AcroMELD

Turns a flat PDF into a fillable form. Give it a PDF that looks like a form but has no form fields, and it finds every field and writes a real, clickable AcroForm.

acromeld input.pdf output.pdf

The first run downloads the model (158 MB) from Hugging Face and caches it. CPU is the default and works fine; a page takes a few seconds.

From Python:

from acromeld import prepare_form

prepare_form("input.pdf", "output.pdf")

Options

What it detects

Three field types — Text, Choice, Signature — plus a learned link that merges several visual candidates into one field instead of emitting duplicates. It reads two channels at once: the rendered page, and the PDF's own drawing primitives, which a purely visual detector ignores. 39.4M parameters, up to 896 fields per page.

How well it works

Measured once on a sealed holdout of 1,996 PDFs / 6,843 pages the model never saw during training, against a threshold registered before training started: containment micro-F1 0.84767 against a required 0.82904 — passed.

Read this before using it:

• Signature detection does not work. At the calibrated threshold the model predicts essentially no signature fields. Text and Choice carry the entire score.
• Under a stricter IoU/COCO adapter the same model reaches only 0.28996 mAP, below a locally evaluated CommonForms-L reference.
• Measured on German-language forms. Other languages and layouts are untested.
• Rotated pages are rejected rather than silently misplaced.
• One sealed run, one seed. No stability claim.

This is a research artifact, not a product.

Licence

Apache-2.0. Vendored third-party components and their modifications are listed in THIRD-PARTY-NOTICES.md in the source distribution.