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import streamlit as st
import leafmap.foliumap as leafmap
import whitebox
st.set_page_config(layout="wide")
st.sidebar.info(
"""
- Web App URL: <https://interactive-crime-map.hf.space/>
- HuggingFace repository: <https://huggingface.co/spaces/interactive-crime/map/tree/main>
"""
)
st.sidebar.title("Contact")
st.sidebar.info(
"""
Yunus Serhat Bıçakçı at [yunusserhat.com](https://yunusserhat.com) | [GitHub](https://github.com/yunusserhat) | [Twitter](https://twitter.com/yunusserhat) | [LinkedIn](https://www.linkedin.com/in/yunusserhat)
"""
)
st.title("Hate Speech Interactive Map Application")
please_note = '<p style="color:Red; font-weight:bold;">Please note that the information displayed may contain sentences containing hateful content. Kindly keep this in mind before reviewing the details.</p>'
st.markdown(
"""
The interactive map illustrate a hate crime tweets in London boroughs for the month of December 2022. Model 1 is the latest model from [TweetNLP](https://arxiv.org/pdf/2206.14774.pdf) and [CardiffNLP](https://huggingface.co/cardiffnlp/twitter-roberta-base-hate-multiclass-latest), and Model 2 is an older version of Model 1, owned by [Dimosthenis Antypas](https://huggingface.co/antypasd/). Both models have been utilized for hate speech detection.
"""
)
st.markdown(please_note, unsafe_allow_html=True)
st.markdown(
"""
"""
)
# add whitebox tools to the map
m = leafmap.Map(center=[51.50, -0.1], zoom=10)
tweets2 = 'https://raw.githubusercontent.com/yunusserhat/data/main/data/London2022DecHateTweetsLatLong.csv'
borough2 = 'https://raw.githubusercontent.com/yunusserhat/data/main/data/londonborough.geojson'
tweets = 'https://raw.githubusercontent.com/yunusserhat/data/main/data/multiclass_latest_latlng.csv'
borough = 'https://raw.githubusercontent.com/yunusserhat/data/main/data/londonborough.geojson'
map_option = st.selectbox('Choose a Map', ('Model 1', 'Model 2'))
#palette_model_1 = ["red", "blue", "green", "yellow", "purple", "orange"]
#palette_model_2 = ["red", "blue", "green", "yellow", "purple"]
if map_option == 'Model 1':
m.add_geojson(borough, layer_name='London Boroughs')
m.add_points_from_xy(
tweets,
x="Longitude",
y="Latitude",
color_column='Hate Prediction',
palette="RedYellowBlue_11",
spin=True,
add_legend=True
)
else:
m.add_geojson(borough2, layer_name='London Boroughs 2')
m.add_points_from_xy(
tweets2,
x="Longitude",
y="Latitude",
color_column='Hate Prediction',
palette="GreenMagenta_16",
spin=True,
add_legend=True
)
m.to_streamlit()
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