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Browse files- app.py +20 -5
- requirements.txt +17 -0
app.py
CHANGED
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@@ -8,8 +8,6 @@ import scipy.spatial as sp
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import streamlit as st
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import folium
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from streamlit.components.v1 import html
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from haversine import haversine, Unit
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@@ -228,6 +226,10 @@ def search_geonames(toponym, df):
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lat=[]
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lon=[]
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if 'geonames' in data:
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for place_info in data['geonames']:
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@@ -236,6 +238,11 @@ def search_geonames(toponym, df):
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lat.append(latitude)
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lon.append(longitude)
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print(latitude)
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print(longitude)
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@@ -261,6 +268,11 @@ def search_geonames(toponym, df):
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df['lat'] = lat
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df['lon'] = lon
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result = torch.cat(result, dim=1).detach().numpy()
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return result
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@@ -275,6 +287,7 @@ def get50Neigbors(locationID, dataset, k=50):
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lat, lon, geohash,name = input_row['Latitude'], input_row['Longitude'], input_row['Geohash'], input_row['Name']
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filtered_dataset = dataset.loc[dataset['Geohash'].str.startswith(geohash[:7])].copy()
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filtered_dataset['distance'] = filtered_dataset.apply(
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@@ -414,17 +427,20 @@ def showing(df):
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size_scale = 100
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color_scale = 255
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for i in range(len(df)):
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lat, lon, prob = df.iloc[i]['lat'], df.iloc[i]['lon'], df.iloc[i]['prob']
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size = int(prob**2 * size_scale )
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color = int(prob**2 * color_scale)
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folium.CircleMarker(
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location=[lat, lon],
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radius=size,
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color=f'#{color:02X}0000',
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fill=True,
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fill_color=f'#{color:02X}0000'
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).add_to(m)
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m.save("map.html")
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@@ -486,7 +502,6 @@ def mapping(selected_place,locations, sentence_info):
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def show_on_map():
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-
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input = st.text_area("Enter a sentence:", height=200)
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st.button("Submit")
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import streamlit as st
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import folium
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from streamlit.components.v1 import html
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from haversine import haversine, Unit
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lat=[]
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lon=[]
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name=[]
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country=[]
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fcodeName=[]
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population=[]
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if 'geonames' in data:
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for place_info in data['geonames']:
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lat.append(latitude)
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lon.append(longitude)
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name.append(place_info.get('name', ''))
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country.append(place_info.get('countryName', ''))
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fcodeName.append(place_info.get('fcodeName', ''))
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population.append(place_info.get('population', ''))
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print(latitude)
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print(longitude)
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df['lat'] = lat
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df['lon'] = lon
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df['name']=name
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df['country']=country
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df['fcodeName']=fcodeName
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df['population']=population
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result = torch.cat(result, dim=1).detach().numpy()
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return result
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lat, lon, geohash,name = input_row['Latitude'], input_row['Longitude'], input_row['Geohash'], input_row['Name']
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filtered_dataset = dataset.loc[dataset['Geohash'].str.startswith(geohash[:7])].copy()
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filtered_dataset['distance'] = filtered_dataset.apply(
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size_scale = 100
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color_scale = 255
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for i in range(len(df)):
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lat, lon, prob, name, country,fcodeName,population = df.iloc[i]['lat'], df.iloc[i]['lon'], df.iloc[i]['prob'],df.iloc[i]['name'],df.iloc[i]['country'],df.iloc[i]['fcodeName'],df.iloc[i]['population']
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size = int(prob**2 * size_scale )
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color = int(prob**2 * color_scale)
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popup_info= f"<strong>Name:</strong>{name} <br/><strong>Country:</strong> {country}<br/> <strong>fcodeName:</strong> {fcodeName} <br/><strong>population:</strong>{population}"
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folium.CircleMarker(
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location=[lat, lon],
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radius=size,
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color=f'#{color:02X}0000',
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fill=True,
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fill_color=f'#{color:02X}0000',
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popup=popup_info
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).add_to(m)
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m.save("map.html")
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def show_on_map():
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input = st.text_area("Enter a sentence:", height=200)
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st.button("Submit")
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requirements.txt
ADDED
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@@ -0,0 +1,17 @@
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streamlit==0.89.0
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torch==2.1.0
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transformers @ git+https://github.com/zekun-li/transformers@geolm
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scipy
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rank_bm25
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scikit-image
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geopandas
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pandas
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numpy
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requests==2.26.0
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folium
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rasterio
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streamlit_folium
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opencv-python
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torchvision
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matplotlib
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haversine
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