Abimael MartellandClaude Opus 4.7
79d75dbdca
Some catalog and archival-finding-aid tables draw each row's horizontal rule as N segments (one segment per cell) with no vertical lines at all. The previous detector rejected these outright at `verticals.len() < 2`, even though the segment break points encoded the column boundaries unambiguously. When the vertical-line count is below the existing threshold, walk the horizontal-segment x-endpoints and cluster them with the same snap_edges path used for vertical-line columns. Accept the derived edges only when ≥3 distinct x-positions each appear on ≥50% of the unique horizontal-line rows — that consistency guard distinguishes real per-cell segments from decorative rules with varying widths (which never share endpoints across many rows). When columns come from segment endpoints, skip the downstream "spanning_v / partial_v" gate (there are no vertical lines to validate against). All other gates — horizontal-span coverage, content density, capture ratio, multi-column distribution, the uniform-spacing chart-grid rejector — still apply. Verified on a 7-row × 3-col archival catalog page that previously extracted 98 chars (a 2-row fragment via the heuristic fallback); now extracts 1754 chars with all rows + multi-line cells. Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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