Update app.py
Browse files
app.py
CHANGED
@@ -25,20 +25,21 @@ suspicious_words = [
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"saboteur", "suicide", "discreet", "hide", "action", "profile", "alert", "vigilant", "clandestine", "riot", "arms", "deal"
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]
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questions = ["What event is going to take place?", "Where is it going to happen", "What time is it going to happen?"]
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# Initialize Streamlit app
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st.title("Crime Detection App")
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# Load data
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df = pd.read_excel('
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parsed_column = df['sentences'].to_list()
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# Process sentences and store results
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output_data = {'Crime Detected': [], 'Location Detected': [], 'Time Detected': []}
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for sentence in parsed_column:
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answers = nlp(
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cw = set(answers[0]['answer'].lower().split()) & set(suspicious_words)
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if cw:
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"saboteur", "suicide", "discreet", "hide", "action", "profile", "alert", "vigilant", "clandestine", "riot", "arms", "deal"
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]
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# Initialize Streamlit app
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st.title("Crime Detection App")
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# Load data
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df = pd.read_excel('senti.xlsx')
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parsed_column = df['sentences'].to_list()
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# Process sentences and store results
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output_data = {'Crime Detected': [], 'Location Detected': [], 'Time Detected': []}
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for sentence in parsed_column:
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answers = nlp({'question': "What event is going to take place?", 'context': sentence},
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{'question': "Where is it going to happen", 'context': sentence},
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{'question': "What time is it going to happen?", 'context': sentence})
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cw = set(answers[0]['answer'].lower().split()) & set(suspicious_words)
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if cw:
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