form-field-v1-medium · commercial
The highest-accuracy tier of the form-field-v1 detector family — locates Text, Choice
(checkbox/radio), and Signature widgets on empty, filled, and handwritten document pages. ~34M params,
NMS-free, single-resolution 1216.
The runnable weights are commercial and are not downloadable from this repository — this public page is the
product specification and scorecard. Prefer a small, open model? See
form-field-v1-nano (Apache-2.0).
- 🎯 Try it: form-field-v1-demo
- 🏆 Leaderboard: form-field-v1-leaderboard
- 📊 Benchmark: form-field-v1-benchmark
Results
COCO mAP50-95 on the form-field-v1-benchmark,
one shared pycocotools scorer across all models.
| Model | Empty | Filled | Handwritten |
|---|---|---|---|
| form-field-v1-medium (this model) | 0.529 | 0.783 | 0.764 |
| FFDetr (baseline) | 0.461 | 0.170 | 0.225 |
| FFDNet-L (baseline) | 0.373 | 0.285 | 0.285 |
Per-class on empty (mAP50-95): Text 0.605 / Choice 0.614 / Signature 0.369. On the neutral CommonForms-test it reaches 0.361. Full per-class breakdowns are on the leaderboard.
Output
[ { "box": [82, 164, 336, 41], "type": "Text", "score": 0.94 } ]
box is [x, y, w, h] in page pixels; type ∈ Text, ChoiceButton, Signature. Served as a single-file
ONNX graph (fp32 + fp16), verified to reproduce the benchmark (fp32 mAP 0.6909 / fp16 0.6860 over all variants).
Intended use and limits
- Empty, filled, and handwritten digital/scanned forms are all supported.
- GPU/server model (~57 fps on an A100). For on-device CPU use
form-field-v1-nano/-small. - Very dense pages benefit from higher input resolution.
License & data
Weights are offered under a commercial Nutrient license. Evaluation is public and reproducible via
form-field-v1-benchmark. The FFDetr
baseline is FF-DETR / CommonForms by jbarrow, Apache-2.0.
📩 Get access
form-field-v1-mediumis commercial and its weights are not downloadable here. To run it on-prem, with documents staying in your infrastructure — contact Nutrient: nutrient.io/contact-sales.
About the author
This project is maintained and funded by Nutrient - The deterministic document infrastructure enterprises run their highest-stakes workflows on: replayable output, clear exceptions, and full audit trails on the messy, regulated documents where AI alone breaks.