Hot Dog

This Flask application lets you upload an image and classifies it as “Hot Dog!” or “Not Hot Dog” using a Hugging Face vision model.

Screenshots

Hot Dog detected

Not Hot Dog detected

Prerequisites

• Python 3.8 or newer
• git (to clone the repository)
• (Optional) CUDA-capable GPU for faster inference

Installation

1. Clone the repository

   git clone https://github.com/your-username/hotdog.git
   cd hotdog

2. Create and activate a virtual environment

   python3 -m venv venv
   source venv/bin/activate

3. Install Python dependencies

   pip install -r requirements.txt

Launching the Web App

You can start the app either via Flask’s CLI or by running the script directly.

Option A: Flask CLI

export FLASK_APP=app.py
export FLASK_ENV=development
export FLASK_RUN_HOST=0.0.0.0
export FLASK_RUN_PORT=8080
flask run

Option B: Direct launch

python app.py

Once the server is running, open your browser to:

http://127.0.0.1:5000

Project Structure

hotdog/
├── assets/                   # Example images for README
├── app.py                    # Flask application
├── requirements.txt          # Python dependencies
├── templates/
│   ├── index.html            # Upload form
│   └── result.html           # Classification result
└── tests/
    ├── __init__.py           # Package marker for tests
    ├── images/               # Sample test images
    └── test_classification.py  # Unittest suite

(Optional) Running the Unit Tests

This runs the real Hugging Face pipeline against your sample images:

python -m unittest discover -v