Create app.py

app.py

@@ -0,0 +1,53 @@
+import streamlit as st
+import numpy as np
+import pandas as pd
+import joblib
+import matplotlib.pyplot as plt
+import seaborn as sns
+from sklearn.metrics import confusion_matrix, ConfusionMatrixDisplay
+
+# Load model
+model = joblib.load("random_forest_model.pkl")
+
+# Page configuration
+st.set_page_config(page_title="Sleep  Detector ", layout="wide")
+
+# Custom CSS
+st.markdown("""
+    <style>
+    .main {
+        background-color: #f4f6f9;
+        font-family: 'Segoe UI', sans-serif;
+    }
+    h1, h2, h3 {
+        color: #333;
+    }
+    </style>
+""", unsafe_allow_html=True)
+
+st.title("😴 AI Sleep  Detection System")
+st.markdown("Navigate the Sleep Detection project through each CRISP-ML(Q) step.")
+
+st.header("🤖 Model Prediction")
+
+angle = st.number_input("📐 Enter Angle (0–360°)", 0.0, 360.0, step=0.1)
+enmo = st.number_input("📊 Enter ENMO (0.0000–10.0000)", 0.0, 10.0, step=0.0001, format="%.4f")
+
+if st.button("🔍 Predict Sleep State"):
+    input_data = np.array([[angle, enmo]])
+    prediction = model.predict(input_data)[0]
+    confidence = model.predict_proba(input_data)[0][prediction] * 100
+
+    label = "🌞 Wakeup" if prediction == 0 else "🌙 Sleep Onset"
+    color = "#ffcc00" if prediction == 0 else "#6699ff"
+
+    st.markdown(f"<h3 style='color:{color}'>🧠 Prediction: {label}</h3>", unsafe_allow_html=True)
+    st.markdown(f"**Confidence Score:** `{confidence:.2f}%`")
+
+    st.subheader("📋 Input Summary")
+    st.json({
+        "Angle": round(angle, 2),
+        "ENMO": round(enmo, 4),
+        "Predicted State": "Wakeup" if prediction == 0 else "Sleep Onset",
+        "Confidence (%)": round(confidence, 2)
+    })