ML-model / app.py
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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}')