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"version": "2.0.3",
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"resolved": "https://registry.npmmirror.com/opencollective-postinstall/-/opencollective-postinstall-2.0.3.tgz",
|
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"integrity": "sha512-8AV/sCtuzUeTo8gQK5qDZzARrulB3egtLzFgteqB2tcT4Mw7B8Kt7JcDHmltjz6FOAHsvTevk70gZEbhM4ZS9Q==",
|
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"license": "MIT",
|
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"optional": true,
|
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"bin": {
|
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"opencollective-postinstall": "index.js"
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}
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},
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"node_modules/optionator": {
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"version": "0.9.4",
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"resolved": "https://registry.npmjs.org/optionator/-/optionator-0.9.4.tgz",
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@@ -6610,6 +6652,13 @@
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"integrity": "sha512-Gd2UZBJDkXlY7GbJxfsE8/nvKkUEU1G38c1siN6QP6a9PT9MmHB8GnpscSmMJSoF8LOIrt8ud/wPtojys4G6+g==",
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"license": "MIT"
|
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},
|
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"node_modules/regenerator-runtime": {
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"version": "0.13.11",
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"resolved": "https://registry.npmmirror.com/regenerator-runtime/-/regenerator-runtime-0.13.11.tgz",
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"integrity": "sha512-kY1AZVr2Ra+t+piVaJ4gxaFaReZVH40AKNo7UCX6W+dEwBo/2oZJzqfuN1qLq1oL45o56cPaTXELwrTh8Fpggg==",
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"license": "MIT",
|
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"optional": true
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},
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"node_modules/require-directory": {
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"version": "2.1.1",
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"resolved": "https://registry.npmjs.org/require-directory/-/require-directory-2.1.1.tgz",
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@@ -7227,6 +7276,33 @@
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"integrity": "sha512-3wdGidZyq5PB084XLES5TpOSRA3wjXAlIWMhum2kRcv/41Sn2emQ0dycQW4uZXLejwKvg6EsvbdlVL+FYEct7A==",
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"license": "ISC"
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},
|
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"node_modules/tesseract.js": {
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"version": "5.1.1",
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"resolved": "https://registry.npmmirror.com/tesseract.js/-/tesseract.js-5.1.1.tgz",
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"integrity": "sha512-lzVl/Ar3P3zhpUT31NjqeCo1f+D5+YfpZ5J62eo2S14QNVOmHBTtbchHm/YAbOOOzCegFnKf4B3Qih9LuldcYQ==",
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"hasInstallScript": true,
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"license": "Apache-2.0",
|
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"optional": true,
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"dependencies": {
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"bmp-js": "^0.1.0",
|
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"idb-keyval": "^6.2.0",
|
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"is-electron": "^2.2.2",
|
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"is-url": "^1.2.4",
|
||||
"node-fetch": "^2.6.9",
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"opencollective-postinstall": "^2.0.3",
|
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"regenerator-runtime": "^0.13.3",
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"tesseract.js-core": "^5.1.1",
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"wasm-feature-detect": "^1.2.11",
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"zlibjs": "^0.3.1"
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}
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},
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"node_modules/tesseract.js-core": {
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"version": "5.1.1",
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"resolved": "https://registry.npmmirror.com/tesseract.js-core/-/tesseract.js-core-5.1.1.tgz",
|
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"integrity": "sha512-KX3bYSU5iGcO1XJa+QGPbi+Zjo2qq6eBhNjSGR5E5q0JtzkoipJKOUQD7ph8kFyteCEfEQ0maWLu8MCXtvX5uQ==",
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"license": "Apache-2.0",
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"optional": true
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},
|
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"node_modules/test-exclude": {
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"version": "6.0.0",
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"resolved": "https://registry.npmjs.org/test-exclude/-/test-exclude-6.0.0.tgz",
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@@ -7652,6 +7728,13 @@
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"makeerror": "1.0.12"
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}
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},
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"node_modules/wasm-feature-detect": {
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"version": "1.8.0",
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"resolved": "https://registry.npmmirror.com/wasm-feature-detect/-/wasm-feature-detect-1.8.0.tgz",
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"integrity": "sha512-zksaLKM2fVlnB5jQQDqKXXwYHLQUVH9es+5TOOHwGOVJOCeRBCiPjwSg+3tN2AdTCzjgli4jijCH290kXb/zWQ==",
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"license": "Apache-2.0",
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"optional": true
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},
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"node_modules/webidl-conversions": {
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"version": "3.0.1",
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"resolved": "https://registry.npmjs.org/webidl-conversions/-/webidl-conversions-3.0.1.tgz",
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@@ -7879,6 +7962,16 @@
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"funding": {
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"url": "https://github.com/sponsors/sindresorhus"
