Update app.py

app.py

@@ -6,11 +6,11 @@ import matplotlib.pyplot as plt
 import seaborn as sns
 
 # ----------- Page Configuration ------------
-st.set_page_config("Smart Sleep Monitor", layout="wide")
-st.title(" 🌚 Smart Sleep Monitoring System")
+st.set_page_config("Smart Sleep Monitoring System", layout="wide")
+st.title(" Sleep State Detection App")
 
 # ----------- Navigation Sidebar ------------
-page = st.sidebar.radio("📍 Navigate", ["Overview", "EDA", "Predict"])
+page = st.sidebar.radio("📍 Navigation", ["Overview", "EDA", "Predict"])
 
 # ----------- Load Data & Model ------------
 @st.cache_data
@@ -32,35 +32,35 @@ def plot_histogram(df, column, color):
 
 # ----------- Overview Page ------------
 if page == "Overview":
-    st.header(" 🔎 Project Overview")
-    st.markdown("This application predicts **sleep** and **wake** states using data from wearable sensors, focusing on `anglez` and `enmo` values to monitor body motion and position.")
+    st.header(" Project Overview")
+    st.markdown("This app detects **sleep onset** and **wake-up states** using `anglez` and `enmo` values from a wearable sensor.")
 
-    with st.expander(" 📄 Problem Statement"):
+    with st.expander(" Problem Statement"):
         st.markdown("""
-        - Increasing mental health issues in fast-paced environments are linked to poor sleep quality.
-        - This system helps in early identification of irregular sleep patterns to support healthier lifestyles.
+        - Detect sleep and wake-up periods using wearable sensor data.  
+        - Sleep is estimated from low-movement patterns.
         """)
 
-    with st.expander(" 🔮 Objective"):
+    with st.expander(" Objective"):
         st.markdown("""
-        - Accurately classify sleep vs wake states using sensor inputs
-        - Provide doctors and users with actionable insights into sleep behavior
-        - Develop lightweight, real-time deployable models
+        - Classify sleep vs wake states  
+        - Build an ML model that generalizes to real users  
         """)
 
-    with st.expander(" ⚠️ Constraints"):
+    with st.expander(" Constraints"):
         st.markdown("""
-        - Noisy or missing data from wearables
-        - Balancing sensitivity with low false-positive rate
-        - Ensuring usability across diverse users and environments
+        - Missing or noisy data  
+        - Ensure low false alarms  
+        - Simple, real-time capable models  
         """)
 
 # ----------- EDA Page ------------
 elif page == "EDA":
-    st.header(" 🔍 Exploratory Data Analysis")
+    st.header(" Exploratory Data Analysis")
     df = load_data("cleaned_sleep_data.csv")
 
-    st.markdown("### 🔍 Filter by Sleep State")
+    # ---- Multi-select Filter Sleep/Wake ----
+    st.markdown("### 🔎 Filter by Sleep State")
     state_options = st.multiselect("Select sleep states to display", ["Sleep", "Wake-Up"], default=["Sleep", "Wake-Up"])
 
     if state_options:
@@ -68,46 +68,52 @@ elif page == "EDA":
         selected_values = [filter_map[opt] for opt in state_options]
         df = df[df["sleep"].isin(selected_values)]
 
+    # ---- Histograms ----
     col1, col2 = st.columns(2)
     with col1:
         st.subheader(" Anglez")
-        plot_histogram(df, "anglez", "#6c5ce7")
-        st.markdown("- Postural behavior during rest")
+        plot_histogram(df, "anglez", "#74b9ff")
+        st.markdown("- Distribution typical of rest posture")
 
     with col2:
         st.subheader(" ENMO")
-        plot_histogram(df, "enmo", "#00cec9")
-        st.markdown("- Captures motion intensity")
+        plot_histogram(df, "enmo", "#81ecec")
+        st.markdown("- ENMO reflects movement intensity")
 
+    # ---- Pairplot ----
     st.subheader(" Feature Relationships")
     with st.spinner("Creating pairplot..."):
-        pairplot_fig = sns.pairplot(df, vars=['anglez', 'enmo'], hue='sleep', palette='Set2')
+        pairplot_fig = sns.pairplot(df, vars=['anglez', 'enmo'], hue='sleep', palette='coolwarm')
         st.pyplot(pairplot_fig.fig, use_container_width=True)
         plt.close()
 
