feat: better placeholder

app.py

@@ -1,7 +1,26 @@
 import gradio as gr
+import cv2
+from PIL import Image
+import numpy as np
+from gradio import components
 
-def greet(name):
-    return "Hello " + name + "!!"
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+def segment_and_show(image):
+    image = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
+
+    # TODO: Implement segmentation logic here
+    return Image.fromarray(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
+
+
+default_image = Image.open("demo.jpeg")
+
+iface = gr.Interface(
+    fn=segment_and_show,
+    inputs=components.Image(value=default_image),
+    outputs=components.Image(type="pil"),
+    title="Urban Autonomy Instance Segmentation Demo",
+    description="Upload an image or use the default to see the instance segmentation model in action.",
+)
+
+if __name__ == "__main__":
+    iface.launch()

requirements.txt

@@ -0,0 +1 @@
+opencv-python