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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.
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