Update app.py

app.py

@@ -18,19 +18,19 @@ from gradio_image_prompter import ImagePrompter
 
 #sam_hq_model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-huge")
 #sam_hq_processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-huge")
-sam_hq_model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base")
+sam_hq_model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base", device_map="auto", torch_dtype="auto")
 sam_hq_processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base")
 
 #sam_model = SamModel.from_pretrained("facebook/sam-vit-huge")
 #sam_processor = SamProcessor.from_pretrained("facebook/sam-vit-huge")
-sam_model = SamModel.from_pretrained("facebook/sam-vit-base")
+sam_model = SamModel.from_pretrained("facebook/sam-vit-base", device_map="auto", torch_dtype="auto")
 sam_processor = SamProcessor.from_pretrained("facebook/sam-vit-base")
 
 @spaces.GPU
 def predict_masks_and_scores(model, processor, raw_image, input_points=None, input_boxes=None):
     if input_boxes is not None:
         input_boxes = [input_boxes]
-    inputs = processor(raw_image, input_boxes=input_boxes, input_points=input_points, return_tensors="pt")
+    inputs = processor(raw_image, input_boxes=input_boxes, input_points=input_points, return_tensors="pt").to(model.device)
     with torch.no_grad():
         outputs = model(**inputs)
 
@@ -118,6 +118,7 @@ with gr.Blocks(theme=theme, title="🔍 Compare SAM vs SAM-HQ") as demo:
     gr.Interface(
         fn=process_inputs,
         examples=example_paths,
+        cache_examples=False,
         inputs=ImagePrompter(show_label=False),
         outputs=result_html,
     )