pdf1.8 KB

OCR Domain — Handwritten-print Form (Searchable PDF)

A searchable PDF handwritten-print form with selectable text — the OCR ground-truth twin of the scanned JPEG. Fictional SAMPLE content for measuring OCR accuracy.

OCR testing PDF editor testing

Rendered preview of OCR Domain — Handwritten-print Form (Searchable PDF)

Rendered preview of the pdf file (1.8 KB). Download above for the original.

Specifications

Role: searchable text PDF
Domain: handwritten
Has Text: true
Page Size: US Letter

What is a .pdf file?

PDF (Portable Document Format) is a page-oriented document format that preserves fixed layout, fonts, vector and raster graphics, and text across platforms. It can also embed forms, annotations, attachments, and digital signatures. It is the de facto standard for finished, print-ready documents.

How to use this file

Use an example PDF to test text extraction, rendering, page-count and metadata parsing, form-field handling, and conversion or OCR pipelines.

How to use this file for testing

“OCR Domain — Handwritten-print Form (Searchable PDF)” is a deterministic Novus Examples fixture for OCR testing, PDF editor testing. Image-only 'scanned' documents paired with their text source, for measuring OCR accuracy against a known ground truth.

Documented properties for this file: searchable text PDF. Compare results against paired or grouped companions on this page when present (clean↔damaged, searchable↔scanned, or format twins) so scores stay reproducible across runs.

Download the file once, keep the path stable in CI or local scripts, and treat the spec table as the contract: dimensions, seeds, field lists, and roles are intentional. Corrupt or invalid samples are labelled as such — expect parsers to fail loudly rather than silently accept them.

Document fixtures list their internal structure (pages, fields, tracked changes, embedded objects) in the spec table. Test extractors, converters, and OCR against that known structure, and compare searchable↔scanned or format-twin companions when present.

Run OCR on the scanned or image twin and score the output against the searchable or text ground truth on this page; the documented rotation, grain, and text content are the reference.

Code examples

import pdfplumber  # pip install pdfplumber

with pdfplumber.open("handwritten-searchable.pdf") as pdf:
    print(len(pdf.pages), "pages")
    print(pdf.pages[0].extract_text())

Generated by generation/docs_ocr_wave_b.py. Free for any use, no attribution required — license.