Abimael Martell
8b63ceb084
* emit ItemType::Image bboxes for Image XObjects (was: silently dropped)
Background. ItemType::Image, MarkdownOptions::include_images, and the
markdown emitter's image-collection path have all been in the tree
for a while, but no producer ever populated them — content_stream.rs
explicitly `// Skip images — text extraction only` at the Do
operator, and the nested Form-XObject walker in xobjects.rs only
matched XObjectType::Form, silently dropping Image entries. The
declared types were dead code.
This PR lights them up. At every Do that resolves to an Image
XObject (both top-level and nested inside Form XObjects), we now
compute the page-space bbox from the current CTM via a new
`image_bbox_from_ctm` helper — handling both axis-aligned and
rotated/sheared placements via 4-corner AABB — and emit a TextItem
with `item_type: ItemType::Image` and the legacy `[Image: <name>]`
text payload that the markdown emitter already knows how to render.
Callers can now find raster figures via `extract_text_with_positions`
(and the `_mem` variant, newly re-exported at the crate root) without
needing to re-parse the PDF or run a vision/layout model. The intended
consumer is layout-aware text pipelines that want to crop figures and
caption them out-of-band.
Two backstops to avoid silent breakage for existing callers:
1. `MarkdownOptions::include_images` default flipped `true → false`.
If it stayed at `true`, every existing user of
`extract_pages_markdown` would suddenly see ``
placeholders inserted throughout their output the moment they
upgraded. Image data is still available structurally via
`extract_text_with_positions`; rendering it into markdown is now
an opt-in. New regression test asserts `extract_pages_markdown`
output is unchanged for the image-bearing fixture.
2. Image items now also skip the layout heuristics
(`detect_columns`, `detect_tables_from_rects`) via a new
`is_text_layout_item` predicate. Without this filter, an image's
left edge would land in the column-projection profile and skew
table column detection — surfaced by
`vector_grid_tests::upstage_key_functions_four_cols` going from 4
detected columns to 5 in CI before the filter was added.
Re-exporting `extract_text_with_positions_mem` at the crate root —
strictly additive; mirrors how `extract_pages_markdown_mem` is already
available there.
Tests:
- test_extract_text_with_positions_emits_image_bboxes — minimal PDF
with one 200×100 image at (50, 600); asserts one Image item with
correct bbox + page + text.
- test_image_xobject_bbox_handles_rotated_ctm — 90° rotated image
via shear-component CTM; asserts AABB is correct (handles non-
axis-aligned placements via 4-corner clamp).
- test_image_emission_does_not_change_default_markdown — asserts no
`Image:` token leaks into default markdown output, regression
guard for the include_images flip.
- test_markdown_options_default_has_include_images_false — explicit
sentinel so anyone flipping it back catches it in CI.
* Bump version from 1.8.15 to 1.9.0
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