davidcastagnetoa/skills

yolov8_documents

Clasificar tipo de documento y localizar regiones (foto, MRZ, campos de texto) con YOLOv8 fine-tuned

First seen Mar 6, 2026

Installation

$ npx skills add davidcastagnetoa/skills --skill yolov8_documents

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Repository health

Stars 1
Default branch main
Open issues 0
Status Active

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 1,356 B
  • docs SUMMARY.md 124 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 5 installs

SKILL.md

yolov8_documents

YOLOv8 fine-tuned en documentos de identidad detecta y clasifica el tipo de documento (DNI, pasaporte, permiso de conducir) y localiza las regiones de interés (foto, MRZ, número de documento).

When to use

Usar como paso de clasificación y segmentación del documento, antes de OCR y face extraction.

Instructions

  1. Instalar: pip install ultralytics.
  2. Partir de YOLOv8n o YOLOv8s (nano/small) para balance velocidad/precisión.
  3. Fine-tuning con dataset de documentos de identidad (MIDV-500, MIDV-2020).
  4. Clases a detectar: ['DNIES', 'PASSPORT', 'DRIVINGLICENSE', 'regionphoto', 'regionmrz', 'regionname', 'regiondob', 'region_docnum'].
  5. Entrenar: yolo train data=documents.yaml model=yolov8s.pt epochs=100 imgsz=640.
  6. Exportar a ONNX: yolo export model=best.pt format=onnx.
  7. Cargar en Triton y servir via gRPC.
  8. Post-procesar: extraer crops de cada región detectada para procesamiento específico.

Notes

  • Dataset MIDV-500: https://arxiv.org/abs/1807.05786 (500 tipos de documentos de 75 países).
  • Si el tipo de documento no se reconoce con confianza > 0.7, rechazar o pedir nueva captura.