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Update app.py
Browse files
app.py
CHANGED
@@ -9,8 +9,10 @@ import matplotlib.pyplot as plt
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import numpy as np
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import seaborn as sns
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# Load the model
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-
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-
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# Define the categories
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categories = {
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@@ -114,6 +116,8 @@ def main():
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# Input fields
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if selected_option == "Predict":
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with st.container():
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col1, col2, col3 = st.columns(3)
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getTitle, getDuration, getCategory = "", 0.00, 1
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@@ -161,7 +165,7 @@ def main():
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st.warning("Please enter a duration.")
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else:
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prediction = predict_trend(title, duration, categoryId)
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if prediction[0] == 1:
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st.success("This video is predicted to be a trend!")
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st.markdown("![Alt Text](https://media.tenor.com/Cyi2zT7wcmcAAAAj/pentol-gif-eak.gif)")
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@@ -182,7 +186,7 @@ def main():
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st.download_button(
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"Download",
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csv,
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"
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"text/csv",
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key='download-csv'
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)
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@@ -241,7 +245,7 @@ def main():
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show_top_titleLength()
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with col13:
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show_best_titleLength()
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-
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def get_picture_from_url(url):
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try:
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response = requests.get(url)
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@@ -388,7 +392,7 @@ def show_best_titleLength():
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st.write(f"<span style='color:{color};font-weight:bold;'>{range}</span>", unsafe_allow_html=True)
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# Function to make predictions
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def predict_trend(title, duration, category_id):
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duration = str(duration)
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category_id = int(category_id)
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clean_new_title = preprocess(title)
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import numpy as np
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import seaborn as sns
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# Load the model
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def read_model(region):
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if(region == "United States"):
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model = joblib.load('85pct(2).pkl')
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return model
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# Define the categories
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categories = {
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# Input fields
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if selected_option == "Predict":
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region = st.sidebar.selectbox("Select Region", ['United States'])
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model = read_model(region)
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with st.container():
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col1, col2, col3 = st.columns(3)
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getTitle, getDuration, getCategory = "", 0.00, 1
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st.warning("Please enter a duration.")
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else:
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prediction = predict_trend(model,title, duration, categoryId)
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if prediction[0] == 1:
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st.success("This video is predicted to be a trend!")
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st.markdown("![Alt Text](https://media.tenor.com/Cyi2zT7wcmcAAAAj/pentol-gif-eak.gif)")
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st.download_button(
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"Download",
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csv,
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"top10Trending.csv",
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"text/csv",
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key='download-csv'
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)
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show_top_titleLength()
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with col13:
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show_best_titleLength()
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def get_picture_from_url(url):
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try:
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response = requests.get(url)
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st.write(f"<span style='color:{color};font-weight:bold;'>{range}</span>", unsafe_allow_html=True)
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# Function to make predictions
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def predict_trend(model,title, duration, category_id):
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duration = str(duration)
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category_id = int(category_id)
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clean_new_title = preprocess(title)
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