Update README.md

README.md

@@ -29,11 +29,6 @@ CropGuard/
 ├── app.py                # Gradio app
 ├── Dockerfile            # Docker container definition
 ├── requirements.txt      # Python dependencies
-├── notebooks/            # Step-by-step project development
-│   ├── 01_data_preprocessing.ipynb
-│   ├── 02_model_training.ipynb
-│   ├── 03_model_validation.ipynb
-│   └── 04_gradcam_visualization.ipynb
 ├── src/                  # Source code (organized into modules)
 │   ├── app/
 │   ├── data/
@@ -44,76 +39,6 @@ CropGuard/
 └── README.md             # (this file)
 ```
 
----
-
-## Notebooks Overview
-
-| Notebook | Purpose |
-|:-|:-|
-| `01_data_preprocessing.ipynb` | Download PlantVillage dataset, clean and split into train/val/test sets |
-| `02_model_training.ipynb` | Set up data augmentation, train MobileNetV2 model, monitor training curves |
-| `03_model_validation.ipynb` | Evaluate model performance, generate metrics, confusion matrix |
-| `04_gradcam_visualization.ipynb` | Generate GradCAM++ heatmaps to visualize model focus |
-
----
-
-## How to Run Locally
-
-1. **Clone the repo:**
-
-```bash
-git clone https://github.com/YOUR_USERNAME/CropGuard.git
-cd CropGuard
-```
-
-2. **Create a virtual environment:**
-
-```bash
-python3 -m venv .venv
-source .venv/bin/activate
-```
-
-3. **Install dependencies:**
-
-```bash
-pip install --upgrade pip
-pip install -r requirements.txt
-```
-
-4. **Launch the app:**
-
-```bash
-python app.py
-```
-
-It will be available at [http://localhost:7860](http://localhost:7860).
-
----
-
-## How to Build and Run with Docker
-
-```bash
-docker build -t cropguard-app .
-docker run -p 7860:7860 cropguard-app
-```
-
----
-
-## Web Deployment
-
-Easily deployable on:
-
-- Hugging Face Spaces
-- DockerHub
-
----
-
-## Sample Images
-
-We provide a few **sample leaf images** in the `sample_images/` directory so users can test the model even without their own images.
-
----
-
 ## License
 
 MIT License.