---
title: HW3 PART2 Image Identification
emoji: 📚
colorFrom: red
colorTo: blue
sdk: gradio
sdk_version: 5.47.2
app_file: app.py
pinned: false
license: mit
short_description: Stop Sign Image Identification
---

# Stop Sign Image Classifier  

**Author:** Your Name  
**Course:** 24679 - Designing and Deploying AI/ML Systems  

This app classifies traffic images into two categories using an AutoGluon-trained model:  
- **0 = Not a Stop Sign**  
- **1 = Stop Sign**  

The interface allows you to upload or drag-and-drop an image of a road scene. The model outputs the predicted class along with probability scores.  

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## How to Use  
1. Upload an image (JPG/PNG).  
2. Click **Submit** to run the classifier.  
3. View the predicted label (`0` or `1`) and the probability distribution.  

---

## Deployment Details  
- **Frameworks:** [AutoGluon Image](https://auto.gluon.ai/stable/tutorials/image_prediction/index.html), [Gradio](https://gradio.app/)  
- **Hosting:** Hugging Face Spaces  
- **Model Loading:** Model is downloaded from the Hugging Face Hub and automatically unpacked on startup.  

---

## Requirements  
Dependencies are listed in `requirements.txt`.  

---

## Acknowledgments  
- Model trained by a classmate in Homework 2  
- Deployment scaffold and documentation supported with AI assistance (ChatGPT, OpenAI)  
- Reference: Class-provided notebook *image gradio.ipynb*  


Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference