README.md

---
license: mit
tags:
  - keras
  - teeth-alignment
  - dental
  - healthcare
  - unsupervised-learning
  - rlhf
  - image-classification
datasets:
  - custom
library_name: keras
language: en
pipeline_tag: image-classification
---


<h1 align="center">🦷 Teeth Alignment Detection Model</h1>

<p align="center">
  <img src="https://huggingface.co/VilaVision/dentalmisalignmentdetection/resolve/main/Overbite.jpeg" alt="VilaVision Logo" width="400"/>
</p>


## 🧠 Overview

This Keras model classifies dental images into **aligned** vs. **misaligned** categories. It is designed to aid dental practitioners and orthodontists by analyzing clinical photos or X-rays and detecting signs of malocclusion, crowding, or improper alignment.

🧪 **Training Highlights**:
- **Unsupervised Learning Phase**: Learns visual features from unlabeled dental image data.
- **RLHF (Reinforcement Learning with Human Feedback)**: Fine-tuned using expert-labeled feedback to make the predictions align with real-world diagnoses.

> 📌 This model is a research tool and not a substitute for professional dental evaluation.

---

## 🏗️ Architecture

The model is a Convolutional Neural Network (CNN), built in Keras. It likely includes:

- Convolutional layers (Conv2D + ReLU)
- MaxPooling or AveragePooling layers
- Dense classification layers
- Possibly residual connections for stability

🖼️ **Input shape**: `(224, 224, 3)`  
📤 **Output**: Class probabilities (e.g., `[0.8, 0.2]` → "aligned")

---

## 🧾 Training Data

Though the dataset is not publicly available, it likely contains:

- Intraoral or panoramic dental photographs  
- Images annotated by human experts  
- Unlabeled data used in the unsupervised phase  
- Labeled samples used during RLHF fine-tuning

The model is inspired by techniques described in [BMC Oral Health, 2022](https://bmcoralhealth.biomedcentral.com/articles/10.1186/s12903-022-02466-x) and [PMC Orthodontic AI](https://pmc.ncbi.nlm.nih.gov/articles/PMC8813223/).

---

## 🚀 Usage

### 🔧 Install Dependencies

```bash
pip install tensorflow huggingface_hub
```

### 📄 Load and Predict

```python
from tensorflow import keras
from huggingface_hub import hf_hub_download

# Download model
model_path = hf_hub_download(repo_id="VilaVision/dentalmisalignmentdetection", filename="final_teeth_model.keras")
model = keras.models.load_model(model_path)

# Preprocess image
img = keras.preprocessing.image.load_img("path/to/teeth_image.jpg", target_size=(224, 224))
x = keras.preprocessing.image.img_to_array(img) / 255.0
x = x.reshape((1,) + x.shape)

# Predict
preds = model.predict(x)
print("Raw output:", preds)
# Example: preds[0][0] > 0.5 → "misaligned"
```

---

## 📥 Input & 📤 Output

| Type   | Description                                 |
| ------ | ------------------------------------------- |
| Input  | JPG/PNG image of teeth (224×224), RGB       |
| Output | Class probabilities for alignment detection |

---

## 📈 Performance

While no official metrics are available, CNN models for orthodontic imaging tasks have reported:

* ~95–98% accuracy ([BMC Oral Health, 2022](https://bmcoralhealth.biomedcentral.com/articles/10.1186/s12903-022-02466-x))
* High F1-scores in clinical benchmarks

**Note:** Performance may vary on images that differ from the training distribution.

---

## ⚠️ Limitations

* Not suitable for diagnostic use without expert supervision
* Trained on specific dental image styles — generalization may be limited
* May not perform well on low-quality or occluded images
* Biases in training data may affect outputs

Always consult a licensed orthodontist or dentist before taking action based on model predictions.

---

## 📜 License

🪪 MIT License – free to use, modify, and distribute.

[View on Hugging Face →](https://huggingface.co/AP6621/teeth_alignment_detection_modal)

---

## 📚 References

* [Deep Learning for Orthodontic Photo Classification – BMC Oral Health](https://bmcoralhealth.biomedcentral.com/articles/10.1186/s12903-022-02466-x)
* [AI for Classifying Orthodontic Images – PMC Study](https://pmc.ncbi.nlm.nih.gov/articles/PMC8813223/)
* [OpenAI – Learning from Human Feedback (RLHF)](https://openai.com/research/learning-from-human-feedback)

---

🧠 *Model built and maintained by [VilaVision](https://github.com/VilaVision)*