Create app.py

app.py

@@ -0,0 +1,49 @@
+import pickle
+import streamlit as st
+
+# Load the model
+with open("BMI_Model.pkl", "rb") as f:
+    model_data = pickle.load(f)
+
+def conditional_prediction(Gender, Height, Weight):
+    Gen = 0
+    if Gender == "Male":
+        Gen = 1
+    elif Gender == "Female":
+        Gen = 0
+
+    Height = float(Height)
+    Weight = float(Weight)
+    
+    result = model_data.predict([[Gen, Height, Weight]])
+    
+    if result[0] == 0:
+        final_result = "You have an Extremely Weak Body Condition"
+    elif result[0] == 1:
+        final_result = "You have a Weak Body Condition"
+    elif result[0] == 2:
+        final_result = "You have a Normal Body Condition"
+    elif result[0] == 3:
+        final_result = "You have Estimated Overweight"
+    elif result[0] == 4:
+        final_result = "You have Estimated Obesity"
+    elif result[0] == 5:
+        final_result = "You seem to have Extreme Obesity"
+    
+    return final_result, result[0]
+
+# Streamlit UI
+st.title("BMI Condition Estimator")
+
+# Input fields
+Gender = st.radio("Gender", ["Male", "Female"])
+Height = st.text_input("Enter Your Height in cm")
+Weight = st.text_input("Enter Your Weight in KG")
+
+if st.button("Predict"):
+    if Height and Weight:
+        condition, index = conditional_prediction(Gender, Height, Weight)
+        st.write(f"Your Estimated Condition: {condition}")
+        st.write(f"Index: {index}")
+    else:
+        st.write("Please enter both Height and Weight.")