Salmane20/soil-growth-prediction

Soil Growth Prediction System 🌱

This application uses machine learning to predict whether soil is suitable for growing crops based on various soil parameters.

Features

• —Analyzes multiple soil chemical properties
• —Considers environmental factors
• —Provides confidence scores for predictions
• —User-friendly interface with sliders and dropdowns

How to Use

1. 1.Adjust the sliders for numerical soil properties
2. 2.Select appropriate categories from dropdowns
3. 3.Click 'Analyze Soil' to get the prediction
4. 4.View the result showing if the soil is suitable for growing crops

Model Details

• —Built using TensorFlow
• —Trained on a comprehensive soil dataset
• —Uses both numerical and categorical features
• —Implements proper preprocessing for accurate predictions

Technical Requirements

• —Python 3.8+
• —TensorFlow
• —scikit-learn
• —pandas
• —numpy
• —gradio

License

This project is open-source and available for educational and research purposes.

Setup

1. 1.Install the required dependencies:

pip install -r requirements.txt

1. 1.Run the application:

python app.py

Usage

1. 1.Enter the soil parameters in the input fields:
2. 2.For numerical values (like pH, temperature, etc.), enter the appropriate number
3. 3.For categorical values (like soil type), select from the dropdown menu

1. 1.Click "Submit" to get the prediction

1. 1.The application will return:
2. 2.Whether the soil is suitable for growing crops
3. 3.The confidence level of the prediction

Files

• —soil.csv: Dataset containing soil parameters and growth conditions
• —soil_model.keras: Trained neural network model
• —app.py: Gradio interface application
• —requirements.txt: Python dependencies