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This project aims to compare the performance metrics of DenseNet201 and a hand-curated CNN using Keras in the classification of plant diseases.

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saaivignesh20-zz/plant-disease-classification

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Plant Disease Classification

This project aims to compare the performance metrics of DenseNet201 and a hand-curated CNN using Keras in the classification of plant diseases.

To view the paper publication on IRJET Journal, click here. The paper is also available in the root of main branch in this repository in PDF format.

Authors:

How to run?

Pre-requisites

  • Jupyter Notebook / Google Colaboratory
  • Python 3.x (if running on local)
  • TensorFlow 2
  • NVIDIA Graphics Card, CUDA Drivers, cuDNN Library [Optional]
  • PlantVillage Dataset [Click Here]

Clone this repository first:

$ git clone https://github.com/saaivignesh20/plant-disease-classification.git

If you don't have Jupyter Notebook or Python installed you can download using Anaconda.

Or if you are an advanced user download and setup Python on your system.

  • For Windows, click here.
  • For Ubuntu/Debian-based operating systems:

Run this in the terminal:

$ sudo apt-get install python3

To download and install Jupyter Notebook:

$ python -m pip install jupyter

To download and install TensorFlow 2:

$ python -m pip install tensorflow

To launch Jupyter Notebook

$ jupyter notebook

Finally open the notebook from this repository.

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This project aims to compare the performance metrics of DenseNet201 and a hand-curated CNN using Keras in the classification of plant diseases.

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