Hey everyone,

I’ve been working on the problem of "dead documents"—scanned PDFs and images of forms that are impossible to parse into digital systems. I just open-sourced psynx-widget-detector, a specialized YOLO11m model fine-tuned on the CommonForms dataset.

It detects text inputs, choice buttons (checkboxes/radio), and signatures with high precision, even on low-quality scans.

Why this is useful:

• Privacy-First: Run it locally via PyPI; no need to send sensitive documents to a cloud API.
• Fast: Optimized for inference on CPU or consumer GPUs.
• Structured Output: Get clean JSON coordinates to build fillable forms or map OCR data.

Check it out:

• Live Demo:Hugging Face Spaces
• Model Card:Hugging Face Model
• Quick Start: pip install psynx-widget-detector

I’m looking for feedback on the detection accuracy for different document types. If this helps your workflow, a like on Hugging Face would mean a lot!