Image Upscaling Using CNN

This project implements a simple web application for upscaling images using a Convolutional Neural Network (CNN). The application is built using Flask, a micro web framework for Python. The image upscaling is performed using a pre-trained CNN model.

Prerequisites

Before running the application, ensure you have the following dependencies installed:

• Python (>= 3.9)
• Flask
• TensorFlow
• OpenCV (cv2)
• Pillow (PIL)
• Werkzeug

Install the required packages using the following command:

pip install requirements.txt

Usage

1. Clone the repository:

git clone https://github.com/yourusername/image-upscaling-cnn.git
cd image-upscaling-cnn

2. Run the Flask application:

python app.py

3. Open your web browser and go to http://localhost:5000/ to access the application.

How It Works

1. Model Loading:

   • The Flask application loads a pre-trained image upscaling model (image_upscale_model) using TensorFlow.

2. Image Processing:

   • When an image is uploaded through the web interface, the application processes the image using the loaded model.

3. Image Upscaling:

   • The model performs upscaling on the input image, converting it to a higher resolution.

4. Display Results:

   • The original and processed images are displayed on the web interface.

File Structure

• app.py: The main Flask application script.
• models/: Directory containing the pre-trained image upscaling model.
• static/: Directory for static files (CSS, JavaScript, etc.).
• templates/: HTML templates for rendering web pages.

Configuration

• ALLOWED_EXTENSIONS: Set of allowed file extensions for image uploads ({'png', 'jpg', 'jpeg'}).
• app.secret_key: Flask secret key for session management. Replace with a secure secret key.

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