Create app.py

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 = '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}')