update

app.py

@@ -17,41 +17,44 @@ DEVICE = devicetorch.get(torch)
 def init():
     global pipe
 
-    config_file = hf_hub_download(
-        "xinsir/controlnet-union-sdxl-1.0",
-        filename="config_promax.json",
-    )
+    if pipe is None:
 
-    config = ControlNetModel_Union.load_config(config_file)
-    controlnet_model = ControlNetModel_Union.from_config(config)
-    model_file = hf_hub_download(
-        "xinsir/controlnet-union-sdxl-1.0",
-        filename="diffusion_pytorch_model_promax.safetensors",
-    )
-    state_dict = load_state_dict(model_file)
-    model, _, _, _, _ = ControlNetModel_Union._load_pretrained_model(
-        controlnet_model, state_dict, model_file, "xinsir/controlnet-union-sdxl-1.0"
-    )
-    model.to(device=DEVICE, dtype=torch.float16)
+        config_file = hf_hub_download(
+            "xinsir/controlnet-union-sdxl-1.0",
+            filename="config_promax.json",
+        )
+
+        config = ControlNetModel_Union.load_config(config_file)
+        controlnet_model = ControlNetModel_Union.from_config(config)
+        model_file = hf_hub_download(
+            "xinsir/controlnet-union-sdxl-1.0",
+            filename="diffusion_pytorch_model_promax.safetensors",
+        )
+        state_dict = load_state_dict(model_file)
+        model, _, _, _, _ = ControlNetModel_Union._load_pretrained_model(
+            controlnet_model, state_dict, model_file, "xinsir/controlnet-union-sdxl-1.0"
+        )
+        model.to(device=DEVICE, dtype=torch.float16)
 
-    vae = AutoencoderKL.from_pretrained(
-        "madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16
-    ).to(DEVICE)
+        vae = AutoencoderKL.from_pretrained(
+            "madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16
+        ).to(DEVICE)
 
-    pipe = StableDiffusionXLFillPipeline.from_pretrained(
-        "SG161222/RealVisXL_V5.0_Lightning",
-        torch_dtype=torch.float16,
-        vae=vae,
-        controlnet=model,
-        variant="fp16",
-    ).to(DEVICE)
+        pipe = StableDiffusionXLFillPipeline.from_pretrained(
+            "SG161222/RealVisXL_V5.0_Lightning",
+            torch_dtype=torch.float16,
+            vae=vae,
+            controlnet=model,
+            variant="fp16",
+        ).to(DEVICE)
 
-    pipe.scheduler = TCDScheduler.from_config(pipe.scheduler.config)
+        pipe.scheduler = TCDScheduler.from_config(pipe.scheduler.config)
 
 
 #@spaces.GPU(duration=16)
 def fill_image(prompt, image, model_selection):
     init()
+    print(f"image {image}")
     source = image["background"]
     mask = image["layers"][0]