README.md

---
license: mit
pipeline_tag: image-classification
base_model: google/vit-base-patch16-224
tags:
- medical-ai
- image-classification
- pneumonia
- chest-xray
- gradcam
- vit
---
# 🫁 Pneumonia Detector
![Python](https://img.shields.io/badge/Python-3.10-blue)
![ViT](https://img.shields.io/badge/ViT-Base%20Patch16%20224-green)
![PyTorch](https://img.shields.io/badge/PyTorch-2.0-red)
![HuggingFace](https://img.shields.io/badge/HuggingFace-Spaces-yellow)

## 🎯 Live Demo
👉 [Try it on Hugging Face Spaces](https://huggingface.co/spaces/mou11/pneumonia-detector)

## 🔍 Overview
A medical image classification system that detects pneumonia from chest X-ray images using Vision Transformer (ViT) with Grad-CAM explainability. The model highlights which regions of the X-ray influenced the prediction, making it transparent and trustworthy for medical screening.

## 📊 Results
| Metric | Score |
|--------|-------|
| Overall Accuracy | 87% |
| AUC-ROC | 0.9805 |
| PNEUMONIA Recall | 1.00 |
| NORMAL Precision | 0.99 |

## 📈 Classification Report
| Class | Precision | Recall | F1-Score |
|-------|-----------|--------|----------|
| NORMAL | 0.99 | 0.66 | 0.79 |
| PNEUMONIA | 0.83 | 1.00 | 0.91 |

## ✨ Features
- ✅ Chest X-ray classification: NORMAL vs PNEUMONIA
- ✅ Vision Transformer (ViT) fine-tuned on medical images
- ✅ Grad-CAM heatmap visualization for explainability
- ✅ Handles class imbalance with weighted loss
- ✅ Gradio demo for interactive predictions

## 🏗️ Architecture
Chest X-Ray Image → Preprocessing (224x224) → ViT Base Patch16 → Fine-tuned Classifier Head → Prediction + Grad-CAM Heatmap

## 🛠️ Tech Stack
| Component | Tool |
|-----------|------|
| Model | Google ViT Base Patch16 224 |
| Framework | PyTorch |
| Explainability | Grad-CAM |
| Dataset | Chest X-Ray Images (Pneumonia) — Kaggle |
| UI | Gradio |
| Training | Google Colab T4 GPU |

## 📁 Dataset
- **Source:** [Chest X-Ray Images (Pneumonia)](https://www.kaggle.com/datasets/paultimothymooney/chest-xray-pneumonia)
- **Total Images:** 5,863
- **Classes:** NORMAL (1,341) vs PNEUMONIA (3,875)
- **Split:** Train / Val / Test

## 🚀 How to Use
```python