Palabras clave
visión
automatización
monitoreo
cuyes
Categorías
Cómo citar
Resumen
La cría de cuyes en pozas tradicionales representa una actividad ganadera clave en los Andes, pero su monitoreo sigue siendo manual y poco eficiente. En este estudio, proponemos un sistema de detección automática en tiempo real de cuyes (Cavia porcellus) utilizando la arquitectura YOLOv12, entrenado exclusivamente con imágenes capturadas in situ en condiciones reales de cría. A partir de un dataset inicial de 305 imágenes, aplicamos preprocesamiento y aumento de datos para generar 839 imágenes, logrando un modelo con precisión de 0.91, exhaustividad de 0.93, mAP50 de 0.95 y un mAP50-95 de 0.63 en el conjunto de prueba. El modelo demostró alta robustez frente a iluminación variable, oclusiones y fondos complejos, sin generar falsos positivos de fondo. Estos resultados validan la viabilidad de soluciones basadas en visión por computadora para la digitalización accesible de la cuyicultura, con potencial para mejorar el monitoreo del bienestar animal y la gestión productiva en contextos rurales.
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