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51a55f7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 | import streamlit as st
from joblib import load
# Load model
Model = load('svm.joblib')
def predict_note_authentication(values):
prediction = Model.predict([values])
return prediction[0]
def main():
st.set_page_config(page_title='Mobile Price Classification', layout='wide')
# Custom CSS
st.markdown("""
<style>
.main {background-color: #f4f4f4;}
.title {color: white; text-align: center; font-size: 26px; font-weight: bold;}
.result {background-color: #4CAF50; padding: 10px; color: white; text-align: center; font-size: 22px; font-weight: bold; border-radius: 10px;}
.predict-button {display: flex; justify-content: center; margin-top: 20px;}
.stButton>button {background-color: #ff5733; color: white; font-size: 18px; font-weight: bold; padding: 10px 20px; border-radius: 10px;}
.stButton>button:hover {background-color: #e64a19;}
</style>
""", unsafe_allow_html=True)
# Title Section
st.markdown("""
<div style="background-color:#ff5733;padding:15px;border-radius:10px;">
<h2 class="title">Predict the Price Range of a Mobile</h2>
</div>
""", unsafe_allow_html=True)
# Input Fields in 3 Columns
col1, col2, col3 = st.columns(3)
with col1:
battery_power = st.number_input('Battery Power (mAh)', min_value=500, max_value=2000, step=10)
colour = st.selectbox('Colour', ['Blue', 'Other'])
clock_speed = st.number_input('Clock Speed (GHz)', min_value=0.5, max_value=3.0, step=0.1)
sim = st.selectbox('SIM Option', ['Dual', 'Single'])
front_camera = st.number_input('Front Camera (MP)', min_value=0, max_value=20, step=1)
network_4G = st.selectbox('Network (4G)', ['Yes', 'No'])
network_3G = st.selectbox('Network (3G)', ['Yes', 'No'])
with col2:
int_memory = st.number_input('Internal Memory (GB)', min_value=2, max_value=64, step=1)
mobile_depth = st.selectbox('Mobile Depth (cm)', [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0])
mobile_wt = st.number_input('Mobile Weight (grams)', min_value=80, max_value=200, step=1)
n_cores = st.selectbox('Number of Cores', [1, 2, 3, 4, 5, 6, 7, 8])
primary_camera = st.number_input('Primary Camera (MP)', min_value=0, max_value=20, step=1)
px_height = st.number_input('Screen Pixel Height', min_value=0, max_value=2000, step=10)
px_width = st.number_input('Screen Pixel Width', min_value=100, max_value=2000, step=10)
with col3:
ram = st.number_input('RAM (MB)', min_value=256, max_value=4000, step=10)
screen_height = st.number_input('Screen Height (cm)', min_value=0, max_value=20, step=1)
screen_width = st.number_input('Screen Width (cm)', min_value=0, max_value=20, step=1)
talk_time = st.number_input('Talk Time (hours)', min_value=1, max_value=20, step=1)
touch_screen = st.selectbox('Touch Screen', ['Yes', 'No'])
wifi = st.selectbox('Wi-Fi Support', ['Yes', 'No'])
# Processing Inputs
colour = 1 if colour == 'Blue' else 0
sim = 1 if sim == 'Dual' else 0
four_g = 1 if network_4G == 'Yes' else 0
three_g = 1 if network_3G == 'Yes' else 0
touch_screen = 1 if touch_screen == 'Yes' else 0
wifi = 1 if wifi == 'Yes' else 0
values = [
battery_power, colour, clock_speed, sim, front_camera, four_g, int_memory, mobile_depth, mobile_wt,
n_cores, primary_camera, px_height, px_width, ram, screen_height, screen_width, talk_time, three_g,
touch_screen, wifi
]
# Predict and Display Result
st.markdown("<div class='predict-button'>", unsafe_allow_html=True)
if st.button("Predict", help="Click to predict the mobile price range"):
result = predict_note_authentication(values)
st.markdown(f'<div class="result">Predicted Price Class: {result}</div>', unsafe_allow_html=True)
st.markdown("</div>", unsafe_allow_html=True)
if __name__ == "__main__":
main()
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