Update app.py

app.py

@@ -6,14 +6,11 @@ from transformers import AutoModelForImageSegmentation
 import torch
 from torchvision import transforms
 
-# GPU 설정을 CPU로 변경
-# GPU 설정을 삭제하거나 "cuda"를 "cpu"로 변경
-# torch.set_float32_matmul_precision("high")는 CPU에선 필요 없음.
-
+# 모델을 전역으로 로드 (기본적으로 CPU에 로드)
 birefnet = AutoModelForImageSegmentation.from_pretrained(
     "ZhengPeng7/BiRefNet", trust_remote_code=True
 )
-birefnet.to("cpu")  # GPU -> CPU로 변경
+# GPU 환경에서만 모델을 GPU로 이동
 
 transform_image = transforms.Compose(
     [
@@ -23,19 +20,21 @@ transform_image = transforms.Compose(
     ]
 )
 
+@spaces.GPU
 def fn(image):
+    # GPU 할당 시 모델을 CUDA로 이동
+    birefnet.to("cuda")
     im = load_img(image, output_type="pil")
     im = im.convert("RGB")
     origin = im.copy()
     processed_image = process(im)
+    # 작업 완료 후 모델을 CPU로 이동
+    birefnet.to("cpu")
     return (processed_image, origin)
 
-# @spaces.GPU 데코레이터 제거
-# CPU 환경에서 동작하도록 설정
-
 def process(image):
     image_size = image.size
-    input_images = transform_image(image).unsqueeze(0).to("cpu")  # GPU -> CPU로 변경
+    input_images = transform_image(image).unsqueeze(0).to("cuda")
     # Prediction
     with torch.no_grad():
         preds = birefnet(input_images)[-1].sigmoid().cpu()
@@ -45,12 +44,15 @@ def process(image):
     image.putalpha(mask)
     return image
 
+@spaces.GPU
 def process_file(f):
+    birefnet.to("cuda")
     name_path = f.rsplit(".", 1)[0] + ".png"
     im = load_img(f, output_type="pil")
     im = im.convert("RGB")
     transparent = process(im)
     transparent.save(name_path)
+    birefnet.to("cpu")
     return name_path
 
 slider1 = ImageSlider(label="Processed Image", type="pil")
@@ -60,7 +62,7 @@ image_file_upload = gr.Image(label="Upload an image", type="filepath")
 url_input = gr.Textbox(label="Paste an image URL")
 output_file = gr.File(label="Output PNG File")
 
-# Example images
+# 예시 이미지
 chameleon = load_img("butterfly.jpg", output_type="pil")
 url_example = "https://hips.hearstapps.com/hmg-prod/images/gettyimages-1229892983-square.jpg"