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import gradio as gr
import pandas as pd
from catboost import CatBoostRegressor
# Load the saved CatBoost model
model = CatBoostRegressor()
model.load_model("catboost_yield_model.cbm")
# Define the unique values for dropdown inputs
unique_soil_types = ['Sandy', 'Clay', 'Loam', 'Silt', 'Peaty', 'Chalky']
unique_crops = ['Cotton', 'Rice', 'Barley', 'Soybean', 'Wheat', 'Maize']
unique_irrigation_used = [True, False]
unique_fertilizer_used = [True, False]
# Prediction function
def predict_yield(soil_type, crop, rainfall, temperature, fertilizer_used, irrigation_used):
input_data = pd.DataFrame({
'Soil_Type': [soil_type],
'Crop': [crop],
'Rainfall_mm': [float(rainfall)],
'Temperature_Celsius': [float(temperature)],
'Fertilizer_Used': [fertilizer_used],
'Irrigation_Used': [irrigation_used]
})
prediction = model.predict(input_data)
return f"Predicted Yield (tons per hectare): {prediction[0]:.2f}"
# Create the Gradio interface
with gr.Blocks() as demo:
gr.Markdown("# 🌾 Crop Yield Prediction App 🌦️")
gr.Markdown("Provide the following details to predict the crop yield (tons per hectare):")
with gr.Row():
soil_type = gr.Dropdown(choices=unique_soil_types, label="Soil Type", value="Sandy")
crop = gr.Dropdown(choices=unique_crops, label="Type of Crop", value="Cotton")
with gr.Row():
rainfall = gr.Textbox(label="Average Rainfall (mm)", value="897.077239")
temperature = gr.Textbox(label="Average Temperature (Celsius)", value="27.676966")
with gr.Row():
fertilizer_used = gr.Dropdown(choices=unique_fertilizer_used, label="Fertilizer Used?", value=False)
irrigation_used = gr.Dropdown(choices=unique_irrigation_used, label="Irrigation Used?", value=True)
predict_button = gr.Button("🔮 Predict Yield")
output = gr.Textbox(label="Prediction Output")
predict_button.click(
predict_yield,
inputs=[soil_type, crop, rainfall, temperature, fertilizer_used, irrigation_used],
outputs=output
)
gr.Examples(
examples=[
["Sandy", "Cotton", "897.077239", "27.676966", False, True],
["Clay", "Rice", "1200", "30", True, False],
],
inputs=[soil_type, crop, rainfall, temperature, fertilizer_used, irrigation_used]
)
gr.Markdown("### 🌟 Thank you for using the Crop Yield Prediction App! 🌱")
# Launch the app
demo.launch()
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