app.py

import streamlit as st
import pickle
import numpy as np

# Define the path to your model file
MODEL_PATH = 'MODEL_PATH = 'cloth_recommendation (3).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}')