https://github.com/row-huh/malamaai
MalamaAI detects skin diseases using ml model based off of dinov2 deployed on a webapp built with Next.js and Flask, it also uses Llama 3.370b model for accurate analysis.
https://github.com/row-huh/malamaai
ai dinov2 flask llama3 ml nextjs
Last synced: about 1 month ago
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MalamaAI detects skin diseases using ml model based off of dinov2 deployed on a webapp built with Next.js and Flask, it also uses Llama 3.370b model for accurate analysis.
- Host: GitHub
- URL: https://github.com/row-huh/malamaai
- Owner: row-huh
- License: mit
- Created: 2024-12-01T08:42:12.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2024-12-24T11:12:52.000Z (5 months ago)
- Last Synced: 2025-04-30T03:49:17.397Z (about 1 month ago)
- Topics: ai, dinov2, flask, llama3, ml, nextjs
- Language: TypeScript
- Homepage:
- Size: 6.93 MB
- Stars: 0
- Watchers: 1
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.MD
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README
# MalamaAI Team
Hassan Mehmood
Roha Pathan
Joy Chris-Odai Nkor
![Okey Amy]()
Okey Amy
# MalamaAI
MalamaAI is a machine learning-powered application designed to recognize various skin diseases using advanced AI models. The name "Malama" is a Hawaiian word that means 'to care for,' reflecting the project's mission to provide care through technology. This project employs the LLM 3.370b model, built on top of a fine-tuned version of Dinov2, enhancing its accuracy and reliability in disease recognition.
## Features
- **Interactive Frontend:** Built with **Next.js** for speed and interactivity.
- **Scalable Backend:** Powered by **Flask**, supporting RESTful API integration.
- **Enhanced Model:** Utilizes LLM 3.370b on top of a fine-tuned version of Dinov2 for improved accuracy.
## Project Structure
```plaintext
MalamaAI/
│
├── Frontend/ # Contains the Next.js frontend
│ ├── app/ # Next.js application
│ ├── components/ # Reusable components
│ ├── svgs/ # SVG assets
│ ├── .gitignore # Git ignored files
│ ├── next.config.mjs # Next.js configuration
│ ├── package-lock.json # Locked versions of dependencies
│ ├── package.json # Frontend dependencies and scripts
│ ├── postcss.config.mjs # PostCSS configuration
│ ├── README.md # Frontend documentation
│ ├── tailwind.config.ts # Tailwind CSS configuration
│ └── tsconfig.json # TypeScript configuration
│
├── webapp/ # Flask backend application
│ ├── __pycache__/ # Compiled Python files
│ ├── static/ # Static files for Flask
│ ├── templates/ # HTML templates for rendering
│ ├── app.py # Main API logic
│ ├── model.py # Model definition and training logic
│ ├── .gitignore # Git ignored files
│ ├── MalamaAi.pptx # Presentation (overview of the project)
│ ├── README.md # Backend documentation
│ └── requirements.txt # Backend dependencies
```
## Getting Started
### Prerequisites
- **Node.js** (for frontend development)
- **Python 3.8+** (for backend)
- **pip** (to install Python dependencies)
### Installation
1. **Clone the repository:**
```bash
git clone https://github.com/row-huh/MalamaAI.git
cd MalamaAI
```
2. **Set up the backend:**
```bash
cd webapp
pip install -r requirements.txt
```
3. **Set up the frontend:**
```bash
cd ../Frontend
npm install
```
4. **Run the application:**
- **Backend:** Start the Flask server:
```bash
python app.py
```
- **Frontend:** Start the Next.js server:
```bash
npm run dev
```
5. Open the application in your browser at `http://localhost:3000`.