Image Stitching API (Django, Flask, FastAPI Versions)

Project Overview

This project provides an API that extracts frames from a video, enhances the images using SRCNN (Super-Resolution Convolutional Neural Network), and stitches them into a panoramic image. It is implemented in three versions: Django, Flask, and FastAPI.

Key Features

• Video frame extraction
• Image enhancement using SRCNN (3-layer and 4-layer models)
• Panoramic image stitching
• GPU acceleration support (if available)

Requirements

• Python 3.7+
• OpenCV (cv2)
• PyTorch
• NumPy
• Django / Flask / FastAPI (depending on the chosen version)

Installation and Setup

1. Clone the repository:

   git clone <repository-url>
   cd <repository-directory>
   

2. Install the required packages:

   pip install django flask fastapi opencv-python-headless torch numpy
   

3. repare the SRCNN model files:

   • 3-layer model: MODEL_PATH
   • 4-layer model: MODEL_4LAYER_PATH

Usage

Django

1. Start the server: python manage.py runserver
2. API Endpoints:
   • GET /: Check API status
   • POST /convert/: Upload and process video

Flask

1. Start the server: python app.py
2. API Endpoints:
   • GET /: Check API status
   • POST /convert/: Upload and process video

FastAPI

1. Start the server: uvicorn main:app --host 0.0.0.0 --port 5050
2. API Endpoints:
   • GET /: Check API status
   • POST /convert/: Upload and process video

License

Apache License 2.0