Skip to content

MalinduLiyanage/Wastu_AI_ObjectDetector_App_v1.0

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

5 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Wastu App v1.0

logo

A simple Java based Android app with TensorflowLite, SQLite, OpenStreetMap and SharedPreferences

*By Malindu Liyanage

Screenshots

Image 1 Image 2 Image 3 Image 4 Image 5 Image 6 Image 7 Image 8 Image 9 Image 10 Image 11 Image 12

Overview

The App uses Tensorflow Lite Object detection model based on YOLO v5 to get predictions. Basically the model is capable to recognize about 42 object classes. The app has a built in SQLite DB that stores data within the device. There is no any internet based DB here, all the operations are done in locally.

Features

  1. Uses Tensorflow Lite Object detection model to detect objects.
  2. Able to take inputs from Camera and Gallery, and toggle between these modes quickly.
  3. Model parameters can be adjusted to get a good prediction.
  4. Detections can be saved and see them inside the App.
  5. Detections can be compared with the base image.
  6. For images captured through Camera, Location data is saved and can be retrieved through the app itself.
  7. Uses sharedpreferences to save model parameters.
  8. SQLite DB is used to track info about detections.
  9. The UI updates with every DB update
  10. Activity Lifecycle management
  11. Modern UI + App icons
  12. Permission Manager for getting permissions

References

The pretrained model from this repo is used in this project. Click here to visit there

Last update

2024.05.14

About

This app is a development assignment for Mobile App development course. Faculty of Applied Sciences, Rajarata University of Sri Lanka.

About

Wastu is a java based Android Application that uses Tensorflow Lite AI model to detect objects by using Camera or images stored in storage of the device.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors

Languages