+    # ---- Boxplots ----
     st.subheader(" Boxplots")
     fig, axs = plt.subplots(1, 2, figsize=(12, 5))
-    sns.boxplot(y=df["anglez"], ax=axs[0], color='#6c5ce7')
+    sns.boxplot(y=df["anglez"], ax=axs[0], color='#74b9ff')
     axs[0].set_title("Boxplot: Anglez")
-    sns.boxplot(y=df["enmo"], ax=axs[1], color='#00cec9')
+    sns.boxplot(y=df["enmo"], ax=axs[1], color='#81ecec')
     axs[1].set_title("Boxplot: ENMO")
     st.pyplot(fig, use_container_width=True)
     plt.close()
 
+    # ---- Correlation ----
     st.subheader(" Correlation Heatmap")
     fig, ax = plt.subplots()
-    sns.heatmap(df[["anglez", "enmo"]].corr(), annot=True, cmap="Purples", ax=ax)
+    sns.heatmap(df[["anglez", "enmo"]].corr(), annot=True, cmap="coolwarm", ax=ax)
     st.pyplot(fig, use_container_width=True)
     plt.close()
 
 # ----------- Predict Page ------------
 elif page == "Predict":
-    st.header(" 🤖 Sleep Prediction")
+    st.header(" Sleep Prediction")
     model = load_model("new_sleep_model.pkl")
 
+    # ---- Sleep/Wake Filter Dropdown
     st.markdown("###  Select Sample Type")
     state_choice = st.selectbox("Choose Sample Type", ["Custom Input", "Sleep Sample", "Wake-Up Sample"])
 
+    # ---- Default Values Based on Choice
     if state_choice == "Sleep Sample":
         default_anglez = -45.0
         default_enmo = 0.01
@@ -118,13 +124,15 @@ elif page == "Predict":
         default_anglez = 0.0
         default_enmo = 0.0
 
+    # ---- Input Sliders
     col1, col2 = st.columns(2)
     with col1:
         anglez = st.slider(" Anglez (-180° to 180°)", -180.0, 180.0, default_anglez)
     with col2:
         enmo = st.slider(" ENMO (0.0 to 1.0)", 0.0, 1.0, default_enmo)
 
-    if st.button(" 🔎 Predict Sleep State"):
+    # ---- Prediction
+    if st.button(" Predict Sleep State"):
         input_vector = np.array([[anglez, enmo]])
         prediction = model.predict(input_vector)[0]
 
@@ -142,13 +150,14 @@ elif page == "Predict":
         st.success(f"** Predicted State:** {label}")
         st.info(message)
 
+        # Display image based on prediction
         if prediction == 1:
             st.image(
-                "https://huggingface.co/spaces/DasariHarshitha/Sleep_Detection_App/resolve/main/th%20(1).jpeg",
+                "https://huggingface.co/spaces/Saidee156/AI_SLEEP_DETECTION/resolve/main/th%20(1).jpeg",
                 use_container_width=True,
             )
             st.markdown("""
-            ###  🛏️ Personalized Sleep Tips
+            ###  Personalized Sleep Tips
              **Tips to Fall Asleep Faster**  
             -  Avoid screens 30 mins before bed  
             -  Keep the room cool and dark  
@@ -157,13 +166,15 @@ elif page == "Predict":
             """)
         else:
             st.image(
-                "https://huggingface.co/spaces/DasariHarshitha/Sleep_Detection_App/resolve/main/cute-little-boy-wake-up-in-morning-stretching-hands-on-bed-in-bedroom-vector.jpg",
+                "https://huggingface.co/spaces/Saidee156/AI_SLEEP_DETECTION/resolve/main/cute-little-boy-wake-up-in-morning-stretching-hands-on-bed-in-bedroom-vector.jpg",
                 use_container_width=True,
             )
             st.markdown("""
-            ###  🌞 Tips to Wake Up Refreshed
+            ###  Tips to Wake Up Refreshed
             -  Get morning sunlight exposure  
             -  Move or stretch your body  
             -  Eat a light, energizing breakfast  
             -  Cold water splash or shower helps  
             """)
+
+