app1.py

# -*- coding: utf-8 -*-
"""app1.ipynb

Automatically generated by Colab.

Original file is located at
    https://colab.research.google.com/drive/1KPGQNmCzYS2jYRmqsqOFKCkw6COyJ_o2
"""

import streamlit as st
import joblib
import numpy as np

# Load the model
def load_model(file_path):
    return joblib.load(file_path)

# Main application
def main():
    # Load Model 1
    model_1 = load_model('model_1d.pkl')

    # Application title and layout
    st.title("CropCrafter: Unlock Your Perfect Yield")
    st.write("Enter your Minimum Yield and Maximum Yield :")

    # Input fields for user interaction
    st.header("Input Fields for Yield Prediction")
    yield_min = st.number_input("Yield Min: g/m^2", min_value=1000.0, max_value=3000.0, value=1000.0)
    yield_max = st.number_input("Yield Max: g/m^2", min_value=3000.0, max_value=4000.0, value=3000.0)

    # Predict and display results
    if st.button("Predict Yield"):
        # Prepare input data
        input_data = np.array([[yield_min, yield_max]])

        # Debug: Display the input shape
        st.write(f"Input Shape: {input_data.shape}")
        st.write(f"Input Data: {input_data}")

        try:
            prediction = model_1.predict(input_data)

            # Break down prediction into temperature, precipitation, and relative humidity
            temperature, precipitation, relative_humidity = map(lambda x: round(x, 2), prediction[0])

            st.success("Predicted Yield Components:")
            st.write(f"Temperature: {temperature}°C")
            st.write(f"Precipitation: {precipitation} mm")
            st.write(f"Relative Humidity: {relative_humidity}%")

            # Use the predicted values for calculations
            seedling_temp = round(temperature * 0.25, 2)
            tillering_temp = round(temperature * 0.30, 2)
            flowering_temp = round(temperature * 0.25, 2)
            harvesting_temp = round(temperature * 0.20, 2)

            seedling_prec = round(precipitation * 0.25, 2)
            tillering_prec = round(precipitation * 0.30, 2)
            flowering_prec = round(precipitation * 0.25, 2)
            harvesting_prec = round(precipitation * 0.20, 2)

            seedling_hum = round(relative_humidity * 0.25, 2)
            tillering_hum = round(relative_humidity * 0.30, 2)
            flowering_hum = round(relative_humidity * 0.25, 2)
            harvesting_hum = round(relative_humidity * 0.20, 2)

            st.write("Tailored Factors for Every Growth Stage:")

            # Create a table for displaying the calculations
            table_data = {
                "Stage": ["Seedling", "Tillering", "Flowering", "Harvesting"],
                "Temperature (°C)": [seedling_temp, tillering_temp, flowering_temp, harvesting_temp],
                "Precipitation (mm)": [seedling_prec, tillering_prec, flowering_prec, harvesting_prec],
                "Relative Humidity (%)": [seedling_hum, tillering_hum, flowering_hum, harvesting_hum],
            }

            st.table(table_data)

        except Exception as e:
            st.error(f"An error occurred during prediction: {e}")

# Run the application
if __name__ == "__main__":
    main()