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🌱 FLORASCAN – AN AI-DRIVEN PLANT DISEASE DETECTION SYSTEM FOR SUSTAINABLE AGRICULTURE

FloraScan is an AI-driven plant disease detection system built with a lightweight custom CNN model. It empowers farmers with real-time, multilingual diagnosis of plant diseases, offering actionable treatment suggestions and prevention techniques even in remote or low-resource agricultural settings.


🔍 Features

  • Custom CNN trained on 87,000+ images across 38 disease classes
  • 🌐 Multilingual interface for inclusive usage
  • Real-time predictions (~2s inference time on-device)
  • 🌿 Designed for smallholder and rural farmers
  • 📊 ~99% accuracy in field tests

📁 Project Structure

File/Folder Description
FloraScan_Streamlit.pynb Streamlit web app for diagnosis
train_plant_disease.ipynb Custom CNN training notebook
test_plant_disease.ipynb Testing & inference notebook
model_weights/ Folder to place downloaded model
requirements.txt Python dependency list
assets Screenshots and demo media

📥 Download Model

Due to size limitations, the trained CNN model is hosted externally.

  • ⬇️ Download florascan_model.h5
  • After downloading, place it inside the model_weights/ folder.

⚙️ Setup Instructions

Clone the repository and install dependencies:

git clone https://github.com/your-username/FloraScan.git
cd FloraScan
pip install -r requirements.txt

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