Tech meets agri in our Plant Disease Detection Project! Podha help farmers reduce crop failure by detecting diseases at early stages 🌱🔬 Open-source ML & image analysis combine to safeguard crops, ensuring sustainable yields. Join us to nurture greener tomorrows. #PlantHealth #AIforAgri
- Make sure you have Python installed (Python 3.8+ recommended).
- Clone this repository:
- git clone
- Navigate to the project directory.
- Install required packages: run this command on termainal "pip install -r requirments.txt" without quotations.
Trained Model link ---https://drive.google.com/file/d/1Xns6liq0twIYB3a80KLLXaseiYeF2Rr3/view?usp=sharing Download the model which is a .h5 file and place in this same project directory.
Dataset link---https://www.kaggle.com/datasets/vipoooool/new-plant-diseases-dataset
Model training python notebook link---https://colab.research.google.com/drive/1NArNwBeDrozSRTNVVdg2zYL-YGhtRifN?usp=sharing This Model achieved accuracy of 96% and is trained on dataset with 70k+ images of 38 catorgies of plant diseases.
To run the Plant Disease Prediction app, execute the following command on terminal:
streamlit run main.py
This will start the Streamlit development server, and you can access the app in your web browser by navigating to http://localhost:8501.
Note: Make sure you are in the project directory when you run the above command.
The following packages are required to run the app:
- streamlit
- tensorflow
- pillow
- keras
- numpy
You can install them using the provided requirements.txt file:
If you have any questions or feedback, feel free to contact me at vaibhavtiwari986gmail.com.