https://github.com/wsdt/malignantbirthmarkrecognition_backend

Backend (Kotlin) for malignant birthmark recognition.
https://github.com/wsdt/malignantbirthmarkrecognition_backend

Last synced: 6 days ago
JSON representation

Backend (Kotlin) for malignant birthmark recognition.

• Host: GitHub
• URL: https://github.com/wsdt/malignantbirthmarkrecognition_backend
• Owner: wsdt
• License: gpl-3.0
• Created: 2019-03-01T21:37:00.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2022-06-29T18:53:55.000Z (over 2 years ago)
• Last Synced: 2023-03-11T07:07:51.389Z (over 1 year ago)
• Language: Kotlin
• Homepage:
• Size: 145 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# Malignant Birthmark Recognition 

## Backend [![Maintenance](https://img.shields.io/badge/Maintained%3F-no-red.svg)](https://bitbucket.org/lbesson/ansi-colors) [![Generic badge](https://img.shields.io/badge/In-KOTLIN-ORANGE.svg)](https://kotlinlang.org/) [![GitHub license](https://img.shields.io/github/license/wsdt/MalignantBirthmarkRecognition_Backend.svg)](https://github.com/wsdt/MalignantBirthmarkRecognition_Backend/blob/master/LICENSE) [![Generic badge](https://img.shields.io/badge/Docker-Compatible-blue.svg)](https://www.docker.com/) [![Donate](https://img.shields.io/badge/Donate-Pay%20me%20a%20coffee-3cf)](https://github.com/wsdt/Global/wiki/Donation) [![saythanks](https://img.shields.io/badge/say-thanks-ff69b4.svg)](https://saythanks.io/to/kevin.riedl.privat%40gmail.com)

Kotlin Backend to serve user requests for [MalignantBirthmarkRecognition_Frontend](https://github.com/wsdt/malignantbirthmarkrecognition_frontend).

### Training

The Backend uses Transfer Learning and the pre-trained model VGG with 16 layers from Oxford University. 

I provided a small shell script to make enlarge the java virtual machine boundaries to avoid OutOfMemoryExceptions. 

### Prediction

The backend provides only a single http-post-route to upload a image. This image is then classified by the 

convolutional neural network and will return a json-array with all confidence-rates. 

### Docker

This application will be dockerized soon. Please be patient. 

### Attribution

This project was inspired and is based on the [Cat and Dog Recognizer by Klevis](https://github.com/klevis/CatAndDogRecognizer). 

### Open-Source

This application is open source. Please see the current license. 

#### Pull-Requests

... are always welcome!