Update README.md

README.md

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+# 🪧 Sign Identification (AutoML) — Gradio App
+
+This app wraps a classmate’s image model **cassieli226/sign-identification-automl** (AutoGluon Multimodal).  
+Upload a sign image to see both the **original** and the **preprocessed (224×224)** image the model actually sees, plus **class probabilities**.
+
+## ✨ What this app shows
+- Image upload (PNG/JPG; webcam optional)
+- Validation & friendly errors (type/size)
+- Original vs. preprocessed image side-by-side
+- Exposed inference parameter: **Top-K**
+- ≥ 3 clickable **Examples** for quick testing
+
+## 🔗 Model & Dataset
+- Model: https://huggingface.co/cassieli226/sign-identification-automl  
+- Original dataset: `ecopus/sign_identification`  
+  - augmented split (385) for train/val
+  - original split (35) for test
+
+## 🛠️ Tech
+- Framework: AutoGluon Multimodal
+- Backbone: TimmAutoModelForImagePrediction (~194M params)
+- Inference: `predict_proba` over 2 classes (0/1)
+
+## ⚠️ Notes & Limitations
+- Small, student-collected dataset (~420 images) → may not generalize.
+- Binary labels only (0, 1).
+
+## 🙏 Acknowledgments
+- AutoGluon team
+- Hugging Face Hub
+- CMU 24-679 (Designing & Deploying AI/ML)
+
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference