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---
title: CDIApp
emoji: 🏆
colorFrom: red
colorTo: black
sdk: gradio
sdk_version: 5.4.0
app_file: app.py
pinned: false
license: apache-2.0
---
# Plant Disease Classification
## Generated by Claude v3
This is a deep learning project for classifying plant diseases from images. It uses a convolutional neural network trained on a dataset of plant disease images.
## Features
- Train a disease classification model on your own dataset
- Evaluate model performance on a test set
- Run inference on new images through a web interface
## Installation
1. Clone the repository:
```
git clone https://github.com/username/plant-disease-classifier.git
```
2. Install dependencies:
```
cd plant-disease-classifier
pip install -r requirements.txt
```
## Usage
### Data Preparation
Organize your image data into folders for each disease class, for example:
```
data/
healthy/
image1.jpg
image2.jpg
...
disease_a/
image1.jpg
image2.jpg
...
disease_b/
...
```
### Training
To train the model, run:
```
python train_classifier.py --data_dir data/
```
This will save the trained model to the `models/` directory.
### Evaluation
Evaluate the model on a test set:
```
python evaluate.py --data_dir data/test/ --model models/classifier.pth
```
This will print the classification metrics.
### Inference
To launch the web interface for running inference on new images:
```
python app.py
```
Then open `http://localhost:5000` in your web browser. You can upload images and see the predicted disease class.
## Contributing
Contributions are welcome! Please open an issue or submit a pull request.
## License
This project is licensed under the [MIT License](LICENSE). |