app.py

import streamlit as st
import pandas as pd
import plotly.express as px
import plotly.graph_objs as go
from data_processing import process_file
from ml_model import predict_yield

# Title of the dashboard
st.title('Sugarcane Yield Prediction Dashboard')

# File upload
uploaded_file = st.file_uploader("Upload your crop log data", type=["csv", "xlsx", "pdf", "tiff"])

# Check if file is uploaded
if uploaded_file is not None:
    data = process_file(uploaded_file)
    if data is not None:
        st.write("Data Preview:")
        st.dataframe(data.head())

        # Machine Learning predictions
        predictions = predict_yield(data)
        data['Predicted Yield'] = predictions
        st.write("Predicted Yield:")
        st.dataframe(data[['feature1', 'feature2', 'Predicted Yield']])

        # 3D Visualization
        fig_hist = px.histogram(data, x='Predicted Yield', nbins=30, title='3D Histogram')
        fig_hist.update_traces(marker=dict(colorscale='Viridis', reversescale=True))
        st.plotly_chart(fig_hist)

        fig_surf = go.Figure(data=[go.Surface(z=data[['feature1', 'feature2', 'Predicted Yield']].values)])
        fig_surf.update_layout(title='3D Surface Plot', autosize=True)
        st.plotly_chart(fig_surf)
    else:
        st.error("Error processing file.")
else:
    st.write("Please upload a file to proceed.")