HumanFaceDetection

The HumanFaceDetection is a small application designed to detect human faces in images using a pre-trained deep learning model. The project leverages several key technologies and frameworks, including Django for the web interface, TensorFlow and MTCNN for deep learning and face detection, and OpenCV and Pillow for image processing. Additionally, the project is containerized using Docker for ease of deployment.

Key Features

Image upload and face detection functionality.
Utilizes a pre-trained deep learning model with TensorFlow and MTCNN.
Web interface built with Django.
Image processing using OpenCV and Pillow.
Containerized application using Docker.

Technologies Used

Django Python Machine Learning Deep Learning OpenCV Pillow TensorFlow Docker MTCNN Computer Vision

Project Links

View Live Code on GitHub

Documentation

Human Face Detection

This is a simple Django application for detecting human faces in images using TensorFlow and MTCNN.

Requirements

Python 3.x
Docker
Docker Compose

Installation

Using Docker

Clone this repository:

git clone https://github.com/portfoliojuanberrios/humanfacedetection.git
cd humanfacedetection

Build and run the Docker containers:
```
docker-compose build
docker-compose up
```
Access the application in your web browser at http://localhost:8011/upload/.

Usage

Upload an image from the upload page.
The application will process the image and indicate if it contains a person.

Project Structure

manage.py: Django management script.
requirements.txt: List of project dependencies.
Dockerfile: Instructions for building the Docker image.
docker-compose.yml: Configuration for Docker Compose.
mi_aplicacion/: Main application folder containing views, forms, and utilities.
- __init__.py: Initializes the application.
- admin.py: Admin site configuration.
- apps.py: Application configuration.
- forms.py: Form for uploading images.
- migrations/: Database migrations.
- models.py: Database models (if any).
- tests.py: Tests for the application.
- urls.py: URL routing for the application.
- utils.py: Utility functions for image processing.
- views.py: View functions for handling requests.
- templates/mi_aplicacion/: HTML templates for the application.
  - result.html: Template for displaying the result.
  - upload.html: Template for uploading images.
humanfacedetection/: Project configuration folder.
- __init__.py: Initializes the project.
- asgi.py: ASGI configuration.
- settings.py: Project settings.
- urls.py: URL routing for the project.
- wsgi.py: WSGI configuration.

Environment Variables

DJANGO_SETTINGS_MODULE: Django settings module (default is humanfacedetection.settings).

Contribution

If you would like to contribute to this project, please fork the repository and submit a pull request.

License

This project is licensed under the MIT License.

Contact

For any inquiries or support, please contact Juan Berrios Moya at info@softdeveloper.com.au.