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alabitech2019/Farmer-assistant-ai

sourceHugging Faceupdated 1y agoView on Hugging Face
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App README

🌿 AI-Powered Crop Assistant (Streamlit App)

Welcome to the AI Crop Assistant — an intelligent tool for farmers, researchers, and agritech teams to:

  • —🦠 Detect crop leaf diseases from images using a deep learning CNN (MobileNetV2)
  • —🌾 Predict expected crop yield based on soil and climate conditions using Random Forest
  • —📊 Explain predictions with SHAP (model explainability) and Grad-CAM (visual heatmaps)
  • —📥 Download prediction reports in CSV format

📂 Features

FeatureDetails
Leaf disease detectionImage classification using CNN
Grad-CAMVisual explanation of predictions
Crop yield predictionBased on rainfall, temp, humidity, pH
SHAPTabular model explainability
Downloadable reportsCSV summaries of yield predictions

🛠 How It Works

  1. 1.Upload a crop leaf image to detect disease
  2. 2.Enter farming parameters (rainfall, temp, etc.)
  3. 3.Select crop type and predict expected yield
  4. 4.View explanation (SHAP) and Grad-CAM visual
  5. 5.Download report 📄

🧠 Technologies Used

  • —Streamlit
  • —TensorFlow (CNN with MobileNetV2)
  • —scikit-learn (Random Forest)
  • —SHAP (Explainability)
  • —OpenCV, Matplotlib, Pillow

📦 Requirements

All dependencies are defined in requirements.txt and installed automatically by Hugging Face Spaces.

📁 Notes

  • —The CNN model (.h5) is downloaded via gdown from Google Drive
  • —Make sure your file is publicly shared via Drive (or uploaded if <500MB)

🚀 Live App

👉 Click “Open in Spaces” above to use the app directly.