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}
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},
|
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"node_modules/zlibjs": {
|
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"version": "0.3.1",
|
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"resolved": "https://registry.npmmirror.com/zlibjs/-/zlibjs-0.3.1.tgz",
|
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"integrity": "sha512-+J9RrgTKOmlxFSDHo0pI1xM6BLVUv+o0ZT9ANtCxGkjIVCCUdx9alUF8Gm+dGLKbkkkidWIHFDZHDMpfITt4+w==",
|
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"license": "MIT",
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"optional": true,
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"engines": {
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"node": "*"
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}
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}
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}
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}
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@@ -17,7 +17,12 @@
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"prisma:migrate": "prisma migrate dev",
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"prisma:studio": "prisma studio"
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},
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"keywords": ["ocr", "document-management", "ai", "tdd"],
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"keywords": [
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"ocr",
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"document-management",
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"ai",
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"tdd"
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],
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"author": "",
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"license": "MIT",
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"dependencies": {
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@@ -30,6 +35,9 @@
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"multer": "^1.4.5-lts.1",
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"winston": "^3.17.0"
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},
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"optionalDependencies": {
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"tesseract.js": "^5.1.1"
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},
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"devDependencies": {
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"@types/bcrypt": "^5.0.2",
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"@types/cors": "^2.8.17",
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@@ -6,7 +6,6 @@ generator client {
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datasource db {
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provider = "sqlite"
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url = env("DATABASE_URL")
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}
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// 用户
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@@ -0,0 +1,114 @@
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"""
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RapidOCR HTTP Server
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为 Node.js 后端提供 OCR API 服务
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"""
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from rapidocr_onnxruntime import RapidOCR
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from http.server import HTTPServer, BaseHTTPRequestHandler
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import json
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import base64
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import numpy as np
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from io import BytesIO
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from PIL import Image
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import cv2
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# 初始化 RapidOCR
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ocr = RapidOCR()
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class OCRHandler(BaseHTTPRequestHandler):
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def _set_cors(self):
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"""设置 CORS"""
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self.send_header('Access-Control-Allow-Origin', '*')
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self.send_header('Access-Control-Allow-Methods', 'GET, POST, OPTIONS')
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self.send_header('Access-Control-Allow-Headers', 'Content-Type')
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def _send_json(self, data, status=200):
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"""发送 JSON 响应"""
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self.send_response(status)
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self.send_header('Content-Type', 'application/json')
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self._set_cors()
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self.end_headers()
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self.wfile.write(json.dumps(data, ensure_ascii=False).encode('utf-8'))
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def do_OPTIONS(self):
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"""处理 OPTIONS 请求"""
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self.send_response(200)
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self._set_cors()
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self.end_headers()
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def do_GET(self):
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"""健康检查"""
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if self.path == '/health':
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self._send_json({"status": "ok", "service": "rapidocr"})
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else:
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self._send_json({"error": "Not found"}, 404)
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def do_POST(self):
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"""处理 OCR 请求"""
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if self.path == '/ocr':
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try:
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content_length = int(self.headers['Content-Length'])
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post_data = self.rfile.read(content_length)
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data = json.loads(post_data.decode('utf-8'))
