Update app.py

app.py

@@ -6,7 +6,15 @@ from transformers import AutoModelForImageSegmentation
 import torch
 from torchvision import transforms
 
-# 모델 로딩을 함수 내로 이동하여 GPU 할당 시 로드되도록 설정
+# 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
+
 transform_image = transforms.Compose(
     [
         transforms.Resize((1024, 1024)),
@@ -15,42 +23,33 @@ 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, birefnet)
+    processed_image = process(im)
     return (processed_image, origin)
 
-def process(image, model):
+# @spaces.GPU 데코레이터 제거
+# CPU 환경에서 동작하도록 설정
+
+def process(image):
     image_size = image.size
-    input_images = transform_image(image).unsqueeze(0).to("cuda")
-    # 예측
+    input_images = transform_image(image).unsqueeze(0).to("cpu")  # GPU -> CPU로 변경
+    # Prediction
     with torch.no_grad():
-        preds = model(input_images)[-1].sigmoid().cpu()
+        preds = birefnet(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, birefnet)
+    transparent = process(im)
     transparent.save(name_path)
     return name_path
 
@@ -61,7 +60,7 @@ 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")
 
-# 예시 이미지
+# Example images
 chameleon = load_img("butterfly.jpg", output_type="pil")
 url_example = "https://hips.hearstapps.com/hmg-prod/images/gettyimages-1229892983-square.jpg"