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import streamlit as st | |
import pickle | |
import numpy as np | |
# Define the path to your model file | |
MODEL_PATH = 'cloth_recommendation.pkl' | |
# Load the trained model | |
with open(MODEL_PATH, 'rb') as f: | |
model = pickle.load(f) | |
# Function to predict size | |
def predict_size(height, weight, age): | |
return model.predict(np.array([[height, weight, age]]))[0] | |
# Streamlit UI | |
st.title('Size Prediction App') | |
st.write("Enter the following details to predict the size:") | |
height = st.number_input('Height (cm)', min_value=0.0, step=0.1) | |
weight = st.number_input('Weight (kg)', min_value=0.0, step=0.1) | |
age = st.number_input('Age (years)', min_value=0.0, step=0.1) | |
if st.button('Predict Size'): | |
size = predict_size(height, weight, age) | |
st.write(f'Predicted Size: {size:.2f}') | |