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license: other
license_name: nutrient-commercial
pipeline_tag: object-detection
language: [en]
tags:
- object-detection
- document-ai
- form-field-detection
datasets:
- nutrientdocs/form-field-v1-benchmark
metrics:
- accuracy
---
# form-field-v1-small · _commercial_
**A compact, high-accuracy form-field detector** — locates `Text`, `Choice` (checkbox/radio), and `Signature`
widgets on **empty, filled, and handwritten** document pages. 8.9M params, ~36 MB; a strong accuracy/size
balance for on-device and edge GPU.
The runnable weights are commercial and are not downloadable from this repository — this public page is the
product specification and scorecard. Prefer a fully open model? See
[`form-field-v1-nano`](https://huggingface.co/nutrientdocs/form-field-v1-nano) (Apache-2.0). Need the highest
accuracy? See [`form-field-v1-medium`](https://huggingface.co/nutrientdocs/form-field-v1-medium).
- 🎯 **Try it:** [form-field-v1-demo](https://huggingface.co/spaces/nutrientdocs/form-field-v1-demo)
- 🏆 **Leaderboard:** [form-field-v1-leaderboard](https://huggingface.co/spaces/nutrientdocs/form-field-v1-leaderboard)
- 📊 **Benchmark:** [form-field-v1-benchmark](https://huggingface.co/datasets/nutrientdocs/form-field-v1-benchmark)
## Results
COCO **mAP50-95** on the [`form-field-v1-benchmark`](https://huggingface.co/datasets/nutrientdocs/form-field-v1-benchmark),
one shared pycocotools scorer across all models.
| Model | Empty | Filled | Handwritten |
|---|---|---|---|
| FFDetr (baseline) | 0.461 | 0.170 | 0.225 |
| **form-field-v1-small** (this model) | **0.456** | **0.716** | **0.680** |
| FFDNet-L (baseline) | 0.373 | 0.285 | 0.285 |
Per-class on empty: Text 0.550 / Choice 0.556 / Signature 0.263. **Throughput:** ~11 pages/sec on a laptop CPU
(ONNX Runtime). Full breakdowns on the
[leaderboard](https://huggingface.co/spaces/nutrientdocs/form-field-v1-leaderboard).
## Output
```json
[ { "box": [82, 164, 336, 41], "type": "Text", "score": 0.91 } ]
```
`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 0.6161 / fp16 0.6134 over all variants).
## Intended use and limits
- Empty, filled, and handwritten digital/scanned forms are all supported.
- On-device / edge GPU target; ~11 pages/sec CPU, faster on GPU.
## License & data
Weights are offered under a commercial Nutrient license. Evaluation is public and reproducible via
[`form-field-v1-benchmark`](https://huggingface.co/datasets/nutrientdocs/form-field-v1-benchmark). The FFDetr
baseline is [FF-DETR / CommonForms](https://huggingface.co/jbarrow/FFDetr) by jbarrow, Apache-2.0.
> ### 📩 Get access
>
> `form-field-v1-small` is commercial and its weights are not downloadable here. To run it on-prem —
> **contact Nutrient: [nutrient.io/contact-sales](https://www.nutrient.io/contact-sales/).**
## About the author
<a href="https://nutrient.io/">
<img src="https://avatars2.githubusercontent.com/u/1527679?v=3&s=200" height="80" />
</a>
This project is maintained and funded by [Nutrient](https://nutrient.io/) - 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.
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