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A deep learning based system ot recognize potato leaf disease by capturing or uploading image.

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Potato Leaf Disease Recognition System

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Overview

Welcome to the Potato Leaf Disease Recognition System! This system helps in identifying potato plant diseases quickly and accurately. By simply uploading or capturing an image of a potato leaf, our system automatically detects potential diseases, offering instant results with high accuracy.

Features

  • Upload or Capture Image – You can either upload an image or capture a live photo of the potato leaf.
  • Disease Detection – The system processes the image using a deep learning model to identify the disease.
  • Instant Results – Receive immediate predictions on the condition of the potato plant.

Supported Diseases

  • Early Blight
  • Late Blight
  • Healthy

How it Works

  1. Upload Image – Upload an image of the potato leaf for analysis.
  2. Analysis – The system processes the image and predicts the disease using a trained machine learning model.
  3. Result – Instantly get the disease name based on the uploaded or captured image.

Technologies Used

  • TensorFlow – For building and utilizing the pre-trained model.
  • Streamlit – To build the interactive web interface.
  • PIL – To handle image processing tasks such as resizing.
  • NumPy – For numerical computations and image array manipulation.
  • OpenCv - For image handling.

About Dataset

  • Dataset Source: Kaggle Potato Leaf Disease Dataset.
  • Dataset Details (After mannual arrangements):
    • Train: 1722 images
    • Validation: 215 images
    • Test: 215 images
    • 3 Classes: Early Blight, Late Blight, Healthy

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A deep learning based system ot recognize potato leaf disease by capturing or uploading image.

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