metadata

title: Bean Plant Health ViT Classifier
emoji: 🌱📸🩺
colorFrom: green
colorTo: green
sdk: gradio
sdk_version: 4.41.0
app_file: app.py
pinned: false
license: afl-3.0

Bean Plant Health Predictor

This application is designed to help farmers quickly identify the health of bean plants by analyzing images of their leaves. The app uses a Vision Transformer (ViT) model to classify images into three categories: angular_leaf_spot, bean_rust, and healthy. This tool can be deployed on a drone for real-time monitoring of crops, enabling timely treatment of diseased plants.

Use Case

Farmers need to monitor the health of their bean plants regularly to prevent the spread of diseases. This app provides a machine learning-based solution to automate the identification of plant diseases, which can be particularly useful when integrated with drone technology.

Features

Image Classification: Upload an image of a bean leaf, and the app will classify it into one of the following categories:
- Angular Leaf Spot
- Bean Rust
- Healthy

Model Details

Model Used: Vision Transformer (ViT) - base-sized model fine-tuned on the Beans dataset.
Image Processor: The app uses the ViTImageProcessor for preparing images before classification.
Labels: The possible outcomes are angular_leaf_spot, bean_rust, and healthy.

How to Use

Upload an Image: Click on the image input field and upload a photo of a bean leaf.
Get Results: The app will classify the image and display the probabilities for each category.
Interpret the Results: The app shows the confidence levels for each label, helping farmers identify whether the plant is healthy or requires treatment.

Technology Stack

Gradio: Used to create the user interface.
PyTorch: Utilized for running the model inference.
Hugging Face Transformers: Provides the pre-trained Vision Transformer model.