initial commit

app.py

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+import pickle
+import streamlit as st
+import numpy as np
+import os
+
+# Load the regression model
+with open("regression_model.pkl", "rb") as f:
+    regression_model = pickle.load(f)
+
+print("Regression model loaded successfully!")
+
+# Load the classification model
+with open("classification_model.pkl", "rb") as f:
+    classification_model = pickle.load(f)
+
+print("Model loaded successfully!")
+
+# Streamlit UI
+st.title("🌍 Air Pollution Prediction System")
+
+st.sidebar.header("Enter Environmental Factors:")
+temperature = st.sidebar.number_input("Temperature (°C)", min_value=-10.0, max_value=50.0, value=25.0)
+humidity = st.sidebar.number_input("Humidity (%)", min_value=0.0, max_value=100.0, value=50.0)
+pm10 = st.sidebar.number_input("PM10 Level", min_value=0.0, max_value=500.0, value=20.0)
+no2 = st.sidebar.number_input("NO2 Level", min_value=0.0, max_value=500.0, value=15.0)
+so2 = st.sidebar.number_input("SO2 Level", min_value=0.0, max_value=500.0, value=10.0)
+co = st.sidebar.number_input("CO Level", min_value=0.0, max_value=10.0, value=1.0)
+industrial_proximity = st.sidebar.slider("Proximity to Industrial Areas", 0.0, 10.0, 5.0)
+population_density = st.sidebar.number_input("Population Density", min_value=0, max_value=10000, value=500)
+
+# Collect input into an array
+features = np.array([[temperature, humidity, pm10, no2, so2, co, industrial_proximity, population_density]])
+
+# Predict PM2.5 Level (Regression)
+if st.sidebar.button("Predict PM2.5 Level"):
+    pm25_pred = regression_model.predict(features)
+    st.write(f"**Predicted PM2.5 Level:** {pm25_pred[0]:.2f}")
+
+# Predict Air Quality (Classification)
+if st.sidebar.button("Predict Air Quality Level"):
+    air_quality_pred = classification_model.predict(features)
+    quality_map = {0: "Good", 1: "Moderate", 2: "Unhealthy", 3: "Hazardous"}
+    st.write(f"**Predicted Air Quality Level:** {quality_map[air_quality_pred[0]]}")

classification_model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:4bd899d04440ab2fe1be4ebd1f2d8fa5267e4a7b858834e86841b29ce2b76931
+size 4628134

regression_model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8a94f357d7debc4269eabd0f7d91630f159b3d170756f8599a78d28af669323e
+size 720