- Introduction
- DISCLAIMER
- Prerequisites
- Installation
- Usage
- Contributing
- Versioning
- License
- Bugs/Issues
The COVID-19 Detection System For Oculus Rift 2020 uses Tensorflow 2, Raspberry Pi 4 & Oculus Rift to provide a Virtual Reality detection system.
The project uses the COVID-19 Tensorflow DenseNet Classifier a Tensorflow implementation of DenseNet and the SARS-COV-2 Ct-Scan Dataset, a large dataset of CT scans for SARS-CoV-2 (COVID-19) identification created by our partners at Lancaster University, Plamenlancaster: Professor Plamen Angelov Centre Director @ Lira, & his researcher, Eduardo Soares PhD.
We use the trained model from COVID-19 Tensorflow DenseNet Classifier with the COVID-19 Tensorflow DenseNet Classifier For Raspberry Pi 4 and serve an API endpoint that exposes the Artificial Intelligence classifier allowing Oculus Rift to communicate with it.
This tutorial and the provided installation guide will allow you to quickly setup the COVID-19 Detection System For Oculus Rift project, however a full tutorial on creating the application from scratch will be published soon.
This project should be used for research purposes only. The purpose of the project is to show the potential of Virtual Reality, Artificial Intelligence, and the Internet of Things for medical support systems such as diagnosis systems.
Although the classifier used in this project is very accurate and shows good results both on paper and in real world testing, it is not meant to be an alternative to professional medical diagnosis.
Developers that have contributed to this repository have experience in using Artificial Intelligence for detecting certain types of cancer & COVID-19. They are not a doctors, medical or cancer/COVID-19 experts. Please use these systems responsibly.
Before you can install the Oculus Rift Unity COVID-19 Detection System, there are some prerequisites.
If you are going to be using the full system you will need to install the HIAS server. Follow the HIAS Installation Guide to complete your HIAS server setup.
If you chose not to use the full system, steps are provided in this tutorial that will allow you to use the system without a HIAS installation.
If you want to train your own Artificial Intelligence required to detect COVID-19, you will need to complete the COVID-19 Tensorflow DenseNet Classifier tutorial. If you would like to use the pre-trained model we have provided, you can skip to the next step.
YOU MUST USE THE SAME TRAIN AND TEST DATA AS THE TUTORIAL SPECIFIES
The test data provided in the Oculus Rift Unity COVID-19 Detection System requires the same model to be used.
The COVID-19 Tensorflow DenseNet Classifier For Raspberry Pi 4 hosts a local server on a RPI4 allowing images to be classified remotely. In this project we use the AI model trained in the COVID-19 Tensorflow DenseNet Classifier, but we also provide the pre-trained model so that you can use the classifier "out of the box".
Regardless of whether you choose to train your own model or use the pre-trained model, you will need to complete the COVID-19 Tensorflow DenseNet Classifier For Raspberry Pi 4 tutorial as this is the project that creates the classifier that the Oculus Rift will interact with.
Please follow the Installation Guide to install Oculus Rift Unity COVID-19 Detection System.
After following the installation guide you should now have all of the required tools installed. Use the following guides to start using the COVID-19 Detection System For Oculus Rift.
Now you need to make sure that your COVID-19 Tensorflow DenseNet Classifier For Raspberry Pi 4 is running in Server mode and waiting for requests.
Now you are ready to fire up the Oculus Rift Unity COVID-19 Detection System!
Head over to Unity and click on the play button. You can remove the cable connection and move to the center of your room. You should now see the Oculus Rift Unity COVID-19 Detection System in your headset.
Now use your controller to hit the blocks by pointing the laser at the blocks. This will send the relevant image to the server for classification.
The server will return the response to the Oculus Rift and the color of the block will change.
- RED Specifies a true positive (COVID-19 positive)
- GREEN Specifies a true negative (COVID-19 negative)
- MAGENTA Specifies a false positive (COVID-19 negative but classifier determined COVID-19 positive)
- CYAN Specifies a false negative (COVID-19 positive but classifier determined COVID-19 negative)
You can reset the application by hitting the RESET button with the laser.
The Peter Moss COVID-19 AI Research Project encourages and welcomes code contributions, bug fixes and enhancements from the Github.
Please read the CONTRIBUTING document for a full guide to forking our repositories and submitting your pull requests. You will also find information about our code of conduct on this page.
- Adam Milton-Barker - Asociacion De Investigacion En Inteligencia Artificial Para La Leucemia Peter Moss President & Lead Developer, Sabadell, Spain
We use SemVer for versioning. For the versions available, see Releases.
This project is licensed under the MIT License - see the LICENSE file for details.
We use the repo issues to track bugs and general requests related to using this project. See CONTRIBUTING for more info on how to submit bugs, feature requests and proposals.