shakibyzn / image-time-classifier-app

Image Time Classifier App with FastAPI and Streamlit

This is an image classification app designed to determine the time of day using the CLIP model, specifically the ViT-B/32 variant from torchvision. Users can easily upload an image, and the app will classify it into one of the following time categories: 'morning,' 'noon,' 'afternoon,' 'night,' or 'sunrise or sunset.' The app utilizes FastAPI for handling backend functionalities and Streamlit for a straightforward user interface. Docker and Docker Compose are employed for easy deployment and management of the application.

Requirements

• Python 3.6 or higher
• FastAPI
• Streamlit
• Torch
• Pillow
• Redis OM
• Matplotlib
• Requests

Installation

1. Clone the repository:

   git clone https://github.com/shakibyzn/image-time-classifier-app.git
   

2. Navigate to the project directory:

   cd image-time-classifier-app
   

Usage

docker compose up --build -d

Demo

License

This project is licensed under the MIT License.