Abimael MartellandClaude Opus 4.6
7c8b09be67
* fix: improve heuristic table detection for numeric columns and multi-line headers Two fixes for tables that have clean extractable text but fail heuristic structure detection: 1. Numeric column merge pass (grid.rs): After initial X-position clustering, adjacent clusters are merged when one is sparse (header text) and the other is dense with >50% numeric items (data column). Multi-line wrapped headers often land slightly offset from their data column — the merge closes gaps within 1.5× the clustering threshold. New is_numeric_text() helper matches decimals, percentages, negative numbers, and comma-separated thousands. 2. Duplicate-header skip (detect_heuristic.rs): Spanning super-headers like "First Degree | First Degree | Higher Degree" contain duplicate cells that trigger looks_like_partial_table_ex rejection. Now skips rows with duplicate cells when a better header candidate exists within the next 3 rows (higher fill ratio or numeric cells). Tested on BITS Pilani university report (430 pages, 314 table pages). Page 4 (multi-line header + numeric data) previously returned needs_ocr=true; now correctly detects the table structure. Eval: 197 PDFs, zero regressions, all 104+ tests pass, zero clippy. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * bump version to 0.7.1 --------- 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