Update app.py

app.py

@@ -1,51 +1,76 @@
 import streamlit as st
-import ee
 import pandas as pd
-from datetime import date
+import ee
 import geemap
 
-# Authenticate Earth Engine
+# Earth Engine authentication
 service_account = 'earth-engine-service-account@ee-esmaeilkiani1387.iam.gserviceaccount.com'
 credentials = ee.ServiceAccountCredentials(service_account, 'ee-esmaeilkiani1387-1b2c5e812a1d.json')
-ee.Initialize(credentials) 
+ee.Initialize(credentials)
 
+# Load the CSV file
 @st.cache_data
-def get_farm_coordinates(farm_name, dataset_url):
-    # بارگذاری دیتاست
-    df = pd.read_csv(dataset_url)
-    # جستجوی مزرعه
-    farm_data = df[df['Farm'] == farm_name]
-    if farm_data.empty:
-        return None
-    return farm_data[['latitude', 'longitude']].values[0]
-
-# تابع برای محاسبه شاخص NDVI در بازه زمانی مشخص
-def get_ndvi_map(latitude, longitude, start_date, end_date):
-    point = ee.Geometry.Point([longitude, latitude])
-    collection = (ee.ImageCollection("COPERNICUS/S2")
-                  .filterBounds(point)
-                  .filterDate(start_date, end_date)
-                  .map(lambda img: img.normalizedDifference(['B8', 'B4']).rename('NDVI')))
-    ndvi_image = collection.median()
-    vis_params = {'min': 0, 'max': 1, 'palette': ['blue', 'white', 'green']}
-    return geemap.ee_to_url(ndvi_image.clip(point.buffer(10000)), vis_params)
-
-# رابط کاربری با Streamlit
-st.title("نمایش نقشه شاخص NDVI مزارع نیشکر")
-farm_name = st.text_input("نام مزرعه را وارد کنید:")
-dataset_url = "https://huggingface.co/datasets/Esmaeilkianii/SugarcaneDataSet/embed/viewer/default/train"
+def load_data():
+    return pd.read_csv('/home/user/Farm_Details_Export.csv')
+
+df = load_data()
+
+st.title('Farm Finder and Sentinel-2 Imagery Viewer')
 
+# Farm search functionality
+farm_name = st.text_input('Enter farm name:')
 if farm_name:
-    coords = get_farm_coordinates(farm_name, dataset_url)
-    if coords is not None:
-        st.success(f"مزرعه یافت شد! مختصات: {coords}")
-        start_date = st.date_input("تاریخ شروع:", date(2023, 1, 1))
-        end_date = st.date_input("تاریخ پایان:", date.today())
-        
-        if start_date < end_date:
-            map_url = get_ndvi_map(coords[0], coords[1], start_date.isoformat(), end_date.isoformat())
-            st.image(map_url, caption=f"نقشه NDVI برای مزرعه {farm_name}")
-        else:
-            st.error("تاریخ شروع باید قبل از تاریخ پایان باشد.")
+    farm = df[df['farm_name'].str.contains(farm_name, case=False)]
+    if not farm.empty:
+        st.write(farm)
     else:
-        st.error("مزرعه‌ای با این نام یافت نشد.")
+        st.write('Farm not found')
+
+# Sentinel-2 index selection
+indices = {'NDVI': 'NDVI', 'EVI': 'EVI', 'NDWI': '(B3 - B8) / (B3 + B8)'}
+selected_index = st.selectbox('Select Sentinel-2 index:', list(indices.keys()))
+
+# Date range selection
+start_date = st.date_input('Start date')
+end_date = st.date_input('End date')
+
+if st.button('Show Map'):
+    # Create a map centered on the mean coordinates of all farms
+    center_lat = df['latitude'].mean()
+    center_lon = df['longitude'].mean()
+    m = geemap.Map(center=[center_lat, center_lon], zoom=10)
+    
+    # Add Sentinel-2 imagery with selected index
+    s2_collection = (ee.ImageCollection('COPERNICUS/S2_SR')
+                     .filterDate(start_date, end_date)
+                     .filter(ee.Filter.lt('CLOUDY_PIXEL_PERCENTAGE', 20)))
+    
+    if selected_index == 'NDVI':
+        vis_params = {'min': 0, 'max': 1, 'palette': ['red', 'yellow', 'green']}
+    elif selected_index == 'EVI':
+        vis_params = {'min': -1, 'max': 1, 'palette': ['blue', 'white', 'green']}
+    else:  # NDWI
+        vis_params = {'min': -1, 'max': 1, 'palette': ['red', 'white', 'blue']}
+    
+    def add_index(image):
+        index = image.expression(indices[selected_index], {
+            'B3': image.select('B3'),
+            'B4': image.select('B4'),
+            'B8': image.select('B8'),
+        }).rename(selected_index)
+        return image.addBands(index)
+    
+    s2_with_index = s2_collection.map(add_index)
+    median_index = s2_with_index.select(selected_index).median()
+    m.addLayer(median_index, vis_params, selected_index)
+    
+    # Add farm locations to the map
+    for idx, row in df.iterrows():
+        info = f"Farm: {row['farm_name']}<br>Age: {row['age']}<br>Variety: {row['variety']}"
+        m.add_marker(location=[row['latitude'], row['longitude']], popup=info)
+    
+    # Display the map
+    m.to_streamlit(height=600)
+
+if __name__ == '__main__':
+    st.write('App is running')