Update app.py

app.py

@@ -6,15 +6,7 @@ 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.
-
-birefnet = AutoModelForImageSegmentation.from_pretrained(
-    "ZhengPeng7/BiRefNet", trust_remote_code=True
-)
-birefnet.to("cpu")  # GPU -> CPU로 변경
-
+# 모델 로딩을 함수 내로 이동하여 GPU 할당 시 로드되도록 설정
 transform_image = transforms.Compose(
     [
         transforms.Resize((1024, 1024)),
@@ -23,33 +15,42 @@ transform_image = transforms.Compose(
     ]
 )
 
+@spaces.GPU
 def fn(image):
+    birefnet = AutoModelForImageSegmentation.from_pretrained(
+        "ZhengPeng7/BiRefNet", trust_remote_code=True
+    )
+    birefnet.to("cuda")
+    
     im = load_img(image, output_type="pil")
     im = im.convert("RGB")
     origin = im.copy()
-    processed_image = process(im)
+    processed_image = process(im, birefnet)
     return (processed_image, origin)
 
-# @spaces.GPU 데코레이터 제거
-# CPU 환경에서 동작하도록 설정
-
-def process(image):
+def process(image, model):
     image_size = image.size
-    input_images = transform_image(image).unsqueeze(0).to("cpu")  # GPU -> CPU로 변경
-    # Prediction
+    input_images = transform_image(image).unsqueeze(0).to("cuda")
+    # 예측
     with torch.no_grad():
-        preds = birefnet(input_images)[-1].sigmoid().cpu()
+        preds = model(input_images)[-1].sigmoid().cpu()
     pred = preds[0].squeeze()
     pred_pil = transforms.ToPILImage()(pred)
     mask = pred_pil.resize(image_size)
     image.putalpha(mask)
     return image
 
+@spaces.GPU
 def process_file(f):
+    birefnet = AutoModelForImageSegmentation.from_pretrained(
+        "ZhengPeng7/BiRefNet", trust_remote_code=True
+    )
+    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 = process(im, birefnet)
     transparent.save(name_path)
     return name_path
 
@@ -60,7 +61,7 @@ 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"