This model is a fine-tuned version of the Vision Transformer (ViT) model, specifically google/vit-base-patch16-224-in21k, tailored for detecting various diseases in orange leaves. The model was fine-tuned on a dataset containing 5185 images of orange leaves categorized into 10 different classes.
Model Description
The OrangeLeafDiseaseDetector model is designed to classify orange leaf images into one of the following ten categories:
Aleurocanthus spiniferus
Chancre citrique
Cochenille blanche
Dépérissement des agrumes
Feuille saine
Jaunissement des feuilles
Maladie de l'oïdium
Maladie du dragon jaune
Mineuse des agrumes
Trou de balle
Intended Uses & Limitations
Intended Uses
This model is intended to help farmers, agricultural researchers, and agronomists diagnose diseases in orange leaves based on images. The use cases include:
Early detection of diseases to prevent the spread and reduce crop loss.
Assisting in field research and agricultural studies.
Limitations
The model is only as good as the dataset it was trained on. It might not perform well on images significantly different from those in the training dataset.
Environmental factors like lighting, leaf condition, and background can affect the model's accuracy.
The model should not be used as the sole diagnostic tool. It is recommended to use it alongside other diagnostic methods.
Training Data
The model was trained on a custom dataset of 5185 images of orange leaves, categorized into the aforementioned ten classes. The images include various disease conditions and healthy leaves, collected from different sources.
Training Procedure
Hyperparameters
The following hyperparameters were used during the training process:
