PotatoTech is an Android application designed to classify potato leaf diseases. Using advanced machine learning models, the app accurately identifies whether a potato leaf is healthy or diseased, specifically detecting Early Blight and Late Blight.
- 🥔 Disease Identification: Develop a prediction system to identify the health status of potato leaves.
- 🤖 Machine Learning Integration: Integrate an efficient machine learning model for specific disease detection (Early Blight and Late Blight).
- 📱 User-Friendly Interface: Design a user-friendly interface for image submission and health status prediction.
The dataset used is "Plant Village - Potato Disease Classification," available on Kaggle. It includes three categories:
- 🥔 Healthy Potato
- 🌿 Potato Early Blight
- 🍂 Potato Late Blight
- 🌿 Real-Time Disease Detection: Quickly and accurately identify potato leaf diseases.
- 📸 Image Submission: Easy image capture and upload for instant analysis.
- 📈 Detailed Results: View comprehensive results and disease information.
- 🔄 Offline Mode: Use the app even without an internet connection.
- 🧠 TensorFlow: For building and training the machine learning models.
- 🕸 Convolutional Neural Networks (CNN): For image classification.
- 📱 Android Studio: For developing the mobile application.
To get started with PotatoTech, follow these steps:
-
Clone the repository:
git clone https://github.com/MohamedAlaouiMhamdi/PotatoTech-App-for-Classification-of-Potato-Leaf-Diseases -
Open the project in Android Studio.
-
Build and run the app on your Android device or emulator.
We welcome contributions to enhance PotatoTech! To contribute:
This project is licensed under the MIT License. See the LICENSE file for details.
Thank you for using PotatoTech! Together, we can help farmers protect their crops and ensure healthier potato plants. 🌿🥔