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import re
import json
import streamlit as st
import pandas as pd
import geopandas as gpd
import leafmap.foliumap as leafmap
# wide streamlit display
st.set_page_config(layout="wide")
query_params = st.experimental_get_query_params()
file_url = query_params.get("file_url", [None])[0]
if file_url:
if file_url.startswith("https://drive.google.com/file/d/"):
ID = file_url.replace("https://drive.google.com/file/d/", "").split("/")[0]
file_url = f"https://drive.google.com/uc?id={ID}"
input_gdf = gpd.read_file(file_url)
input_gdf = input_gdf.to_crs(epsg=7761) # Gujarat zone
def format_fn(x):
return input_gdf.drop(columns=["geometry"]).loc[x].to_dict()
input_geometry_idx = st.selectbox("Select the geometry", input_gdf.index, format_func=format_fn)
geometry_gdf = input_gdf[input_gdf.index == input_geometry_idx]
m = leafmap.Map()
m.add_wms_layer(
"https://wayback.maptiles.arcgis.com/arcgis/rest/services/World_Imagery/WMTS/1.0.0/GoogleMapsCompatible/MapServer/tile/56450/{z}/{y}/{x}"
)
m.add_gdf(
geometry_gdf,
layer_name="Geometry",
zoom_to_layer=True,
style_function=lambda x: {"color": "red", "fillOpacity": 0.0},
)
m.to_streamlit()
# Metrics
stats_df = pd.DataFrame()
stats_df.loc["Points"] = json.loads(geometry_gdf.to_crs(4326).to_json())["features"][0]["geometry"]["coordinates"]
stats_df.loc["Area (ha)"] = geometry_gdf.geometry.area.item() / 10000
stats_df.loc["Perimeter (m)"] = geometry_gdf.geometry.length.item()
st.write("<h3><div style='text-align: center;'>Geometry Metrics</div></h3>", unsafe_allow_html=True)
st.markdown(
f"""| Metric | Value |
| --- | --- |
| Area (m^2) | {stats_df['Area (m^2)'].item():.2f} m^2 = {stats_df['Area (m^2)'].item()/10000:.2f} ha |
| Perimeter (m) | {stats_df['Perimeter (m)'].item():.2f} m |
"""
)
else:
st.warning("Please provide a KML or GeoJSON URL as a query parameter, e.g., `?file_url=<your_file_url>`")
|