Update app.py

app.py

@@ -12,12 +12,12 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
 model = SamModel.from_pretrained("facebook/sam-vit-base").to(device)
 processor = SamProcessor.from_pretrained("facebook/sam-vit-base")
 
-def segment_image(input_image, points):
+def segment_image(input_image, x, y):
     # Convert input_image to PIL Image
     input_image = Image.fromarray(input_image)
     
     # Prepare inputs
-    inputs = processor(input_image, input_points=[points], return_tensors="pt").to(device)
+    inputs = processor(input_image, input_points=np.array([[x, y]]), return_tensors="pt").to(device)
     
     # Generate masks
     with torch.no_grad():
@@ -47,11 +47,12 @@ iface = gr.Interface(
     fn=segment_image,
     inputs=[
         gr.Image(type="numpy"),
-        gr.Image(type="numpy", tool="sketch", brush_radius=5, label="Click on objects to segment")
+        gr.Slider(minimum=0, maximum=1000, step=1, label="X coordinate"),
+        gr.Slider(minimum=0, maximum=1000, step=1, label="Y coordinate")
     ],
     outputs=gr.Image(type="numpy"),
     title="Segment Anything Model (SAM) Image Segmentation",
-    description="Click on objects in the image to segment them using SAM."
+    description="Enter X and Y coordinates of the object you want to segment."
 )
 
 # Launch the interface