Lemon Disease Detector

License: CC BY-NC-SA 4.0

Overview

This is Bi-Model Deep Learning Architecture that uses 2 Convolutional Neural Networks to detect the if a lemon leaf is healthy or is diseased.

  1. Binary Classification: Determines if the leaf is from a Lemon tree.
  2. Multi-Class Classification: If it does, this model predicts whether the leaf is healthy or affected by one or more diseases.

The models are trained using Transfer Learning from MobileNetV2, pretrained on ImageNet.


Use Cases

  • Early disease detection in agriculture
  • Educational applications in plant pathology
  • Research and experimentation (non-commercial)

Not suitable for real-world diagnostics without domain expert validation.


Architecture

Binary Model

  • Base: MobileNetV2
  • Input: 224x224 RGB leaf image
  • Output: Binary classification (Target species or not)

Multi-Class Classifier

  • Base: MobileNetV2
  • Input: 224x224 RGB leaf image (if species matched)
  • Output: Multi-label classification (Healthy or 1+ diseases)

Performance

Metric Binary Model Multi-Class Model
Accuracy 1.00 0.96
Precision 1.00 0.95
Recall 1.00 0.95
F1 Score 0.99 0.95

Datasets Used

Lemon Leaf Disease Dataset was used to train both models, and images from PlantVillage Dataset and Natural Images Dataset were used as negatives for training the Binary Model.


License

This project is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license, due to the inclusion of CC BY-NC-SA 4.0-licensed datasets.

You may:

  • Use and share the model for non-commercial purposes
  • Modify it and publish derivatives under the same license
  • Must give proper attribution to the original data providers

Author

Muhammad Ishaque Junejo


Acknowledgement

Creators of MobileNetV2 Dataset Providers:

  • Lemon-Leaf-Disease-Dataset
  • PlantVillage Dataset
  • Natural Images
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