| # 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. | |