Add OCR routing integration guide with confidence threshold and Mixed-PDF handling examples

[yulinlina]

Description

pdf-inspector advertises smart classification and per-page OCR routing, but the README does not currently provide clear guidance on how users should interpret the confidence score, choose a threshold, or handle Mixed PDFs in production workflows.

A dedicated integration guide would help users make reliable routing decisions such as:

• When a PDF can be processed locally without OCR.
• When specific pages should be sent to an OCR service.
• How to handle low-confidence or mixed-content documents.
• What thresholds are reasonable for different use cases.

Motivation

One of the main goals of this library is to help applications skip expensive OCR services for PDFs that do not need them. However, in real-world integrations, users need more than the raw classification output.

For example, developers may have questions like:

• Is a confidence score of 0.65 safe to treat as text-based?
• Should Mixed documents always trigger OCR?
• How should per-page routing results be combined with external OCR providers?
• What happens if text extraction succeeds but the confidence is low?
• Should the threshold be stricter for archival workflows versus search indexing?

Without documented guidance, users may choose inconsistent thresholds, accidentally route too many pages to OCR, or incorrectly treat scanned/mixed PDFs as fully text-based.

Proposed Solution

Add a documentation page such as docs/ocr-routing.md that explains how to use the classification and routing APIs effectively.

The guide could include:

1. Explanation of classification results

   • TextBased
   • Scanned
   • ImageBased
   • Mixed
   • Meaning of confidence scores
   • Meaning of per-page routing decisions

2. Recommended default thresholds

   • Example: high-confidence text-based processing
   • Example: conservative OCR fallback
   • Example: balanced cost/accuracy mode

3. Language-specific examples

   • Rust
   • Python
   • Node.js
   • WebAssembly, if applicable

4. Common routing patterns

   • Process locally if confidence is above threshold.
   • Send only selected pages to OCR.
   • Fall back to full-document OCR for low-confidence or mixed PDFs.
   • Combine pdf-inspector with external OCR providers.

5. Edge cases and caveats

   • Password-protected PDFs
   • PDFs with embedded images but extractable text
   • Poor-quality scans
   • Mixed pages containing both text and images
   • Documents where text extraction succeeds but reading order is unreliable

6. Optional helper pattern

   • A small example utility such as should_use_ocr(page_result, threshold) could be included in documentation without necessarily changing the core API.

Alternatives Considered

• Leave the current API as-is and expect users to infer routing behavior from the raw fields.
• Add a higher-level routing API inside the library, but that may be a larger design decision.
• Provide examples only in the README, though a dedicated guide would be easier to maintain and discover.

A documentation-first approach is low-risk, improves developer experience, and helps users get value from the existing classification features without requiring breaking API changes.

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[thompsoncrystal038]

⚙️ 读写分离场景注意点有哪些

[hansenisaac8461]

无障碍方面有考虑过吗 😄😄

[yulinlina]

有考虑，而且我觉得应该作为这个 integration guide 的一部分。对无障碍场景来说，confidence 不只是“要不要 OCR”的成本信号，还要判断最终产物是否能被屏幕阅读器、搜索、复制、辅助技术正常消费。

我建议在指南里加入一个 Accessibility / 无障碍处理 小节，至少覆盖这些点：

• 低置信度不能只依赖本地解析：即使 pdf-inspector 能提取到少量文本，如果 confidence 较低或页面被判定为 Mixed，对无障碍场景仍应路由到 OCR，生成真实文本层。
• Mixed PDF 建议更保守：如果文档用于用户阅读、教育、政务、医疗等场景，Mixed 不应简单跳过 OCR，最好按页 OCR 或整文档进入可访问性增强流程。
• 输出不能只是 searchable PDF：无障碍场景最好要求 tagged PDF、PDF/UA，或转换为结构化 HTML/Markdown，并保留标题、列表、表格、语言信息和阅读顺序。
• 图片和公式需要额外处理：纯扫描页、图表、公式、印章、手写内容可能需要 OCR + layout analysis，必要时加人工审核。
• 阈值应该按用途区分：搜索索引可以宽松一些，例如 0.65；但无障碍阅读、合规归档、法律文档建议更严格，例如 0.85 以上。

可以给指南加一个示例策略：

type RoutingPolicy = {
  accessibility: {
    minConfidence: number;
    mixed: "ocr" | "review" | "skip";
    lowConfidenceText: "review" | "ocr";
  };
};

const policy: RoutingPolicy = {
  accessibility: {
    minConfidence: 0.85,
    mixed: "ocr",
    lowConfidenceText: "ocr",
  },
};

function routeForAccessibility(page: PageInspectionResult) {
  if (page.confidence >= policy.accessibility.minConfidence) {
    return "local-text";
  }

  if (page.classification === "Mixed") {
    return "ocr-with-tagging";
  }

  return "ocr-with-review";
}

另外可以提醒用户：“能提取文本” 不等于 “可访问”。如果 PDF 没有 tag、阅读顺序错误、扫描页没有 ActualText，辅助技术仍然可能读不出来。这个点放进指南里会很有价值。

