| license: mit | |
| tags: | |
| - image-classification | |
| - agricultural | |
| - plant-disease | |
| - fastai | |
| - resnet | |
| widget: | |
| - src: https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/plant-disease-test-image.jpg | |
| example_title: "Tomato Late Blight" | |
| # 🌿 GreenLens: Plant Disease Detection Model | |
| This is a `fastai` image classification model trained to identify 38 different types of plant diseases from leaf images. | |
| ## Model Description | |
| **GreenLens** is a computer vision model that can classify healthy and diseased plant leaves across various species like tomato, potato, and corn. It was built by fine-tuning a **ResNet34** architecture on the augmented "New Plant Diseases Dataset". | |
| This project was developed as an end-to-end demonstration of a real-world ML workflow: from data sourcing on Kaggle, training on Google Colab, to being shared on the Hugging Face Hub. | |
| ## How to Use this Model | |
| To use this model, you need to have the `fastai` library installed. You can then load the model and make predictions on your images. | |