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This Android application uses Google's ML Kit to identify machinery components at the University of Birmingham's Collaborative Teaching Laboratory. The machine learning models are trained using TensorFlow Lite Model Maker.

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Jack-Development/LabVision

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LabVision

Welcome to the CTL Machine Learning Application project! This is an Android application that leverages Google MLKit to identify components of machinery used within the Collaborative Teaching Laboratory at the University of Birmingham.

The models used in the application are trained using the TensorFlow Lite Model Maker. They are Image Classification models, created using images taken within the labs and labelled with labelImg, created by Tzuta Lin.

Overview 📝

This Android application was designed to aid in the identification of machinery components within the Collaborative Teaching Laboratory (CTL) at the University of Birmingham. With the help of Google's MLKit, we can harness the power of machine learning to achieve our goals.

Features 🎮

  • Identification of machinery components via MLKit
  • Utilizes Image Classification models trained by TensorFlow Lite Model Maker
  • Easy-to-use Android application

Documentation 📚

A detailed breakdown of the development and maintenance of the application can be found in our documentation.

Development 💻

This project was developed using the following tools:

python java gradle ubuntu AndroidStudio TensorFlow MLKit

License 📄

This project is licensed under a custom proprietary license. Please see the LICENSE file for more details.

About

This Android application uses Google's ML Kit to identify machinery components at the University of Birmingham's Collaborative Teaching Laboratory. The machine learning models are trained using TensorFlow Lite Model Maker.

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