Potato Disease Classification project

In this project I trained a CNN model and predicted three types of potato leaf. Either the potato may be healthy or has an early blight disease or late blight disase. The model has good accuracy on these 3 classes. But it is accepting only images of size (256,256) if we pass images other than that shape it won't work. As a future work I have planned to insert resizing function. I used FastApi as a back end implementation to call the model and predict the disease.

Built With

• Python, HTML, CSS, JavaScript, jQuery
• FastApi

Getting Started

git clone https://github.com/Micky373/potato_disease_classification_using_deep_learning.git

cd potato_disease_classification_using_deep_learning

pip install -r requirements.txt

cd api

python main.py

Then cd .. to go to the frontend foler

Here run npm install --from-lock-json and when it finshes npm audit fix

After the installation completed run npm run start

Then drag and drop any images of potato leaf which is a size of (256,256)

Then the result will be shown shortly

The EDA and model training is contained in the notebooks folder the notebook is EDA_model_training_and_saving.ipynb

Author

• GitHub: @GitHub

• LinkedIn: LinkedIn

🤝 Contributing

Contributions, issues, and feature requests are welcome!

Feel free to check the issues page.

Show your support

Give a ⭐️ if you like this project!

Acknowledgments

• Special thanks to Dhaval Patel
• The UI implementation and code flow done with the help of this play list