Humin-Trait-Analysis

This repository contains a Python-based project with several components including an application script, upload functionality, and machine learning model.

Project Structure

• app.py: Main application script.
• upload.py: Script for handling file uploads.
• fairface.pt: Pre-trained model file.
• prediction.json: JSON file for storing predictions.
• requirements.txt: Python dependencies.
• Dockerfile: Docker configuration for containerizing the application.
• .dockerignore and .gitignore: Ignore files for Docker and Git.

Setup

1. Create a virtual environment and activate it:

   python -m venv .venv
   .\.venv\Scripts\activate

2. Install dependencies:

   pip install -r requirements.txt

Usage

• Run the main application:

  python app.py

• Use upload.py to handle file uploads.

Docker

Build and run the Docker container:

docker build -t new-test-app .
docker run -p 8000:8000 new-test-app

Notes

• The project uses a pre-trained model fairface.pt for predictions.
• prediction.json stores the output predictions.

Project Explanation and Functionality

This project is a Python-based facial analysis application that leverages a pre-trained machine learning model to analyze images. The main functionalities include:

• Handling image uploads through the upload.py script.
• Processing uploaded images using the pre-trained model fairface.pt to predict facial attributes such as age, gender, and ethnicity.
• Storing the prediction results in prediction.json for further use or display.
• The main application logic is contained in app.py, which coordinates the workflow and serves as the entry point.
• The project supports containerization via Docker for easy deployment.

This setup allows users to upload images, have them analyzed automatically, and retrieve the results efficiently.