import ee
import streamlit as st
import pandas as pd

# Authenticate Earth Engine
service_account = 'earth-engine-service-account@ee-esmaeilkiani1387.iam.gserviceaccount.com'
credentials = ee.ServiceAccountCredentials(service_account, 'ee-esmaeilkiani1387-1b2c5e812a1d.json')
ee.Initialize(credentials) 

# آپلود فایل مختصات
uploaded_file = st.file_uploader("Farm_Details_Export (1).csv", type="csv")
if uploaded_file:
    farms_df = pd.read_csv(uploaded_file)
    
    # پردازش اطلاعات هر مزرعه
    for idx, row in farms_df.iterrows():
        lat, lon = row['latitude'], row['longitude']
        location = ee.Geometry.Point(lon, lat)
        
        # دریافت تصویر ماهواره‌ای و محاسبه NDVI
        image = ee.ImageCollection('COPERNICUS/S2') \
                  .filterBounds(location) \
                  .filterDate('2023-01-01', '2023-12-31') \
                  .mean()
        ndvi = image.normalizedDifference(['B8', 'B4']).reduceRegion(
            reducer=ee.Reducer.mean(),
            geometry=location,
            scale=30
        )
        
        st.write(f"شاخص NDVI برای مزرعه {idx}: {ndvi.getInfo()['nd']}")