Plant-Disease-Detection

LINK to WEBAPP

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DATASET LINK

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Table of Content

• Overview
• Architechture
• Demo
• Installation
• Technology Stack

Overview

• In real world, farmers face lots of devastating loss only due to they don't know which disease is affecting their crop. This project is mainly focused to solve that problem.
• Here I take images of corn, potato and tomato which is affected by the disease Corn-Common_rust, Potato-Early_blight and Tomato-Bacterial_spot and train it on custom CNN model.

Architechture

🙋 Project Workflow

Our pipeline consists of three steps:

1. An AI model which detect plant disease.
2. An AI model which predict if the leaves has disease or not.
3. The output is predicted disease name.

🚀 Model's performance

• Our Custom CNN model perform better by giving near 95% accuracy.

Demo

Installation

• Clone the repository:

  https://github.com/dipesg/Plant-Disease-Detection.git

• Create separate conda environment:

  conda create -n plant python=3.6 -y

• Activate environment:

  conda activate plant

• Install all the requirements:

  pip install -r requirements.txt

• Run following script to run the program:

  streamlit run app.py

⚠️ Technology Stack

• Pandas
• Numpy
• Matplotlib
• Sklearn
• Tensorflow
• Streamlit
• OpenCV