Abimael MartellandClaude Opus 4.6
843a745460
Two changes that reduce false needsOcr rejections without hurting quality: 1. Per-region GID check instead of per-page blanket rejection. Previously, if ANY font on the page used GID-encoded glyphs (common in logos, decorative fonts), ALL table and text regions on that page were forced to GPU OCR via needsOcr=true. Now the page-level bail is removed; per-region text quality checks (is_garbage_text, is_cid_garbage, detect_encoding_issues) catch actual GID corruption in the extracted content. Tables whose text is clean pass through even if an unrelated font elsewhere on the page is GID-encoded. 2. Relaxed looks_like_partial_table for layout-assisted extraction. When the layout model already identified a region as a table (i.e., extract_tables_in_regions_mem), boundary-detection heuristics are less necessary — we're not guessing "is this a table?" anymore, only "can we extract it correctly?". Relaxations: - Numeric first header cell accepted (e.g., year "2024") - 1 empty header cell allowed in 3+ column tables (merged headers) - Sparse first data row threshold relaxed from 33% to 50% Paragraph detection and duplicate-header checks remain strict. Eval: 196/196 pass (full regression suite), 91/91 Rust tests pass including 7 new layout-assisted validation tests. Zero regressions. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
firecrawl-pdf-inspector
Fast PDF classification and region-based text extraction for Node.js/Bun. Native Rust performance via napi-rs.
Built by Firecrawl for hybrid OCR pipelines — extract text from PDF structure where possible, fall back to OCR only when needed.
Install
npm install firecrawl-pdf-inspector
# or
bun add firecrawl-pdf-inspector
Prebuilt binaries included for linux-x64 and macOS ARM64. No Rust toolchain needed.
API
classifyPdf(buffer: Buffer): PdfClassification
Classify a PDF as TextBased, Scanned, Mixed, or ImageBased (~10-50ms). Returns which pages need OCR.
import { classifyPdf } from 'firecrawl-pdf-inspector'
import { readFileSync } from 'fs'
const pdf = readFileSync('document.pdf')
const result = classifyPdf(pdf)
console.log(result.pdfType) // "TextBased" | "Scanned" | "Mixed" | "ImageBased"
console.log(result.pageCount) // 42
console.log(result.pagesNeedingOcr) // [5, 12, 15] (0-indexed)
console.log(result.confidence) // 0.875
extractTextInRegions(buffer: Buffer, pageRegions: PageRegions[]): PageRegionTexts[]
Extract text within bounding-box regions from a PDF. Designed for hybrid OCR pipelines where a layout model detects regions in rendered page images, and this function extracts text from the PDF structure for text-based pages — skipping GPU OCR.
Each region result includes a needsOcr flag that signals unreliable extraction (empty text, GID-encoded fonts, garbage text, encoding issues).
import { extractTextInRegions } from 'firecrawl-pdf-inspector'
const result = extractTextInRegions(pdf, [
{
page: 0, // 0-indexed
regions: [
[0, 0, 300, 400], // [x1, y1, x2, y2] in PDF points, top-left origin
[300, 0, 612, 400],
]
}
])
for (const region of result[0].regions) {
if (region.needsOcr) {
// Unreliable text — send this region to OCR instead
} else {
console.log(region.text) // Extracted text in reading order
}
}
Types
interface PdfClassification {
pdfType: string // "TextBased" | "Scanned" | "Mixed" | "ImageBased"
pageCount: number
pagesNeedingOcr: number[] // 0-indexed page numbers
confidence: number // 0.0 - 1.0
}
interface PageRegions {
page: number // 0-indexed
regions: number[][] // [[x1, y1, x2, y2], ...] in PDF points, top-left origin
}
interface PageRegionTexts {
page: number
regions: RegionText[]
}
interface RegionText {
text: string
needsOcr: boolean // true when text is unreliable
}
Platforms
| Platform | Architecture | Supported |
|---|---|---|
| Linux | x64 | Yes |
| macOS | ARM64 | Yes |
License
MIT