Update README.md

README.md

@@ -25,29 +25,3 @@ This project predicts whether a chest X-ray image is NORMAL or shows signs of PN
 - `app.py`: Streamlit app for interactive predictions
 - `Disease_Detection_model.pth`: Trained model weights
 - `requirements.txt`: Python dependencies
-
-## Getting Started
-
-### 1. Install dependencies
-```bash
-pip install -r requirements.txt
-```
-
-### 2. Run the Streamlit app
-```bash
-streamlit run app.py
-```
-
-### 3. Train the model (optional)
-Open `Disease_Detection.ipynb` in Jupyter and follow the steps to train and evaluate the model. The trained weights will be saved as `Disease_Detection_model.pth`.
-
-## Usage
-- Upload a chest X-ray image (JPG, JPEG, PNG) in the Streamlit app
-- The app will predict NORMAL or PNEUMONIA and show confidence/probability chart
-
-## Dataset
-- [Chest X-ray Pneumonia Dataset](https://www.kaggle.com/datasets/paultimothymooney/chest-xray-pneumonia)
-
-## License
-This project is for educational purposes.
-# Junaid0-glitch-Chest-X-ray-Disease-Detection