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Update emotion_predictor.py
Browse files- emotion_predictor.py +1 -21
emotion_predictor.py
CHANGED
@@ -10,7 +10,6 @@ from sklearn.linear_model import LinearRegression
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from collections import defaultdict
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import base64
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from io import BytesIO
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import streamlit as st
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# ํฐํธ ์ค์
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font_path = './NanumGothic.ttf'
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@@ -136,23 +135,4 @@ def predict_and_plot(raw_text):
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else:
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html_output += "<p>โ ๏ธ ์๊ฐํํ ์ ์๋ ๊ฐ์ ์ด ์์ต๋๋ค.</p><hr/>"
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return html_output
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# ํ์ผ ์
๋ก๋ ์ฒ๋ฆฌ ํจ์
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def upload_and_analyze():
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uploaded_file = st.file_uploader("ํ
์คํธ ํ์ผ ์
๋ก๋", type=["txt"])
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if uploaded_file is not None:
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# ํ์ผ ๋ด์ฉ ์ฝ๊ธฐ
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raw_text = uploaded_file.getvalue().decode("utf-8")
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# ์์ธก ๋ฐ ์๊ฐํ
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html_output = predict_and_plot(raw_text)
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# ์ถ๋ ฅ ๊ฒฐ๊ณผ๋ฅผ HTML๋ก ๋ณด์ฌ์ฃผ๊ธฐ
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st.markdown(html_output, unsafe_allow_html=True)
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# Streamlit ์ฑ ์คํ
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if __name__ == "__main__":
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st.title("๊ฐ์ ๋ถ์๊ธฐ")
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st.write("ํ
์คํธ ํ์ผ์ ์
๋ก๋ํ์ฌ ๊ฐ์ ๋ถ์์ ํด๋ณด์ธ์.")
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upload_and_analyze()
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from collections import defaultdict
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import base64
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from io import BytesIO
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# ํฐํธ ์ค์
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font_path = './NanumGothic.ttf'
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else:
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html_output += "<p>โ ๏ธ ์๊ฐํํ ์ ์๋ ๊ฐ์ ์ด ์์ต๋๋ค.</p><hr/>"
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return html_output
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