/Plant-Disease-Prediction-Using-MobileNet

Plant disease classification using deep learning. Detect plant issues from images using CNNs. Jupyter notebook, model, and dataset included.

Primary LanguageJupyter NotebookMIT LicenseMIT

Plant Disease Classification using Deep Learning

This GitHub repository contains code and resources for a plant disease classification project using deep learning models. The project focuses on using convolutional neural networks (CNNs) to identify diseases in plant images.

Features:

Implementation of deep learning models for plant disease classification. Data preprocessing and augmentation techniques for improved model performance. Training, validation, and evaluation of models on a diverse dataset. Visualization tools to assess model predictions and performance.

Files and Folders:

notebook.ipynb: Jupyter Notebook with code for data processing, model training, and evaluation. images/: Sample images used for visualization. model.h5: Trained deep learning model in HDF5 format.

Getting Started:

Clone the repository: git clone https://github.com/your-username/plant-disease-classification.git Open and run the notebook.ipynb to execute the project.

Requirements:

Python 3.6+ TensorFlow 2.x Jupyter Notebook Acknowledgments: The project is inspired by the need for automated plant disease detection. The dataset is sourced from PlantVillage.

License:

This project is licensed under the MIT License.