corn-leaf-disease-classifier

This project attempts to classify images of corn leaves to identify presence or absence of disease.

The models trained include a:

• Convolutional Neural Network (CNN)
• Support Vector Machine (SVM)

The image classifications consist of:

• Healthy
• Blight
• Common Rust
• Gray Leaf Spot

The commands listed below assume a Windows installation. The dataset was provided for use in the project.

Setup

First, follow the linked instructions install https://pipx.pypa.io/stable/installation/, a dependency manager for Python.

Install Python 3.12 natively, or through Poetry, and create a virtual environment in the project root directory.

Next, open a terminal instance.

• Go to the root (/) directory and run:

poetry run pip install ipykernel

The first command allows Jupyter notebooks to be run with Python in the Poetry environment.

Convolutional Neural Network (CNN)

The Python notebook for running the CNN may be found in the /cnn directory of the project.

• /cnn/cnn.ipynb for the CNN proper
• /cnn/cnn_demo.ipynb for the CNN demo (but use the web app)

Support Vector Machine (CNN)

The Python notebook for running the SVM may be found in the /svm directory of the project.

• /svm/svm.ipynb for the SVM proper
• /svm/svm_demo.ipynb for the SVM demo (but use the web app)

Web Application

An offline web application exists for the demo, although Python notebooks also exist

To run the web app, first open a terminal instance.

• Go to the /app directory, and run:

npm install
npm run dev

• Go to the /server directory, and run:

uvicorn main:app --reload