# STOP Sign Identification App

This Gradio application identifies whether an image contains a STOP sign or not using an AutoGluon Multimodal predictor.

## How to Use

1.  **Upload an Image:** You can upload an image from your computer or use your webcam.
2.  **Select an Example:** Choose one of the provided example images to quickly test the application.
3.  **Apply Preprocessing:** The "Apply Preprocessing" checkbox controls whether the input image is resized and converted to RGB before being fed to the model. By default, preprocessing is applied.
4.  **View Results:** The application will display:
    *   The original uploaded image.
    *   The preprocessed image (if preprocessing is applied).
    *   The predicted class probabilities ("Not a STOP sign" and "STOP sign").

## Model

The application uses a pre-trained AutoGluon Multimodal predictor fine-tuned for this binary classification task.

## Deployment on Hugging Face Spaces

This application is designed to be easily deployed on Hugging Face Spaces. The `app.py` and `requirements.txt` files generated in the `hf_spaces` directory contain all the necessary code and dependencies. Simply create a new Space on Hugging Face, select the "Gradio" SDK, and upload the contents of the `hf_spaces` directory.