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# 获取图片数据
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images = data.get('images', [])
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if not images:
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self._send_json({"error": "No images provided"}, 400)
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return
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# 处理第一张图片
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image_base64 = images[0]
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image_data = base64.b64decode(image_base64)
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# 转换为 OpenCV 格式
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nparr = np.frombuffer(image_data, np.uint8)
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img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
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if img is None:
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self._send_json({"error": "Failed to decode image"}, 400)
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return
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# 执行 OCR
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result, _ = ocr(img)
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# 格式化结果
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ocr_results = []
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for line in result:
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ocr_results.append({
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"text": line[0],
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"score": float(line[1]),
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"box": line[2]
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})
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# 计算平均置信度
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avg_confidence = 0
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if ocr_results:
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avg_confidence = sum(r["score"] for r in ocr_results) / len(ocr_results)
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self._send_json({
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"code": 200,
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"msg": "success",
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"data": ocr_results
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})
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except Exception as e:
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self._send_json({"error": str(e)}, 500)
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else:
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self._send_json({"error": "Not found"}, 404)
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def log_message(self, format, *args):
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||||
"""减少日志输出"""
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pass
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def run_server(port=8080):
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||||
"""启动服务器"""
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server_address = ('', port)
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httpd = HTTPServer(server_address, OCRHandler)
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print(f"RapidOCR Server running on port {port}")
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print(f"Health check: http://localhost:{port}/health")
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print(f"OCR endpoint: http://localhost:{port}/ocr")
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httpd.serve_forever()
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||||
if __name__ == '__main__':
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run_server()
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@@ -6,11 +6,16 @@ import express from 'express';
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||||
import cors from 'cors';
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||||
import dotenv from 'dotenv';
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||||
import path from 'path';
|
||||
import { fileURLToPath } from 'url';
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||||
import authRoutes from './routes/auth.routes';
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||||
import documentRoutes from './routes/document.routes';
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||||
import todoRoutes from './routes/todo.routes';
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||||
import imageRoutes from './routes/image.routes';
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||||
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||||
// 获取当前文件的目录
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||||
const __filename = fileURLToPath(import.meta.url);
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||||
const __dirname = path.dirname(__filename);
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||||
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||||
// Load environment variables
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||||
dotenv.config();
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||||
|
||||
@@ -24,8 +29,8 @@ app.use(cors({
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||||
app.use(express.json());
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||||
app.use(express.urlencoded({ extended: true }));
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||||
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||||
// Static files for uploads
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||||
app.use('/uploads', express.static(path.join(process.cwd(), 'uploads')));
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||||
// Static files for uploads (使用绝对路径指向 backend/uploads)
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||||
app.use('/uploads', express.static(path.join(__dirname, '..', 'uploads')));
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||||
|
||||
// Health check
|
||||
app.get('/api/health', (_req, res) => {
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||||
|
||||
@@ -0,0 +1,84 @@
|
||||
/**
|
||||
* 路径解析工具
|
||||
* 解决开发环境下路径解析问题
|
||||
*/
|
||||
|
||||
import path from 'path';
|
||||
import fs from 'fs';
|
||||
import { fileURLToPath } from 'url';
|
||||
|
||||
/**
|
||||
* 获取项目根目录
|
||||
* 通过从当前文件向上查找 package.json 来确定
|
||||
*/
|
||||
export function getProjectRoot(): string {
|
||||
// 在开发环境使用 tsx 时，使用 process.cwd()
|
||||
// 在构建后的环境，使用 __dirname 的方式
|
||||
let currentDir: string;
|
||||
|
||||
try {
|
||||
// ESM 模式下获取当前文件目录
|
||||
const __filename = fileURLToPath(import.meta.url);
|
||||
currentDir = path.dirname(__filename);
|
||||
} catch {
|
||||
// 回退到 process.cwd()
|
||||
currentDir = process.cwd();
|
||||
}
|
||||
|
||||
// Windows 路径处理（去除开头的 /）
|
||||
if (process.platform === 'win32' && currentDir.startsWith('/') && /^[a-zA-Z]:/.test(currentDir.slice(1))) {
|
||||
currentDir = currentDir.substring(1);
|
||||
}
|
||||
|
||||
// 从当前目录向上查找 package.json
|
||||
let searchDir = currentDir;
|
||||
for (let i = 0; i < 10; i++) {
|
||||
const pkgPath = path.join(searchDir, 'package.json');
|
||||
if (fs.existsSync(pkgPath)) {
|
||||
return searchDir;
|
||||
}
|
||||
searchDir = path.dirname(searchDir);
|
||||
}
|
||||
|
||||
// 如果找不到，回退到 process.cwd()
|
||||
return process.cwd();
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取上传目录的绝对路径
|
||||
*/
|
||||
export function getUploadsDir(): string {
|
||||
const projectRoot = getProjectRoot();
|
||||
return path.join(projectRoot, 'uploads');
|
||||
}
|
||||
|
||||
/**
|
||||
* 解析图片路径
|
||||
* 将数据库中存储的路径 (/uploads/xxx.png) 解析为绝对路径
|
||||
*/
|
||||
export function resolveImagePath(imagePath: string): string {
|
||||
// 在 Windows 上，path.isAbsolute 会将 /uploads/... 认为是绝对路径
|
||||
// 但这实际上是 Unix 风格的相对路径，需要特殊处理
|
||||
const isWindowsAbsPath = process.platform === 'win32'
|
||||
? /^[a-zA-Z]:\\/.test(imagePath) // Windows 真正的绝对路径如 C:\
|
||||
: path.isAbsolute(imagePath);
|
||||
|
||||
if (isWindowsAbsPath) {
|
||||
return imagePath;
|
||||
}
|
||||
|
||||
// 处理 /uploads/ 开头的相对路径
|
||||
if (imagePath.startsWith('/uploads/')) {
|
||||
return path.join(getUploadsDir(), imagePath.replace('/uploads/', ''));
|
||||
}
|
||||
|
||||
// 其他相对路径，使用项目根目录
|
||||
return path.join(getProjectRoot(), imagePath);
|
||||
}
|
||||
|
||||
/**
|
||||
* 生成存储到数据库的路径
|
||||
*/
|
||||
export function generateDbPath(filename: string): string {
|
||||
return `/uploads/${filename}`;
|
||||
}
|
||||
@@ -5,9 +5,16 @@
|
||||
import multer from 'multer';
|
||||
import path from 'path';
|
||||
import fs from 'fs';
|
||||
import { fileURLToPath } from 'url';
|
||||
|
||||
// 获取当前文件的目录
|
||||
const __filename = fileURLToPath(import.meta.url);
|
||||
const __dirname = path.dirname(__filename);
|
||||
|
||||
// uploads 目录放在 backend 根目录下
|
||||
const uploadDir = path.join(__dirname, '..', '..', 'uploads');
|
||||
|
||||
// Ensure upload directory exists
|
||||
const uploadDir = path.join(process.cwd(), 'uploads');
|
||||
if (!fs.existsSync(uploadDir)) {
|
||||
fs.mkdirSync(uploadDir, { recursive: true });
|
||||
}
|
||||
@@ -51,3 +58,6 @@ export const upload = multer({
|
||||
fileSize: 10 * 1024 * 1024, // 10MB limit
|
||||
},
|
||||
});
|
||||
|
||||
// 导出上传目录路径供其他模块使用
|
||||
export { uploadDir };
|
||||
|
||||
@@ -7,7 +7,8 @@ import { Router } from 'express';
|
||||
import { ImageController } from '../controllers/image.controller';
|
||||
import { authenticate } from '../middleware/auth.middleware';
|
||||
import { upload } from '../middleware/upload.middleware';
|
||||
import { triggerOCRProcessing } from '../services/ocr-processor.service';
|
||||
import { triggerOCRProcessing, OCRProcessorService } from '../services/ocr-processor.service';
|
||||
import { OCRProviderType } from '../services/ocr-providers';
|
||||
|
||||
const router = Router();
|
||||
|
||||
@@ -32,6 +33,27 @@ router.get('/', authenticate, ImageController.getUserImages);
|
||||
*/
|
||||
router.get('/pending', authenticate, ImageController.getPending);
|
||||
|
||||
/**
|
||||
* @route GET /api/images/ocr/providers
|
||||
* @desc Get available OCR providers
|
||||
* @access Private
|
||||
*/
|
||||
router.get('/ocr/providers', authenticate, async (_req, res) => {
|
||||
try {
|
||||
const providers = await OCRProcessorService.getAvailableProviders();
|
||||
res.json({
|
||||
success: true,
|
||||
data: providers,
|
||||
});
|
||||
} catch (error) {
|
||||
const message = error instanceof Error ? error.message : '获取 OCR 提供商失败';
|
||||
res.status(500).json({
|
||||
success: false,
|
||||
error: message,
|
||||
});
|
||||
}
|
||||
});
|
||||
|
||||
/**
|
||||
* @route GET /api/images/:id
|
||||
* @desc Get image by ID
|
||||
@@ -43,14 +65,16 @@ router.get('/:id', authenticate, ImageController.getById);
|
||||
* @route POST /api/images/:id/reprocess
|
||||
* @desc Re-trigger OCR processing
|
||||
* @access Private
|
||||
* @body { provider?: 'tesseract' | 'baidu' | 'rapidocr' | 'auto' }
|
||||
*/
|
||||
router.post('/:id/reprocess', authenticate, async (req, res) => {
|
||||
try {
|
||||
const userId = req.user!.user_id;
|
||||
const { id } = req.params;
|
||||
const userId = typeof req.user!.user_id === 'string' ? req.user!.user_id : String(req.user!.user_id);
|
||||
const id = typeof req.params.id === 'string' ? req.params.id : req.params.id[0];
|
||||
const { provider } = req.body;
|
||||
|
||||
// 触发 OCR 处理
|
||||
triggerOCRProcessing(id, userId);
|
||||
triggerOCRProcessing(id, userId, { provider: provider as OCRProviderType });
|
||||
|
||||
res.json({
|
||||
success: true,
|
||||
|
||||
@@ -1,20 +1,36 @@
|
||||
/**
|
||||
* OCR Processor Service
|
||||
* 处理图片 OCR 识别的异步服务
|
||||
* 支持多种 OCR Provider: Tesseract.js, Baidu OCR, RapidOCR
|
||||
*/
|
||||
|
||||
import { prisma } from '../lib/prisma';
|
||||
import { ImageService } from './image.service';
|
||||
import fs from 'fs';
|
||||
import path from 'path';
|
||||
import {
|
||||
OCRProviderFactory,
|
||||
OCRProviderType,
|
||||
IImageSource,
|
||||
} from './ocr-providers';
|
||||
|
||||
export interface OCRProcessOptions {
|
||||
/** 指定 OCR Provider */
|
||||
provider?: OCRProviderType;
|
||||
/** 置信度阈值 */
|
||||
confidenceThreshold?: number;
|
||||
}
|
||||
|
||||
export class OCRProcessorService {
|
||||
/**
|
||||
* 处理图片的 OCR 识别
|
||||
* 注意：当前是模拟实现，返回占位符文本
|
||||
* 实际使用时需要集成 Tesseract.js 或其他 OCR 服务
|
||||
* @param imageId 图片 ID
|
||||
* @param userId 用户 ID
|
||||
* @param options 处理选项
|
||||
*/
|
||||
static async processImage(imageId: string, userId: string): Promise<void> {
|
||||
static async processImage(
|
||||
imageId: string,
|
||||
userId: string,
|
||||
options: OCRProcessOptions = {}
|
||||
): Promise<void> {
|
||||
try {
|
||||
// 更新状态为处理中
|
||||
await prisma.image.update({
|
||||
@@ -28,12 +44,14 @@ export class OCRProcessorService {
|
||||
throw new Error('Image not found');
|
||||
}
|
||||
|
||||
// TODO: 集成真实的 OCR 服务
|
||||
// 当前使用模拟实现
|
||||
const ocrResult = await this.performOCRSimulated(image);
|
||||
// 执行 OCR 识别
|
||||
const ocrResult = await this.performOCR(image, options);
|
||||
|
||||
// 根据置信度决定状态
|
||||
const status = ocrResult.confidence >= 0.3 ? 'completed' : 'failed';
|
||||
const threshold = options.confidenceThreshold
|
||||
? parseFloat(options.confidenceThreshold.toString())
|
||||
: parseFloat(process.env.OCR_CONFIDENCE_THRESHOLD || '0.3');
|
||||
const status = ocrResult.confidence >= threshold ? 'completed' : 'failed';
|
||||
|
||||
await prisma.image.update({
|
||||
where: { id: imageId },
|
||||
@@ -57,109 +75,106 @@ export class OCRProcessorService {
