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📸🎬 Django Image & Video Enhancement System

A full-stack Django application that allows users to register, upload images and videos, and automatically enhance their quality using OpenCV, PIL, MoviePy, and NumPy. The system supports:

  • User authentication (register, login, logout)
  • Image enhancement (upscaling, denoising, sharpening, color boost)
  • Video enhancement (frame-by-frame processing + audio preservation)
  • Media management (upload, list, delete)
  • Per-user image & video library

This README explains the setup, features, project structure, and usage.

🚀 Features

🔐 Authentication

  • User registration
  • Login & logout
  • Login-required protection for media pages

📸 Image Enhancement Pipeline

Every image uploaded goes through:

  1. Upscaling (×3 using Lanczos interpolation)
  2. Denoising (Bilateral filter)
  3. Sharpening (Unsharp mask)
  4. Contrast & brightness adjustment
  5. Color saturation enhancement
  6. Saves both original & high-quality versions

🎬 Video Enhancement Pipeline

Each frame is processed using the following:

  1. Upscaling (×3)
  2. Denoising for small frames
  3. Sharpening
  4. Brightness & contrast improvement
  5. Color enhancement
  6. Audio preserved using MoviePy

📁 User Media Dashboard

  • List all your images
  • List all your videos
  • View enhanced results
  • Delete media

📦 Tech Stack

Area Technology
Backend Django
Media Processing OpenCV, Pillow, NumPy, MoviePy
Frontend HTML, CSS, JavaScript (AJAX JSON response)
Database SQLite / PostgreSQL
Authentication Django Auth System

📂 Project Structure (Relevant Parts)

your_project/
│
├── media/                  # Stores uploaded and enhanced media
│
├── app_name/
│   ├── models.py           # UploadedImage & UploadedVideo models
│   ├── views.py            # (Your provided code)
│   ├── forms.py
│   ├── urls.py
│   ├── templates/
│       ├── index.html
│       ├── login.html
│       ├── register.html
│       ├── home.html
│       ├── video_home.html
│       ├── upload.html
│       ├── upload_video.html
│
└── requirements.txt

⚙️ Installation & Setup

1. Clone the Repository

git clone https://github.com/yourusername/yourrepo.git
cd yourrepo

2. Create and Activate Virtual Environment

python3 -m venv venv
source venv/bin/activate   # Linux/Mac
venv\Scripts\activate      # Windows

3. Install Dependencies

pip install -r requirements.txt

Required packages include:

Django
opencv-python
pillow
numpy
moviepy
scikit-image

4. Apply Migrations

python manage.py migrate

5. Create Superuser (optional)

python manage.py createsuperuser

6. Run Development Server

python manage.py runserver

Visit:

http://127.0.0.1:8000/

🖼️ Image Enhancement Flow

When a user uploads an image:

  1. Stored temporarily
  2. Enhanced using:
upscale_image(image, scale_factor=3)
apply_denoising(image)
apply_sharpening(image)
adjust_contrast_brightness(image)
enhance_color(image)

  1. Saved as:

    original_image.jpg
high_quality_original_image.jpg

  2. Returns JSON:

{
  "original_image_url": "...",
  "high_quality_image_url": "..."
}

🎬 Video Enhancement Flow

Video is processed frame by frame:

  1. Extract each frame with OpenCV
  2. Enhance with same pipeline as images
  3. Save enhanced video (temporary)
  4. Add original audio using MoviePy
  5. Save as:
original.mp4
high_quality_original.mp4

🔧 API Endpoints

Image Endpoints

URL Method Description
/upload/ POST Upload & enhance image
/home/ GET List user images
/delete-image/<id>/ POST Delete image

Video Endpoints

URL Method Description
/upload-video/ POST Upload & enhance video
/video-home/ GET List user videos
/delete-video/<id>/ POST Delete video

Authentication

URL Description
/register/ Create account
/login/ Login
/logout/ Logout

💾 Models Summary

UploadedImage

  • user
  • original_image
  • high_quality_image
  • uploaded_at

UploadedVideo

  • user
  • original_video
  • high_quality_video
  • uploaded_at

🛡️ Authentication & Security

  • Uses Django built-in auth system
  • CSRF protection enabled except AJAX upload
  • Access to images/videos is user-restricted

🔮 Future Improvements (Optional)

  • Add progress bar during enhancement
  • Support batch processing
  • Integrate WebSockets for real-time progress updates
  • Add AI-based super resolution (ESRGAN)

📜 License

MIT License — free to use, modify, and distribute.