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[dunncharles0112]

👍 对标竞品差异点能列一下吗

[wellsashley00]

🙌 异步写法很干净，学习了

[yulinlina]

+1。这里确实值得把“异步路由”写进指南：生产环境不建议逐页 await，更好的模式是：

1. 先拿到所有页面的 inspection 结果；
2. 根据 confidence / classification 做路由分桶；
3. 对需要 OCR 或人工审核的页面并发提交；
4. 用 Promise.allSettled 收集结果，避免单页失败拖垮整个 PDF 处理任务。

可以给指南补一个这样的示例：

type PageRoute = "local" | "ocr" | "review";

type PageInspectionResult = {
  pageNumber: number;
  classification: "Text" | "Scanned" | "Mixed";
  confidence: number;
};

type RoutingPolicy = {
  minConfidence: number;
  mixed: PageRoute;
  lowConfidenceText: PageRoute;
};

function routePage(page: PageInspectionResult, policy: RoutingPolicy): PageRoute {
  if (page.confidence >= policy.minConfidence && page.classification === "Text") {
    return "local";
  }

  if (page.classification === "Mixed") {
    return policy.mixed;
  }

  if (page.classification === "Text") {
    return policy.lowConfidenceText;
  }

  return "ocr";
}

async function routePdfForOcr(
  pages: PageInspectionResult[],
  policy: RoutingPolicy,
) {
  const routes = pages.map(page => ({
    page,
    route: routePage(page, policy),
  }));

  const ocrJobs = routes
    .filter(({ route }) => route === "ocr")
    .map(({ page }) => submitPageToOcr(page.pageNumber));

  const reviewJobs = routes
    .filter(({ route }) => route === "review")
    .map(({ page }) => queueForHumanReview(page.pageNumber));

  const [ocrResults, reviewResults] = await Promise.all([
    Promise.allSettled(ocrJobs),
    Promise.allSettled(reviewJobs),
  ]);

  return { routes, ocrResults, reviewResults };
}

对于无障碍场景，可以把策略设得更保守一些：

const accessibilityPolicy: RoutingPolicy = {
  minConfidence: 0.85,
  mixed: "ocr",
  lowConfidenceText: "review",
};

生产环境还建议加并发限制、重试和审计日志，方便后续根据真实文档分布调整阈值。我可以提一个 PR，把这段异步路由示例、阈值建议和无障碍策略一起补到 integration guide 里。

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[yulinlina]

📦 Follow-up: the promised pull request is now open → #261

Happy to iterate on it based on your feedback.

[wellsashley00]

🧠 消息队列至少一次还是恰好一次

[dunncharles0112]

🧪 时钟漂移对签名校验影响大吗

[harveysamuel99]

⭐ 萌新刚开始造轮子，有没有入门建议

[harveysamuel99]

标注规范有没有简版说明 ✨🛠️📦

[yulinlina]

有，可以先用这个“最小可用标注规范”来统一指南和示例：

type PageLabel = {
  page: number;
  classification: "text" | "scanned" | "mixed";
  confidence: number; // 0-1
  route: "local" | "ocr" | "review";
  reason:
    | "high_conf_text"
    | "low_conf_text"
    | "mixed_policy"
    | "scanned"
    | "text_length_low"
    | "manual_override";
};

类别定义可以简化为：

• text：页面主要由可提取文本层组成。
• scanned：页面主要是图像，缺少有效文本层。
• mixed：同一页既有可提取文本，又有可能需要 OCR 的图像内容。

路由标注建议：

• local：Text 且 confidence >= threshold，并且本地抽取文本长度达到最低要求。
• ocr：Scanned，或 Mixed 按业务策略要求 OCR，或低置信度 Text 但业务要求高准确率。
• review：低置信度但 OCR 成本较高，或 Mixed 只需要部分文本，或出现“高置信但文本长度异常低”等情况。

策略示例可以写成：

const archival = {
  minConfidence: 0.9,
  mixed: "ocr",
  lowConfidenceText: "ocr",
};

const searchIndex = {
  minConfidence: 0.75,
  mixed: "ocr",
  lowConfidenceText: "review",
};

const triage = {
  minConfidence: 0.6,
  mixed: "review",
  lowConfidenceText: "review",
};

标注示例：

{
  "page": 7,
  "classification": "mixed",
  "confidence": 0.58,
  "route": "ocr",
  "reason": "mixed_policy"
}

如果是做评测集，建议额外记录 human_class 和 expected_routes，其中 expected_routes 可以是多个值，因为同一页在归档、搜索、低成本预览不同场景下可接受的路由可能不同。最好再补一个 text_length 或 chars_per_page，用来识别“confidence 很高但实际没抽到有效文本”的边界情况。

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[blackwellmiranda8]

训练/推理脚本分开维护了吗 🔥🚀🙌

[hansenisaac8461]

🚀 和 monorepo 一起用有坑吗