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---
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.
---
## 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
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