Update app.py

app.py

@@ -7,11 +7,48 @@ from PIL import Image
 import io
 import torch
 
+# Set page config
+st.set_page_config(page_title="Building Detection App", page_icon="🏢", layout="wide")
+
+# Custom CSS
+st.markdown("""
+<style>
+    .reportview-container {
+        background: #f0f2f6
+    }
+    .main {
+        background-color: #ffffff;
+        padding: 2rem;
+        border-radius: 10px;
+        box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
+    }
+    .stButton>button {
+        background-color: #4CAF50;
+        color: white;
+        font-weight: bold;
+        border: none;
+        border-radius: 5px;
+        padding: 0.5rem 1rem;
+        transition: all 0.3s;
+    }
+    .stButton>button:hover {
+        background-color: #45a049;
+        box-shadow: 0 2px 4px rgba(0, 0, 0, 0.2);
+    }
+    .upload-box {
+        border: 2px dashed #4CAF50;
+        border-radius: 10px;
+        padding: 2rem;
+        text-align: center;
+    }
+</style>
+""", unsafe_allow_html=True)
+
 # Load the YOLO model
 @st.cache_resource
 def load_model():
-    model = YOLO("mosaic_medium_100_tiny_object.pt")  
-    model.to('cpu')  
+    model = YOLO("mosaic_medium_100_tiny_object.pt")  # Update this to the filename of your model
+    model.to('cpu')  # Ensure the model is on CPU
     return model
 
 model = load_model()
@@ -44,18 +81,52 @@ def process_image(image):
     return cv2.cvtColor(annotated_image, cv2.COLOR_BGR2RGB)
 
 def main():
-    st.title("Detect Buildings through Satellite Images")
+    st.title("🏢 Building Detection App")
+    st.markdown("Upload an image to detect buildings using our advanced AI model.")
+
+    col1, col2 = st.columns(2)
+
+    with col1:
+        st.markdown("### Upload Image")
+        uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
+        
+        if uploaded_file is not None:
+            image = Image.open(uploaded_file)
+            st.image(image, caption="Uploaded Image", use_column_width=True)
+            
+            if st.button("🔍 Detect Buildings"):
+                with st.spinner("Processing..."):
+                    result_image = process_image(image)
+                    with col2:
+                        st.markdown("### Detection Results")
+                        st.image(result_image, caption="Processed Image", use_column_width=True)
+                    st.success("Detection completed successfully!")
+        else:
+            st.markdown(
+                """
+                <div class="upload-box">
+                    <h3>📁 Upload an image to get started</h3>
+                    <p>Supported formats: JPG, JPEG, PNG</p>
+                </div>
+                """,
+                unsafe_allow_html=True
+            )
 
-    uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
+    with col2:
+        if uploaded_file is None:
+            st.markdown("### How it works")
+            st.markdown(
+                """
+                1. **Upload** an image using the file uploader on the left.
+                2. Click the **Detect Buildings** button to process the image.
+                3. View the results with bounding boxes around detected buildings.
 
-    if uploaded_file is not None:
-        image = Image.open(uploaded_file)
-        st.image(image, caption="Uploaded Image", use_column_width=True)
+                Our AI model is trained to identify various types of buildings from satellite images.
+                """
+            )
 
-        if st.button("Detect Buildings"):
-            with st.spinner("Processing..."):
-                result_image = process_image(image)
-                st.image(result_image, caption="Processed Image", use_column_width=True)
+    st.markdown("---")
+    st.markdown("Developed with ❤️ using Streamlit and YOLOv8")
 
 if __name__ == "__main__":
     main()