Plant Disease Detection and Treatment Suggestion

This project, built using Flask, analyzes plant images to detect diseases, recommends treatment options, and provides links to purchase necessary medicines. The backend can be integrated into any UI, or used with a simple cURL command.

Key Features

• Detects plant diseases from images.
• Provides a detailed description of the disease.
• Suggests appropriate treatment measures.
• Offers a link to purchase the required medicine.
• Gives a step-by-step procedure to cure the disease.

You can try the live demo here

The project BitBucket repository is available here.

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Example API Usage:

To analyze an image, you can use the following cURL command:

curl -X POST -F "image=@/path/to/your/image.jpg" https://plant-dd-co9k.onrender.com/predict

The API will return a detailed JSON response like this:

{
  "title": "Strawberry: Leaf Scorch",
  "description": "Leaf scorch symptoms are very similar to...",
  "image_url": "https://content.ces.ncsu.edu/media/images/17531_IMG_2126.JPG",
  "prevent": "Key prevention strategies include proper garden sanitation...",
  "supplement_buy_link": "https://agribegri.com/products/buy-organic-fungicide-online--organic-fungicide-with-best-rate-.php",
  "supplement_image_url": "https://encrypted-tbn3.gstatic.com/shopping?q=tbn:ANd9GcSV3dLQAuhGWWsZSX3Ray15J_uSeFgSo7oLE0G2BxPFSwVNnOUY7VsBbLzDbw_mzUw3ZFLaF4kPWPyzatefP2bnSZwEbwrYnGGYgEl8rS6XWmwRnloOWnwy&usqp=CAE",
  "supplement_name": "Greatindos Premium Quality All in 1 Organic Fungicide"
}

How It Works

1. Upload the Plant Image:
   The backend receives an image of the plant, which is passed through a trained convolutional neural network (CNN) model.

2. Analyze and Detect:
   The CNN model identifies the disease based on the input image and provides a detailed description of the disease.

3. Suggest Treatment:
   Along with the disease detection, the API suggests the appropriate treatment options, including:

   • Preventive measures to avoid further damage.
   • Links to purchase medicine (organic fungicides, pesticides, etc.).
   • Step-by-step instructions on how to cure the disease.

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Screenshots of the Project:

Model Information

Real-World Application

This project can be utilized in agricultural sectors to assist farmers and gardeners in identifying and curing plant diseases early. Whether it’s a small backyard garden or a large-scale farm, timely identification and treatment are crucial for preventing crop losses.

The system is designed to be easily integrated into mobile or web apps, making it accessible to anyone with a smartphone.

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Stay updated for more features, including multi-language support and mobile app integration!