Leaf Disease Detection

This repository contains a simple example for detecting diseased apple leaves (We can use the same structure for any anomaly detection). The code was originally developed as a Google Colab notebook and demonstrates image preprocessing, a small convolutional neural network, and basic evaluation.

Contents

• leaf_disease_detection.py - Main script (Colab-oriented) with preprocessing, model definition, training, and evaluation.

Requirements

• Python 3.8+
• TensorFlow
• OpenCV (cv2)
• imutils
• scikit-learn
• matplotlib
• numpy

You can install the main packages with:

pip install tensorflow opencv-python imutils scikit-learn matplotlib numpy

Notes about Colab

The script uses Google Colab-specific helpers (google.colab.drive and google.colab.patches.cv2_imshow). To run locally, remove or adapt the Colab mount lines and update dataset paths to point to a local folder structure.

Running locally (quick)

1. Update the dataset paths inside leaf_disease_detection.py to point to your local dataset directories.
2. Remove or comment out the drive.mount(...) line and Colab-specific cv2_imshow usages, replacing them with cv2.imshow or matplotlib display calls where appropriate.
3. Run:

python leaf_disease_detection.py

Personal project/learning/studies!