Update app.py

app.py

@@ -1,10 +1,9 @@
 import gradio as gr
-import sahi
+from gradio.mix import SquareImageMixin
 import torch
 from ultralyticsplus import YOLO, render_model_output
 
-
-
+# Define the model names
 model_names = [
     "yolov8n-seg.pt",
     "yolov8s-seg.pt",
@@ -53,6 +52,7 @@ def yolov8_inference(
     return renders[0]
 
 
+# Define the input and output components
 inputs = [
     gr.Image(type="filepath", label="Input Image"),
     gr.Dropdown(
@@ -68,13 +68,15 @@ inputs = [
 ]
 
 outputs = gr.Image(type="filepath", label="Output Image")
-title = "Ultralytics YOLOv8 Segmentation Demo"
 
+# Define the title and examples
+title = "Ultralytics YOLOv8 Segmentation Demo"
 examples = [
     ["ikun.jpg", "yolov8m-seg.pt", 640, 0.6, 0.45],
     ["people.png", "yolov8m-seg.pt", 640, 0.25, 0.45],
-
 ]
+
+# Create the Gradio interface
 demo_app = gr.Interface(
     fn=yolov8_inference,
     inputs=inputs,
@@ -84,4 +86,15 @@ demo_app = gr.Interface(
     cache_examples=True,
     theme="default",
 )
+
+# Set the custom CSS style with background image
+demo_app.css = """
+body {
+    background-image: url('backbone.jpg'); /* URL of your background image */
+    background-size: cover; /* Cover the entire interface */
+    background-position: center; /* Center the background image */
+}
+"""
+
+# Launch the interface
 demo_app.launch(debug=True, enable_queue=True)