Update app.py

app.py

@@ -18,11 +18,9 @@ import torch
 from segment_anything import sam_model_registry, SamPredictor
 
 # --- CONFIG ---
-SAM_CHECKPOINT = "sam_vit_h_4b8939.pth"
 SAM_MODEL_TYPE = "vit_h"
 DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
 BLUR_RADIUS = 10
-DEMO_IMAGE = "demo.png"   # put a demo image in the repo
 # --------------
 
 sam = sam_model_registry[SAM_MODEL_TYPE](checkpoint=SAM_CHECKPOINT)
@@ -64,14 +62,20 @@ def isolate_with_click(image: Image.Image, evt: gr.SelectData):
     rgba = np.dstack((fg_rgb, (fg_alpha * 255).astype(np.uint8)))
     return Image.fromarray(rgba)
 
+# --- Gradio UI ---
 with gr.Blocks() as demo:
-    gr.Markdown("### SAM Object Isolation\nUpload an image or use the demo below, then click on the object to isolate it.")
+    gr.Markdown("### SAM Object Isolation\nUpload an image, then click on the object to isolate it.")
 
     inp = gr.Image(type="pil", label="Upload image", interactive=True)
-    demo_img = gr.Image(value=DEMO_IMAGE, type="pil", label="Demo image (click to try)", interactive=True)
     out = gr.Image(type="pil", label="Isolated cutout (RGBA)")
 
     inp.select(isolate_with_click, inputs=[inp], outputs=out)
-    demo_img.select(isolate_with_click, inputs=[demo_img], outputs=out)
+
+    # Examples section at the bottom
+    gr.Examples(
+        examples=["demo.jpg"],   # put demo.jpg in repo
+        inputs=inp,
+        label="Try with demo image"
+    )
 
 demo.launch()