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.gitattributes

@@ -33,3 +33,7 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+covid_xray_model.keras filter=lfs diff=lfs merge=lfs -text
+covid.jpg filter=lfs diff=lfs merge=lfs -text
+normal.jpeg filter=lfs diff=lfs merge=lfs -text
+WHO-COVID-19-global-data.csv filter=lfs diff=lfs merge=lfs -text

WHO-COVID-19-global-data.csv

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+version https://git-lfs.github.com/spec/v1
+oid sha256:c671cd13d4186f4917bb5ce6cbf26342e07cb46f2e5c4c87e7d8e87d2d091f70
+size 14718014

covid_xray_model.keras

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+version https://git-lfs.github.com/spec/v1
+oid sha256:537d9cc3bcf24288d784380ca34fd51e42db1d4a52ca2705b046f6503660cd5d
+size 286932881

requirements.txt

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+streamlit
+tensorflow==2.10.0
+keras
+pandas
+numpy
+matplotlib

runtime.txt

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+python-3.10

streamlit_app1.py

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+import streamlit as st
+import pandas as pd
+import numpy as np
+from tensorflow.keras.models import load_model
+from tensorflow.keras.preprocessing import image
+import matplotlib.pyplot as plt
+
+# ------------------------- PAGE CONFIG -------------------------
+st.set_page_config(page_title="COVID-19 AI System", layout="centered")
+
+# ------------------------- SIDEBAR -------------------------
+st.sidebar.image("https://i.imgur.com/NbA3RfI.png", use_container_width=True)  # Optional: Replace with your own logo
+st.sidebar.title("🧠 COVID-19 AI Dashboard")
+app_mode = st.sidebar.radio("📍 Select Module", ["🏠 Home", "🩻 X-ray Classifier", "📊 Global Data Analysis"])
+
+# ------------------------- CUSTOM CSS -------------------------
+st.markdown("""
+    <style>
+        .main { background-color: #f7f7f7; padding: 20px; border-radius: 10px; }
+        .title { text-align: center; font-size: 36px; color: #4A90E2; font-weight: bold; }
+        .subtitle { text-align: center; font-size: 18px; color: #444; }
+    </style>
+""", unsafe_allow_html=True)
+
+# ------------------------- HOME PAGE -------------------------
+if app_mode == "🏠 Home":
+    st.markdown('<div class="main"><div class="title">COVID-19 Detection & Analysis</div><div class="subtitle">An integrated AI system using Deep Learning and WHO data</div></div>', unsafe_allow_html=True)
+    st.write("Welcome to the COVID-19 AI dashboard. Use the sidebar to navigate between modules:")
+
+    st.markdown("""
+    - 🩻 **X-ray Classifier**: Upload a chest X-ray to detect COVID-19 using a deep learning model.
+    - 📊 **Global Data Analysis**: Explore real-world trends using WHO global COVID-19 dataset.
+    """)
+
+# ------------------------- X-RAY PREDICTION -------------------------
+elif app_mode == "🩻 X-ray Classifier":
+    st.header("🩺 Chest X-ray COVID Prediction")
+
+    uploaded_image = st.file_uploader("📤 Upload Chest X-ray", type=["jpg", "jpeg", "png"])
+
+    if uploaded_image:
+        with st.spinner("🔍 Predicting..."):
+            model = load_model("covid_xray_model.keras")
+            img = image.load_img(uploaded_image, target_size=(224, 224))
+            img_array = image.img_to_array(img) / 255.0
+            img_array = np.expand_dims(img_array, axis=0)
+
+            pred = model.predict(img_array)[0]
+            labels = ['COVID', 'NORMAL', 'Viral Pneumonia']
+            result = labels[np.argmax(pred)]
+
+            col1, col2 = st.columns([1, 2])
+            with col1:
+                st.image(uploaded_image, caption="Uploaded X-ray", use_container_width=True)
+            with col2:
+                st.success(f"🧠 **Predicted Condition:** `{result}`")
+
+# ------------------------- DATA ANALYSIS -------------------------
+elif app_mode == "📊 Global Data Analysis":
+    st.header("📊 WHO COVID-19 Data Analysis")
+
+    df = pd.read_csv("WHO-COVID-19-global-data.csv")
+    df["Date_reported"] = pd.to_datetime(df["Date_reported"])
+
+    top_countries = df.groupby("Country")["New_cases"].sum().sort_values(ascending=False).head(10)
+
+    st.subheader("🌍 Top 10 Countries by Total Reported Cases")
+    st.bar_chart(top_countries)
+
+    st.subheader("📈 Trend for Selected Country")
+    selected_country = st.selectbox("Choose a country", df["Country"].unique())
+    country_data = df[df["Country"] == selected_country]
+
+    col1, col2 = st.columns(2)
+    with col1:
+        st.markdown("**Daily New Cases**")
+        st.line_chart(country_data.set_index("Date_reported")[["New_cases"]])
+    with col2:
+        st.markdown("**Cumulative Cases Over Time**")
+        st.line_chart(country_data.set_index("Date_reported")[["Cumulative_cases"]])
+
+    with st.expander("📄 Show Raw Data"):
+        st.dataframe(country_data.tail(10))