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A newer version of the Streamlit SDK is available:
1.44.0
metadata
title: Cotton Plant Disease Classifier
sdk: streamlit
emoji: 🏃
colorFrom: green
colorTo: yellow
pinned: false
short_description: This Streamlit app utilizes a deep learning model to classif
license: apache-2.0
This Streamlit app utilizes a deep learning model to classify images of cotton leaves into various disease categories or as healthy. The model, built with TensorFlow, has been trained on a dataset of cotton plant leaves under different conditions, aiming to assist farmers and agronomists in early disease detection and management.
Features
- Image Upload: Users can upload images of cotton leaves to get instant predictions.
- Disease Classification: The app classifies the leaf as healthy or identifies the specific disease affecting it.
- Model Insights: Provides insights into the confidence levels of the predictions.
How to Use
- Upload Image: Click on the 'Upload Image' button to upload a photo of a cotton leaf.
- View Prediction: After the image is processed, view the prediction displayed on the screen.
Technology Stack
- TensorFlow & Keras: For building and training the deep learning model.
- Streamlit: For creating the web application interface.
- Python: The backend logic and model training scripts.
Configuration Reference
For more details on configuring and deploying Streamlit apps on Hugging Face Spaces, check out the configuration reference.
About
Developed by Sharjeel Ahmad khan, this tool aims to leverage machine learning for agricultural advancements, making it easier to detect and manage plant diseases early on.