|
||||
}
|
||||
|
||||
/**
|
||||
* 模拟 OCR 处理
|
||||
* 实际实现应该调用 Tesseract.js 或其他 OCR API
|
||||
* 执行 OCR 识别
|
||||
* @param image 图片信息
|
||||
* @param options 处理选项
|
||||
*/
|
||||
private static async performOCRSimulated(image: any): Promise<{
|
||||
text: string;
|
||||
confidence: number;
|
||||
}> {
|
||||
// 模拟处理延迟
|
||||
await new Promise(resolve => setTimeout(resolve, 2000));
|
||||
private static async performOCR(
|
||||
image: any,
|
||||
options: OCRProcessOptions = {}
|
||||
): Promise<{ text: string; confidence: number }> {
|
||||
// 获取 OCR Provider
|
||||
const providerType = options.provider || (process.env.OCR_PROVIDER as OCRProviderType) || 'auto';
|
||||
const provider = OCRProviderFactory.create(providerType);
|
||||
|
||||
// TODO: 实际 OCR 集成选项：
|
||||
// 1. Tesseract.js (本地)
|
||||
// import Tesseract from 'tesseract.js';
|
||||
// const { data: { text, confidence } } = await Tesseract.recognize(imagePath, 'chi_sim+eng');
|
||||
//
|
||||
// 2. PaddleOCR (需要 Python 服务)
|
||||
// const response = await fetch('http://localhost:5000/ocr', {
|
||||
// method: 'POST',
|
||||
// body: JSON.stringify({ image_path: imagePath }),
|
||||
// });
|
||||
//
|
||||
// 3. 云端 OCR API (百度/腾讯/阿里)
|
||||
// 检查 provider 是否可用
|
||||
const available = await provider.isAvailable();
|
||||
if (!available) {
|
||||
throw new Error(
|
||||
`OCR Provider "${provider.getName()}" 不可用。` +
|
||||
`请检查配置或安装相应的依赖。`
|
||||
);
|
||||
}
|
||||
|
||||
// 准备图片来源
|
||||
const source: IImageSource = {
|
||||
path: image.file_path,
|
||||
};
|
||||
|
||||
// 执行识别
|
||||
const result = await provider.recognize(source);
|
||||
|
||||
console.log(
|
||||
`[OCR] Provider: ${provider.getName()}, ` +
|
||||
`Confidence: ${(result.confidence * 100).toFixed(1)}%, ` +
|
||||
`Duration: ${result.duration}ms, ` +
|
||||
`Text length: ${result.text.length}`
|
||||
);
|
||||
|
||||
// 模拟返回结果
|
||||
return {
|
||||
text: '[模拟 OCR 结果] 图片文字识别功能尚未集成。请在设置页面配置 OCR 服务后重试。',
|
||||
confidence: 0.5,
|
||||
text: result.text,
|
||||
confidence: result.confidence,
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* 使用 Tesseract.js 进行 OCR 识别（需要安装依赖）
|
||||
* 获取所有可用的 OCR Providers
|
||||
*/
|
||||
private static async performOCRWithTesseract(imagePath: string): Promise<{
|
||||
text: string;
|
||||
confidence: number;
|
||||
}> {
|
||||
// 动态导入 Tesseract（如果已安装）
|
||||
try {
|
||||
const Tesseract = await import('tesseract.js');
|
||||
|
||||
// 检查文件是否存在
|
||||
const fullPath = path.join(process.cwd(), imagePath.replace('/uploads/', 'uploads/'));
|
||||
if (!fs.existsSync(fullPath)) {
|
||||
throw new Error(`Image file not found: ${fullPath}`);
|
||||
}
|
||||
|
||||
const result = await Tesseract.recognize(fullPath, 'chi_sim+eng', {
|
||||
logger: (m: any) => console.log(m),
|
||||
});
|
||||
|
||||
return {
|
||||
text: result.data.text,
|
||||
confidence: result.data.confidence / 100, // Tesseract 返回 0-100，需要转换为 0-1
|
||||
};
|
||||
} catch (error) {
|
||||
// 如果 Tesseract 未安装，返回模拟结果
|
||||
console.warn('Tesseract.js not installed, using simulated OCR:', error);
|
||||
return this.performOCRSimulated(null);
|
||||
}
|
||||
static async getAvailableProviders(): Promise<
|
||||
Array<{ type: string; name: string; available: boolean; typeDesc: string }>
|
||||
> {
|
||||
return OCRProviderFactory.getAvailableProviders();
|
||||
}
|
||||
|
||||
/**
|
||||
* 调用外部 OCR API（示例）
|
||||
* 测试指定的 OCR Provider
|
||||
*/
|
||||
private static async performOCRWithAPI(imagePath: string): Promise<{
|
||||
text: string;
|
||||
confidence: number;
|
||||
static async testProvider(
|
||||
providerType: OCRProviderType,
|
||||
imagePath: string
|
||||
): Promise<{
|
||||
success: boolean;
|
||||
result?: { text: string; confidence: number; duration: number };
|
||||
error?: string;
|
||||
}> {
|
||||
// 示例：调用百度 OCR API
|
||||
// const apiKey = process.env.BAIDU_OCR_API_KEY;
|
||||
// const secretKey = process.env.BAIDU_OCR_SECRET_KEY;
|
||||
//
|
||||
// // 获取 access token
|
||||
// const tokenResponse = await fetch(`https://aip.baidubce.com/oauth/2.0/token?grant_type=client_credentials&client_id=${apiKey}&client_secret=${secretKey}`);
|
||||
// const { access_token } = await tokenResponse.json();
|
||||
//
|
||||
// // 读取图片并转为 base64
|
||||
// const imageBuffer = fs.readFileSync(imagePath);
|
||||
// const imageBase64 = imageBuffer.toString('base64');
|
||||
//
|
||||
// // 调用 OCR API
|
||||
// const ocrResponse = await fetch(`https://aip.baidubce.com/rest/2.0/ocr/v1/general_basic?access_token=${access_token}`, {
|
||||
// method: 'POST',
|
||||
// headers: { 'Content-Type': 'application/x-www-form-urlencoded' },
|
||||
// body: `image=${encodeURIComponent(imageBase64)}`,
|
||||
// });
|
||||
//
|
||||
// const result = await ocrResponse.json();
|
||||
//
|
||||
// return {
|
||||
// text: result.words_result?.map((w: any) => w.words).join('\n') || '',
|
||||
// confidence: (result.words_result?.[0]?.probability?.average || 0.5) / 100,
|
||||
// };
|
||||
try {
|
||||
const provider = OCRProviderFactory.create(providerType);
|
||||
const available = await provider.isAvailable();
|
||||
|
||||
throw new Error('OCR API not configured');
|
||||
if (!available) {
|
||||
return {
|
||||
success: false,
|
||||
error: `Provider "${provider.getName()}" 不可用`,
|
||||
};
|
||||
}
|
||||
|
||||
const result = await provider.recognize({ path: imagePath });
|
||||
|
||||
return {
|
||||
success: true,
|
||||
result: {
|
||||
text: result.text,
|
||||
confidence: result.confidence,
|
||||
duration: result.duration || 0,
|
||||
},
|
||||
};
|
||||
} catch (error) {
|
||||
return {
|
||||
success: false,
|
||||
error: error instanceof Error ? error.message : String(error),
|
||||
};
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// 导出异步处理函数（用于在后台触发 OCR）
|
||||
export const triggerOCRProcessing = async (imageId: string, userId: string) => {
|
||||
export const triggerOCRProcessing = async (
|
||||
imageId: string,
|
||||
userId: string,
|
||||
options?: OCRProcessOptions
|
||||
) => {
|
||||
// 不等待完成，在后台处理
|
||||
OCRProcessorService.processImage(imageId, userId).catch(error => {
|
||||
OCRProcessorService.processImage(imageId, userId, options).catch((error) => {
|
||||
console.error('OCR processing failed:', error);
|
||||
});
|
||||
};
|
||||
|
||||
@@ -0,0 +1,187 @@
|
||||
/**
|
||||
* Baidu OCR Provider
|
||||
* 特点：准确率高、速度快、国内访问快
|
||||
* 缺点：需要付费 (有免费额度)、需要网络连接
|
||||
* 官方文档: https://cloud.baidu.com/doc/OCR/index.html
|
||||
*/
|
||||
|
||||
import { BaseOCRProvider, IImageSource, OCRRecognitionResult, OCRProviderConfig } from './base.provider';
|
||||
import fs from 'fs';
|
||||
|
||||
interface BaiduOCRResponse {
|
||||
words_result: Array<{
|
||||
words: string;
|
||||
probability?: {
|
||||
average: number;
|
||||
variance: number;
|
||||
min: number;
|
||||
};
|
||||
}>;
|
||||
error_code?: number;
|
||||
error_msg?: string;
|
||||
}
|
||||
|
||||
