Plant Disease Detection

Abstract

1. Introduction

This Project takes a apple pant leaf image and predicts that is the plant leaf is healthy or not using Machine learning and Computer Vision.

This Website help you to detect disease in your plant based to the plant's leaf image

~The Website is LIVE HERE !, Check it out~ - Due to horoku recent removal of free projects, it's no longer available

2. Objective

The Website predicts if the leaf🌿 is healthy or not using by taking plant's left image using Machine Learning🤖

This project demonstrates how Python, Machine Learning, Computer Vision can be applied to a real-world AI & Machine Learning problem.

4. Technology Stack

• Streamlit

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

• Python 3.8 or later
• pip / virtualenv for dependencies
• VS Code, PyCharm or Jupyter Notebook
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/Shubhamai/plant-disease-detection.git
cd plant-disease-detection

1. Clone the repo git clone https://github.com/Shubhamai/plant-disease-detection
2. Run the pip install -r requirements.txt command.
3. Download the model.h5 from my kaggle notebook and save it as model_weights.h5 in the main directory of the repo.
4. Run streamlit run app.py

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

• Deploy the model as a web app with Streamlit, Flask or FastAPI
• Compare against an additional model and report the metric difference
• Add explainability (SHAP / Grad-CAM)

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

1. What dataset does the project use and how was it pre-processed?
2. Which algorithm / model architecture is used and why was it chosen over alternatives?
3. How are training and testing data split, and how is overfitting avoided?
4. Which evaluation metrics (accuracy, precision, recall, F1) are reported and what do they mean here?
5. How would you deploy this model for real users?

9. Source Code & License

This project is developed by Shubhamai and published on GitHub under the GNU General Public License v3.0. Please follow the license terms and credit the original author when you use or modify this code.