/RealTimeObjectDetection

Primary LanguageSwiftMIT LicenseMIT

KeepCoding - Práctica de Machine Learning / Machine Learning practical exercise

Swift Version License: MIT

Objetivos principales

El objetivo principal es poner en practica el todo lo aprendido relacionado con Machine Learning y CoreML. Se trata de una aplicación que reconoce objetos random y es capaz de nombrarlos/clasificarlos.

  • Aprender y asentar las bases de Core ML y Machine Learning en general
  • Practicar todo lo posible relacionado con la creación de UI por codigo.
  • Aplicar arquitecturas de codigo como MVVM.
  • El codigo debe tener como base los comceptos de programación SOLID.

Main goals

The main goal of this exercise, is to put into practice Machine Learning and Core ML course. This app recognises random objects and is able to name/classify them.

  • Learn and reinforce Machine Learning and Core ML basics.
  • Put on practice as much as possible how to create UI by code.
  • Apply code design patterns such as MVVM.
  • The code should be based on SOLID programming principles.

Samples

APP NOT FINISHED YET...

¡ATENCION!
Para poder probar esta aplicacion, debes instalar manualmente el modelo Yolov3

ATTENTION!
To play around with this example you should install Yolov3 model manually

https://developer.apple.com/machine-learning/models/





Este es un proyecto de puesta en practica del BootCamp Full Stack Mobile de KeepCoding. No representa ningun beneficio comercial.
This is a learning project from KeepCoding Full Stack Mobile BootCamp. For this project there is no commercial benefits.

Author

Check my LinkedIn profile to know more about me. Feel free to contact for any question.

Rodrigo Candido