interface BaiduTokenResponse {
|
||||
access_token: string;
|
||||
expires_in: number;
|
||||
}
|
||||
|
||||
export class BaiduProvider extends BaseOCRProvider {
|
||||
private apiKey: string;
|
||||
private secretKey: string;
|
||||
private accessToken: string | null = null;
|
||||
private tokenExpireTime: number = 0;
|
||||
private apiUrl = 'https://aip.baidubce.com/rest/2.0/ocr/v1/general_basic';
|
||||
|
||||
constructor(config: OCRProviderConfig & { apiKey?: string; secretKey?: string } = {}) {
|
||||
super(config);
|
||||
this.apiKey = config.apiKey || process.env.BAIDU_OCR_API_KEY || '';
|
||||
this.secretKey = config.secretKey || process.env.BAIDU_OCR_SECRET_KEY || '';
|
||||
}
|
||||
|
||||
getName(): string {
|
||||
return 'Baidu OCR';
|
||||
}
|
||||
|
||||
getType(): 'local' | 'cloud' {
|
||||
return 'cloud';
|
||||
}
|
||||
|
||||
/**
|
||||
* 检查配置是否完整
|
||||
*/
|
||||
async isAvailable(): Promise<boolean> {
|
||||
return !!(this.apiKey && this.secretKey);
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取访问令牌
|
||||
*/
|
||||
private async getAccessToken(): Promise<string> {
|
||||
// 检查缓存
|
||||
if (this.accessToken && Date.now() < this.tokenExpireTime) {
|
||||
return this.accessToken;
|
||||
}
|
||||
|
||||
const url = `https://aip.baidubce.com/oauth/2.0/token?grant_type=client_credentials&client_id=${this.apiKey}&client_secret=${this.secretKey}`;
|
||||
|
||||
const response = await fetch(url);
|
||||
const data = (await response.json()) as BaiduTokenResponse;
|
||||
|
||||
if (!data.access_token) {
|
||||
throw new Error('获取百度 OCR access_token 失败');
|
||||
}
|
||||
|
||||
this.accessToken = data.access_token;
|
||||
this.tokenExpireTime = Date.now() + (data.expires_in - 300) * 1000; // 提前 5 分钟过期
|
||||
|
||||
return this.accessToken;
|
||||
}
|
||||
|
||||
/**
|
||||
* 执行 OCR 识别
|
||||
*/
|
||||
async recognize(
|
||||
source: IImageSource,
|
||||
options?: OCRProviderConfig
|
||||
): Promise<OCRRecognitionResult> {
|
||||
const startTime = Date.now();
|
||||
|
||||
// 检查配置
|
||||
const available = await this.isAvailable();
|
||||
if (!available) {
|
||||
throw new Error('百度 OCR 未配置。请设置 BAIDU_OCR_API_KEY 和 BAIDU_OCR_SECRET_KEY 环境变量');
|
||||
}
|
||||
|
||||
// 获取图片 Base64
|
||||
const imageBase64 = await this.getImageBase64(source);
|
||||
|
||||
// 获取访问令牌
|
||||
const token = await this.getAccessToken();
|
||||
|
||||
// 调用 OCR API
|
||||
const response = await this.withTimeout(
|
||||
fetch(`${this.apiUrl}?access_token=${token}`, {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/x-www-form-urlencoded' },
|
||||
body: `image=${encodeURIComponent(imageBase64)}`,
|
||||
}),
|
||||
options?.timeout || this.config.timeout || 10000
|
||||
);
|
||||
|
||||
const data = (await response.json()) as BaiduOCRResponse;
|
||||
const duration = Date.now() - startTime;
|
||||
|
||||
// 检查错误
|
||||
if (data.error_code) {
|
||||
throw new Error(`百度 OCR 错误: ${data.error_msg} (${data.error_code})`);
|
||||
}
|
||||
|
||||
// 提取文本和置信度
|
||||
const words = data.words_result || [];
|
||||
const text = words.map((w) => w.words).join('\n');
|
||||
|
||||
// 计算平均置信度
|
||||
let confidence = 0.9; // 默认置信度
|
||||
if (words.length > 0 && words[0].probability) {
|
||||
const sum = words.reduce((acc, w) => acc + (w.probability?.average || 0), 0);
|
||||
confidence = (sum / words.length) / 100;
|
||||
}
|
||||
|
||||
return {
|
||||
text: text.trim(),
|
||||
confidence,
|
||||
duration,
|
||||
extra: {
|
||||
provider: 'baidu',
|
||||
wordCount: words.length,
|
||||
},
|
||||
};
|
||||
}
|
||||
|
||||
getRecommendations() {
|
||||
return {
|
||||
maxImageSize: 4 * 1024 * 1024, // 4MB 限制
|
||||
supportedFormats: ['jpg', 'jpeg', 'png', 'bmp'],
|
||||
notes: '百度 OCR 标准版 QPS 限制为 2，每日免费额度 1000 次。适合高精度需求场景。',
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取图片 Base64
|
||||
*/
|
||||
private async getImageBase64(source: IImageSource): Promise<string> {
|
||||
if (source.base64) {
|
||||
// 移除 data URL 前缀
|
||||
return source.base64.replace(/^data:image\/\w+;base64,/, '');
|
||||
}
|
||||
|
||||
if (source.buffer) {
|
||||
return source.buffer.toString('base64');
|
||||
}
|
||||
|
||||
if (source.path) {
|
||||
// 使用基类的路径解析方法
|
||||
const fullPath = this.resolveImagePath(source.path);
|
||||
const buffer = fs.readFileSync(fullPath);
|
||||
return buffer.toString('base64');
|
||||
}
|
||||
|
||||
throw new Error('无效的图片来源');
|
||||
}
|
||||
|
||||
/**
|
||||
* 超时包装
|
||||
*/
|
||||
private async withTimeout<T>(promise: Promise<T>, timeout: number): Promise<T> {
|
||||
return Promise.race([
|
||||
promise,
|
||||
new Promise<never>((_, reject) =>
|
||||
setTimeout(() => reject(new Error('timeout')), timeout)
|
||||
),
|
||||
]);
|
||||
}
|
||||
}
|
||||
|
||||
// 导出单例实例
|
||||
export const baiduProvider = new BaiduProvider();
|
||||
@@ -0,0 +1,127 @@
|
||||
/**
|
||||
* OCR Provider Base Interface
|
||||
* OCR 提供商基础接口
|
||||
*/
|
||||
|
||||
import { resolveImagePath } from '../../lib/path';
|
||||
|
||||
export interface OCRRecognitionResult {
|
||||
/** 识别的文本内容 */
|
||||
text: string;
|
||||
/** 置信度 (0-1) */
|
||||
confidence: number;
|
||||
/** 处理耗时 (毫秒) */
|
||||
duration?: number;
|
||||
/** 额外信息 */
|
||||
extra?: Record<string, unknown>;
|
||||
}
|
||||
|
||||
export interface OCRProviderConfig {
|
||||
/** 超时时间 (毫秒) */
|
||||
timeout?: number;
|
||||
/** 语言代码 (chi_sim, eng 等) */
|
||||
language?: string;
|
||||
/** 额外配置 */
|
||||
extras?: Record<string, unknown>;
|
||||
}
|
||||
|
||||
export interface IImageSource {
|
||||
/** 图片本地路径 */
|
||||
path?: string;
|
||||
/** 图片 Buffer */
|
||||
buffer?: Buffer;
|
||||
/** 图片 Base64 */
|
||||
base64?: string;
|
||||
/** 图片 URL */
|
||||
url?: string;
|
||||
}
|
||||
|
||||
/**
|
||||
* OCR Provider 抽象基类
|
||||
* 所有 OCR 提供商都需要实现此接口
|
||||
*/
|
||||
export abstract class BaseOCRProvider {
|
||||
protected config: OCRProviderConfig;
|
||||
|
||||
constructor(config: OCRProviderConfig = {}) {
|
||||
this.config = {
|
||||
timeout: 30000,
|
||||
language: 'chi_sim+eng',
|
||||
...config,
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Provider 名称
|
||||
*/
|
||||
abstract getName(): string;
|
||||
|
||||
/**
|
||||
* Provider 类型 (local | cloud)
|
||||
*/
|
||||
abstract getType(): 'local' | 'cloud';
|
||||
|
||||
/**
|
||||
* 检查 Provider 是否可用
|
||||
*/
|
||||
abstract isAvailable(): Promise<boolean> | boolean;
|
||||
|
||||
/**
|
||||
* 执行 OCR 识别
|
||||
* @param source 图片来源 (路径/Buffer/Base64/URL)
|
||||
* @param options 可选配置
|
||||
*/
|
||||
abstract recognize(
|
||||
source: IImageSource,
|
||||
options?: OCRProviderConfig
|
||||
): Promise<OCRRecognitionResult>;
|
||||
|
||||
/**
|
||||
* 批量识别
|
||||
*/
|
||||
async batchRecognize(
|
||||
sources: IImageSource[],
|
||||
options?: OCRProviderConfig
|
||||
): Promise<OCRRecognitionResult[]> {
|
||||
const results: OCRRecognitionResult[] = [];
|
||||
|
||||
for (const source of sources) {
|
||||
try {
|
