Update app.py
Browse files
app.py
CHANGED
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@@ -8,7 +8,6 @@ import nltk
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from nltk.tokenize import word_tokenize
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from nltk.corpus import stopwords
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from nltk.stem import WordNetLemmatizer
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-
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# Download necessary resources
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nltk.download('punkt_tab')
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nltk.download('stopwords')
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@@ -17,8 +16,8 @@ nltk.download('wordnet')
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import tensorflow
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import keras
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from keras.utils import pad_sequences
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import pickle
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import base64
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# Streamlit UI
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st.set_page_config(page_title="News Category Classifier", page_icon="📰", layout="centered")
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@@ -40,7 +39,7 @@ def set_background(image_path):
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st.markdown(bg_image_style, unsafe_allow_html=True)
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# Update the image path
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set_background("page/
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# Initialize stopwords and lemmatizer
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stop_words = set(stopwords.words('english')).union({"pm"})
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@@ -159,4 +158,4 @@ if st.button("Analyze 🏷️"):
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category = predict_category(user_input)
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st.markdown(f"<div class='result-box'><span class='result-text'>🗂️ Predicted Category: <strong>{category}</strong></span></div>", unsafe_allow_html=True)
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else:
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st.warning("⚠️ Please enter some text to analyze.")
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from nltk.tokenize import word_tokenize
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from nltk.corpus import stopwords
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from nltk.stem import WordNetLemmatizer
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# Download necessary resources
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nltk.download('punkt_tab')
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nltk.download('stopwords')
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import tensorflow
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import keras
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from keras.utils import pad_sequences
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+
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import pickle
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# Streamlit UI
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st.set_page_config(page_title="News Category Classifier", page_icon="📰", layout="centered")
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st.markdown(bg_image_style, unsafe_allow_html=True)
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# Update the image path
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set_background("page/News image 2.png") # Ensure the image is in the correct folder
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# Initialize stopwords and lemmatizer
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stop_words = set(stopwords.words('english')).union({"pm"})
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category = predict_category(user_input)
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st.markdown(f"<div class='result-box'><span class='result-text'>🗂️ Predicted Category: <strong>{category}</strong></span></div>", unsafe_allow_html=True)
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else:
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st.warning("⚠️ Please enter some text to analyze.")
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