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README.md
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## Key Features
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---
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docker build -t plantoi-app .
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# 3. Run the container
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docker run -p 7860:7860 plantoi-app
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## Key Features
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* **Instant Analysis:** Upload an image and get results in milliseconds.
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* **Deep Learning Accuracy:** Powered by a custom-trained CNN model (`plant_disease_model_final.h5`).
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* **Responsive Interface:** A clean, user-friendly web UI built with HTML5/CSS3.
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* **Containerized:** Fully Dockerized for consistent performance across any environment.
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* **Secure & Private:** Images are processed securely within the session.
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---
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docker build -t plantoi-app .
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# 3. Run the container
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docker run -p 7860:7860 plantoi-app
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```
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### Method 2: Manual Python Setup
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```bash
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# 1. Create a virtual environment
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python -m venv venv
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source venv/bin/activate # On Windows: venv\Scripts\activate
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# 2. Install dependencies
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pip install -r requirements.txt
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# 3. Run the application
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python app.py
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```
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## Project Structure
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```text
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Plantoi/
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βββ model/
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β βββ plant_disease_model_final.h5 # The trained AI model
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βββ static/
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β βββ css/ # Stylesheets
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β βββ js/ # Frontend scripts
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β βββ images/ # Assets
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βββ templates/
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β βββ index.html # Main user interface
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βββ app.py # Main Flask application entry point
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βββ disease_data.py # Disease info and treatment dictionary
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βββ Dockerfile # Container configuration
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βββ requirements.txt # Python dependencies
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```
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## Disclaimer
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This tool is intended for educational and assistive purposes. While the AI model strives for high accuracy, it should not replace professional agricultural advice. Always consult with a plant pathologist for critical crop management decisions.
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<div align="center">
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Developed by Ali Abdullah <br> BS Artificial Intelligence Student at SZABIST Islamabad
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</div>
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