||||
const result = await this.recognize(source, options);
|
||||
results.push(result);
|
||||
} catch (error) {
|
||||
results.push({
|
||||
text: '',
|
||||
confidence: 0,
|
||||
duration: 0,
|
||||
extra: { error: error instanceof Error ? error.message : String(error) },
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
return results;
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取推荐配置
|
||||
*/
|
||||
getRecommendations(): {
|
||||
maxImageSize?: number;
|
||||
supportedFormats?: string[];
|
||||
notes?: string;
|
||||
} {
|
||||
return {
|
||||
maxImageSize: 10 * 1024 * 1024, // 10MB
|
||||
supportedFormats: ['jpg', 'jpeg', 'png', 'webp', 'bmp', 'gif'],
|
||||
notes: '建议图片分辨率不低于 300dpi',
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* 解析图片路径
|
||||
* 将数据库路径转换为绝对路径
|
||||
*/
|
||||
protected resolveImagePath(imagePath: string): string {
|
||||
return resolveImagePath(imagePath);
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,100 @@
|
||||
/**
|
||||
* OCR Providers Module
|
||||
* 导出所有 OCR 提供商
|
||||
*/
|
||||
|
||||
export { BaseOCRProvider, IImageSource, OCRRecognitionResult, OCRProviderConfig } from './base.provider';
|
||||
export { TesseractProvider, tesseractProvider } from './tesseract.provider';
|
||||
export { BaiduProvider, baiduProvider } from './baidu.provider';
|
||||
export { RapidOCRProvider, rapidocrProvider } from './rapidocr.provider';
|
||||
|
||||
import { TesseractProvider, BaiduProvider, RapidOCRProvider } from './index';
|
||||
|
||||
/**
|
||||
* OCR Provider 类型
|
||||
*/
|
||||
export type OCRProviderType = 'tesseract' | 'baidu' | 'rapidocr' | 'auto';
|
||||
|
||||
/**
|
||||
* OCR Provider 工厂
|
||||
* 根据 provider 类型返回对应的实例
|
||||
*/
|
||||
export class OCRProviderFactory {
|
||||
private static providers = {
|
||||
tesseract: TesseractProvider,
|
||||
baidu: BaiduProvider,
|
||||
rapidocr: RapidOCRProvider,
|
||||
};
|
||||
|
||||
/**
|
||||
* 创建 Provider 实例
|
||||
*/
|
||||
static create(
|
||||
type: OCRProviderType,
|
||||
config?: any
|
||||
): TesseractProvider | BaiduProvider | RapidOCRProvider {
|
||||
if (type === 'auto') {
|
||||
// 自动选择可用的 provider
|
||||
return this.autoSelect();
|
||||
}
|
||||
|
||||
const ProviderClass = this.providers[type];
|
||||
if (!ProviderClass) {
|
||||
throw new Error(`未知的 OCR provider: ${type}`);
|
||||
}
|
||||
|
||||
return new ProviderClass(config);
|
||||
}
|
||||
|
||||
/**
|
||||
* 自动选择可用的 provider
|
||||
* 优先级: RapidOCR > Tesseract > Baidu
|
||||
*/
|
||||
private static autoSelect(): TesseractProvider | BaiduProvider | RapidOCRProvider {
|
||||
const envProvider = process.env.OCR_PROVIDER as OCRProviderType;
|
||||
|
||||
// 如果指定了 provider 且不是 auto，使用指定的
|
||||
if (envProvider && envProvider !== 'auto' && this.providers[envProvider]) {
|
||||
const ProviderClass = this.providers[envProvider];
|
||||
return new ProviderClass();
|
||||
}
|
||||
|
||||
// 检查可用性并选择
|
||||
// RapidOCR (本地快速)
|
||||
if (process.env.RAPIDOCR_API_URL) {
|
||||
return new RapidOCRProvider();
|
||||
}
|
||||
|
||||
// Baidu OCR (云端准确)
|
||||
if (process.env.BAIDU_OCR_API_KEY && process.env.BAIDU_OCR_SECRET_KEY) {
|
||||
return new BaiduProvider();
|
||||
}
|
||||
|
||||
// Tesseract.js (本地兜底)
|
||||
return new TesseractProvider();
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取所有可用的 providers
|
||||
*/
|
||||
static async getAvailableProviders(): Promise<
|
||||
Array<{ type: string; name: string; available: boolean; typeDesc: string }>
|
||||
> {
|
||||
const providers = [
|
||||
{ type: 'rapidocr', name: 'RapidOCR', instance: new RapidOCRProvider(), typeDesc: '本地快速准确' },
|
||||
{ type: 'baidu', name: 'Baidu OCR', instance: new BaiduProvider(), typeDesc: '云端准确' },
|
||||
{ type: 'tesseract', name: 'Tesseract.js', instance: new TesseractProvider(), typeDesc: '本地轻量' },
|
||||
];
|
||||
|
||||
const results = await Promise.all(
|
||||
providers.map(async (p) => ({
|
||||
type: p.type,
|
||||
name: p.name,
|
||||
available: await p.instance.isAvailable(),
|
||||
typeDesc: p.typeDesc,
|
||||
}))
|
||||
);
|
||||
|
||||
return results;
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,167 @@
|
||||
/**
|
||||
* RapidOCR Provider
|
||||
* 特点：速度快、准确率高、免费、本地运行
|
||||
* 基于 PaddleOCR，中文识别效果优秀
|
||||
*
|
||||
* 部署方式：
|
||||
* 1. 安装 Python 服务: pip install rapidocr-onnxruntime
|
||||
* 2. 启动服务 (参考 rapidocr_server 项目)
|
||||
* 3. 或使用 Docker: docker run -p 8080:8080 cshgg/rapidocr
|
||||
*
|
||||
* GitHub: https://github.com/RapidAI/RapidOCR
|
||||
*/
|
||||
|
||||
import { BaseOCRProvider, IImageSource, OCRRecognitionResult, OCRProviderConfig } from './base.provider';
|
||||
import fs from 'fs';
|
||||
|
||||
interface RapidOCRResponse {
|
||||
code: number;
|
||||
msg: string;
|
||||
data: Array<{
|
||||
text: string;
|
||||
score: number;
|
||||
box: number[][];
|
||||
}>;
|
||||
}
|
||||
|
||||
interface RapidOCRRequest {
|
||||
images: string[];
|
||||
options?: {
|
||||
use_dilation?: boolean;
|
||||
use_cls?: boolean;
|
||||
use_tensorrt?: boolean;
|
||||
};
|
||||
}
|
||||
|
||||
export class RapidOCRProvider extends BaseOCRProvider {
|
||||
private apiUrl: string;
|
||||
|
||||
constructor(config: OCRProviderConfig & { apiUrl?: string } = {}) {
|
||||
super(config);
|
||||
this.apiUrl = config.apiUrl || process.env.RAPIDOCR_API_URL || 'http://localhost:8080';
|
||||
}
|
||||
|
||||
getName(): string {
|
||||
return 'RapidOCR';
|
||||
}
|
||||
|
||||
getType(): 'local' | 'cloud' {
|
||||
return 'local';
|
||||
}
|
||||
|
||||
/**
|
||||
* 检查 RapidOCR 服务是否可用
|
||||
*/
|
||||
async isAvailable(): Promise<boolean> {
|
||||
try {
|
||||
const response = await fetch(`${this.apiUrl}/health`, {
|
||||
signal: AbortSignal.timeout(2000),
|
||||
});
|
||||
return response.ok;
|
||||
} catch {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 执行 OCR 识别
|
||||
*/
|
||||
async recognize(
|
||||
source: IImageSource,
|
||||
options?: OCRProviderConfig
|
||||
): Promise<OCRRecognitionResult> {
|
||||
const startTime = Date.now();
|
||||
|
||||
// 获取图片 Base64
|
||||
const imageBase64 = await this.getImageBase64(source);
|
||||
|
||||
// 调用 RapidOCR API
|
||||
const response = await this.withTimeout(
|
||||
fetch(`${this.apiUrl}/ocr`, {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
body: JSON.stringify({
|
||||
images: [imageBase64],
|
||||
options: {
|
||||
use_dilation: true, // 使用膨胀增强识别
|
||||
use_cls: true, // 使用文字方向分类
|
||||
},
|
||||
} as RapidOCRRequest),
|
||||
}),
|
||||
options?.timeout || this.config.timeout || 15000
|
||||
);
|
||||
|
||||
const data = (await response.json()) as RapidOCRResponse;
|
||||
const duration = Date.now() - startTime;
|
||||
|
||||
// 检查错误（支持两种错误格式）
|
||||
if (data.code !== 200 && 'error' in data) {
|
||||
throw new Error(`RapidOCR 错误: ${(data as any).error || data.msg} (${data.code})`);
|
||||
}
|
||||
|
||||
// 提取文本和置信度（确保 data.data 存在）
|
||||
const ocrResults = Array.isArray(data.data) ? data.data : [];
