Upload app.py

app.py

@@ -42,6 +42,7 @@ enhancer = RealESRGANer(
     scale=4, model_path=weights_path, model=esrgan_model,
     tile=512, tile_pad=10, pre_pad=0, half=True,
 )
+enhancer.device = torch.device("cuda")
 print("Real-ESRGAN ready.")
 """
 # LOAD NAFNET (Deblurring)
@@ -66,8 +67,8 @@ print("Loading SD2 Inpainting...")
 inpaint = StableDiffusionInpaintPipeline.from_pretrained(
     "sd2-community/stable-diffusion-2-inpainting",
     torch_dtype=torch.float16,
-)
-# No .to("cuda") — ZeroGPU rule: only move inside @spaces.GPU functions
+).to("cuda")
+
 print("SD2 Inpainting ready.")
 
 
@@ -92,8 +93,7 @@ blip_processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning
 blip_model = BlipForConditionalGeneration.from_pretrained(
     "Salesforce/blip-image-captioning-base",
     torch_dtype=torch.float16,
-    use_safetensors= True
-)
+).to("cuda")
 print("All models loaded.")
 
 
@@ -114,7 +114,6 @@ def is_greyscale(image):
 
 
 def get_caption(image):
-    blip_model.to("cuda")
     inputs  = blip_processor(
         image.convert("RGB"), return_tensors="pt"
     ).to("cuda", torch.float16)
@@ -156,8 +155,6 @@ def enhance_image(image, scale_factor): #deblur
             print(f"deblur failed: {e}, skipping deblur")
    """ 
     #Enhance
-    enhancer.device = torch.device("cuda")
-    enhancer.half   = True
 
     image_array = np.array(image)
     image_array = image_array[:, :, :3]
@@ -359,9 +356,6 @@ def outpaint_image(image, direction, extend_percent, custom_prompt, progress=gr.
         raise gr.Error("Please upload an image first.")
     
     custom_prompt = custom_prompt or ""
-    inpaint.to("cuda")
-    blip_model.to("cuda")
-    # Move to GPU inside @spaces.GPU — ZeroGPU has allocated GPU here
 
     max_side = 512
     ratio    = min(max_side / image.width, max_side / image.height)