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app.py

@@ -25,30 +25,35 @@ crop = st.selectbox("🌱 Crop", ["Rice", "Wheat", "Cotton", "Maize", "Pulses"])
 season = st.selectbox("🗓️ Season", ["Kharif", "Rabi", "Whole Year"])
 crop_year = st.number_input("📅 Crop Year", min_value=1990, max_value=2025, value=2024)
 
-area = st.number_input("🌾 Area (hectares)", min_value=0.1, step=0.1)
-production = st.number_input("📦 Production (tonnes)", min_value=0.1, step=0.1)
+area_acres = st.number_input("🌾 Area (in acres)", min_value=0.1, step=0.1)
+production_bags = st.number_input("📦 Production (in bags)", min_value=1, step=1)
 bag_weight = st.number_input("⚖️ Bag Weight (kg)", min_value=50, max_value=100, value=75)
 
 rainfall = st.number_input("🌧️ Annual Rainfall (mm)", min_value=0.0, step=1.0)
 fertilizer = st.number_input("💊 Fertilizer Used (kg)", min_value=0.0, step=1.0)
 pesticide = st.number_input("🧴 Pesticide Used (kg)", min_value=0.0, step=1.0)
 
+area_ha = area_acres / 2.47   # convert acres → hectares
+production_tonnes = (production_bags * bag_weight) / 1000  # convert bags → tonnes
 
 
-# --- Input DataFrame (aligned with training data) ---
 input_data = pd.DataFrame({
     "Crop": [crop],
     "Crop_Year": [crop_year],
     "Season": [season],
     "State": [state],
-    "Area": [area],
-    "Production": [production],
+    "Area": [area_ha],
+    "Production": [production_tonnes],
     "Annual_Rainfall": [rainfall],
     "Fertilizer": [fertilizer],
     "Pesticide": [pesticide],
 })
 
+
 # --- Prediction ---
 if st.button("🚀 Predict Yield"):
     prediction = model.predict(input_data)[0]   # model outputs yield in t/ha
     st.success(f"🌾 Estimated Yield: {prediction:.2f} t/ha")
+
+    prediction_bags_per_acre = (prediction * 2.47 * 1000) / bag_weight
+    st.info(f"Equivalent: {prediction_bags_per_acre:.2f} bags per acre")