|
||||
const text = ocrResults.map((r) => r.text).join('\n');
|
||||
|
||||
// 计算平均置信度
|
||||
const confidence = ocrResults.length > 0
|
||||
? ocrResults.reduce((acc, r) => acc + (r.score || 0), 0) / ocrResults.length
|
||||
: 0;
|
||||
|
||||
return {
|
||||
text: text.trim(),
|
||||
confidence,
|
||||
duration,
|
||||
extra: {
|
||||
provider: 'rapidocr',
|
||||
textCount: ocrResults.length,
|
||||
},
|
||||
};
|
||||
}
|
||||
|
||||
getRecommendations() {
|
||||
return {
|
||||
maxImageSize: 10 * 1024 * 1024,
|
||||
supportedFormats: ['jpg', 'jpeg', 'png', 'webp', 'bmp'],
|
||||
notes: 'RapidOCR 是基于 PaddleOCR 的本地服务，速度快且准确率高。需要先启动 RapidOCR 服务。',
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取图片 Base64
|
||||
*/
|
||||
private async getImageBase64(source: IImageSource): Promise<string> {
|
||||
if (source.base64) {
|
||||
// 移除 data URL 前缀
|
||||
return source.base64.replace(/^data:image\/\w+;base64,/, '');
|
||||
}
|
||||
|
||||
if (source.buffer) {
|
||||
return source.buffer.toString('base64');
|
||||
}
|
||||
|
||||
if (source.path) {
|
||||
// 使用基类的路径解析方法
|
||||
const fullPath = this.resolveImagePath(source.path);
|
||||
const buffer = fs.readFileSync(fullPath);
|
||||
return buffer.toString('base64');
|
||||
}
|
||||
|
||||
throw new Error('无效的图片来源');
|
||||
}
|
||||
|
||||
/**
|
||||
* 超时包装
|
||||
*/
|
||||
private async withTimeout<T>(promise: Promise<T>, timeout: number): Promise<T> {
|
||||
return Promise.race([
|
||||
promise,
|
||||
new Promise<never>((_, reject) =>
|
||||
setTimeout(() => reject(new Error('timeout')), timeout)
|
||||
),
|
||||
]);
|
||||
}
|
||||
}
|
||||
|
||||
// 导出单例实例
|
||||
export const rapidocrProvider = new RapidOCRProvider();
|
||||
@@ -0,0 +1,166 @@
|
||||
/**
|
||||
* Tesseract.js OCR Provider
|
||||
* 特点：免费、本地运行、支持多语言
|
||||
* 缺点：速度较慢、准确率中等
|
||||
*/
|
||||
|
||||
import { BaseOCRProvider, IImageSource, OCRRecognitionResult, OCRProviderConfig } from './base.provider';
|
||||
import fs from 'fs';
|
||||
|
||||
interface TesseractModule {
|
||||
recognize: (
|
||||
image: string | Buffer,
|
||||
lang: string,
|
||||
options?: { logger?: (m: any) => void }
|
||||
) => Promise<{ data: { text: string; confidence: number } }>;
|
||||
}
|
||||
|
||||
export class TesseractProvider extends BaseOCRProvider {
|
||||
private tesseract: TesseractModule | null = null;
|
||||
private initialized = false;
|
||||
|
||||
constructor(config: OCRProviderConfig = {}) {
|
||||
super(config);
|
||||
}
|
||||
|
||||
getName(): string {
|
||||
return 'Tesseract.js';
|
||||
}
|
||||
|
||||
getType(): 'local' | 'cloud' {
|
||||
return 'local';
|
||||
}
|
||||
|
||||
/**
|
||||
* 检查 Tesseract.js 是否已安装
|
||||
*/
|
||||
async isAvailable(): Promise<boolean> {
|
||||
if (this.initialized) {
|
||||
return this.tesseract !== null;
|
||||
}
|
||||
|
||||
try {
|
||||
const module = await import('tesseract.js');
|
||||
// tesseract.js 是默认导出，需要使用 .default
|
||||
this.tesseract = (module as any).default || module;
|
||||
this.initialized = true;
|
||||
return true;
|
||||
} catch {
|
||||
this.initialized = true;
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 执行 OCR 识别
|
||||
*/
|
||||
async recognize(
|
||||
source: IImageSource,
|
||||
options?: OCRProviderConfig
|
||||
): Promise<OCRRecognitionResult> {
|
||||
const startTime = Date.now();
|
||||
|
||||
// 确定语言
|
||||
const language = options?.language || this.config.language || 'chi_sim+eng';
|
||||
|
||||
// 获取图片数据
|
||||
const imageData = await this.getImageData(source);
|
||||
|
||||
// 动态导入 tesseract.js
|
||||
try {
|
||||
const tesseractModule = await import('tesseract.js');
|
||||
const Tesseract = (tesseractModule as any).default || tesseractModule;
|
||||
|
||||
const result = await this.withTimeout(
|
||||
Tesseract.recognize(imageData, language, {
|
||||
logger: (m: any) => {
|
||||
if (m.status === 'recognizing text') {
|
||||
// 可选：记录进度
|
||||
// console.log(`Tesseract progress: ${(m.progress * 100).toFixed(0)}%`);
|
||||
}
|
||||
},
|
||||
}),
|
||||
options?.timeout || this.config.timeout || 30000
|
||||
) as { data: { text: string; confidence: number } };
|
||||
|
||||
const duration = Date.now() - startTime;
|
||||
|
||||
return {
|
||||
text: this.cleanText(result.data.text),
|
||||
confidence: result.data.confidence / 100, // Tesseract 返回 0-100
|
||||
duration,
|
||||
extra: {
|
||||
provider: 'tesseract.js',
|
||||
language,
|
||||
},
|
||||
};
|
||||
} catch (error) {
|
||||
if (error instanceof Error && error.message === 'timeout') {
|
||||
throw new Error('OCR 识别超时');
|
||||
}
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
getRecommendations() {
|
||||
return {
|
||||
...super.getRecommendations(),
|
||||
notes: '首次运行会下载语言包 (约 20MB)，后续运行会更快。适合少量图片处理。',
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取图片数据 (路径或 Buffer)
|
||||
*/
|
||||
private async getImageData(source: IImageSource): Promise<string | Buffer> {
|
||||
if (source.buffer) {
|
||||
return source.buffer;
|
||||
}
|
||||
|
||||
if (source.path) {
|
||||
// 使用基类的路径解析方法
|
||||
const fullPath = this.resolveImagePath(source.path);
|
||||
|
||||
if (!fs.existsSync(fullPath)) {
|
||||
throw new Error(`图片文件不存在: ${fullPath}`);
|
||||
}
|
||||
|
||||
return fullPath;
|
||||
}
|
||||
|
||||
if (source.base64) {
|
||||
// Tesseract.js 支持 Base64，需要添加 data URL 前缀
|
||||
const base64Data = source.base64.startsWith('data:')
|
||||
? source.base64
|
||||
: `data:image/png;base64,${source.base64}`;
|
||||
return base64Data;
|
||||
}
|
||||
|
||||
throw new Error('无效的图片来源');
|
||||
}
|
||||
|
||||
/**
|
||||
* 超时包装
|
||||
*/
|
||||
private async withTimeout<T>(promise: Promise<T>, timeout: number): Promise<T> {
|
||||
return Promise.race([
|
||||
promise,
|
||||
new Promise<never>((_, reject) =>
|
||||
setTimeout(() => reject(new Error('timeout')), timeout)
|
||||
),
|
||||
]);
|
||||
}
|
||||
|
||||
/**
|
||||
* 清理识别结果文本
|
||||
*/
|
||||
private cleanText(text: string): string {
|
||||
return text
|
||||
.replace(/\s+/g, ' ') // 多个空格合并为一个
|
||||
.replace(/\n\s*\n/g, '\n\n') // 多个空行合并
|
||||
.trim();
|
||||
}
|
||||
}
|
||||
|
||||
// 导出单例实例
|
||||
export const tesseractProvider = new TesseractProvider();
|
||||
Vendored
+15
@@ -0,0 +1,15 @@
|
||||
// Type declarations for optional tesseract.js dependency
|
||||
declare module 'tesseract.js' {
|
||||
export interface TesseractResult {
|
||||
data: {
|
||||
text: string;
|
||||
confidence: number;
|
||||
};
|
||||
}
|
||||
|
||||
export function recognize(
|
||||
image: string | Buffer,
|
||||
lang: string,
|
||||
options?: { logger?: (m: any) => void }
|
||||
): Promise<TesseractResult>;
|
||||
}
|
||||
@@ -1,7 +1,7 @@
|
||||
{
|
||||
"compilerOptions": {
|
||||
"target": "ES2022",
|
||||
"module": "commonjs",
|
||||
"module": "es2020",
|
||||
"lib": ["ES2022"],
|
||||
"outDir": "./dist",
|
||||
"rootDir": "./src",
|
||||
|
||||
Reference in New Issue
Block a user