Clean up dead code and add startup model loading

- Remove unused `new` parameter from preprocess_sketch, preprocessing_inputs, postprocess
- Simplify load_model globals check (model is always defined)
- Load first available model at startup

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

app.py

@@ -11,7 +11,7 @@ links = {
     "v1.5": "https://arxiv.org/abs/2502.19937v1",
     "v2": "https://arxiv.org/abs/2504.06895",
     "xl": "https://arxiv.org/abs/2601.04883",
-    "weights": "https://huggingface.co/tellurion/colorizer/tree/main",
+    "weights": "https://huggingface.co/tellurion/ColorizeDiffusionXL/tree/main",
     "github": "https://github.com/tellurion-kanata/colorizeDiffusion",
 }
 
@@ -53,6 +53,9 @@ def init_interface(opt, *args, **kwargs) -> None:
                     <a href="{links['v2']}" target="_blank">
                         <img src="https://img.shields.io/badge/arXiv-2504.06895 (v2)-B31B1B?style=flat&logo=arXiv" alt="arXiv v2 Paper">
                     </a>
+                    <a href="{links['xl']}" target="_blank">
+                        <img src="https://img.shields.io/badge/CVPR 2026-XL-0CA4A5?style=flat&logo=Semantic%20Web" alt="CVPR 2026">
+                    </a>
                     <a href="{links['weights']}" target="_blank">
                         <img src="https://img.shields.io/badge/Hugging%20Face-Model%20Weights-FF9D00?style=flat&logo=Hugging%20Face" alt="Model Weights">
                     </a>
@@ -219,4 +222,7 @@ if __name__ == '__main__':
     opt = app_options()
     switch_extractor(default_line_extractor)
     switch_mask_extractor(default_mask_extractor)
+    available_models = get_available_models()
+    if available_models:
+        load_model(available_models[0])
     init_interface(opt)

backend/appfunc.py

@@ -26,7 +26,7 @@ smask_extractor = create_model("ISNet-sketch").cpu()
 MAXM_INT32 = 429496729
 
 # HuggingFace model repository
-HF_REPO_ID = "tellurion/sdxl"
+HF_REPO_ID = "tellurion/ColorizeDiffusionXL"
 MODEL_CACHE_DIR = "models"
 
 model_types = ["sdxl", "xlv2"]
@@ -115,8 +115,8 @@ def load_model(ckpt_name):
                 new_model_type = key
                 break
 
-        if model_type != new_model_type or not "model" in globals():
-            if "model" in globals() and exists(model):
+        if model_type != new_model_type:
+            if exists(model):
                 del model
             config_path = osp.join(config_root, f"{new_model_type}.yaml")
             new_model = instantiate_from_config(OmegaConf.load(config_path).model).cpu().eval()

backend/functool.py

@@ -67,7 +67,7 @@ def lineart_standard(x: Image.Image):
     result = to_tensor(intensity.clip(0, 255).astype(np.uint8))
     return result
 
-def preprocess_sketch(sketch, resolution, preprocess="none", extractor=None, new=False):
+def preprocess_sketch(sketch, resolution, preprocess="none", extractor=None):
     w, h = sketch.size
     th, tw = resolution
     r = min(th/h, tw/w)
@@ -82,11 +82,7 @@ def preprocess_sketch(sketch, resolution, preprocess="none", extractor=None, new
         sketch = extractor.proceed(resize((768, 768))(sketch)).repeat(1, 3, 1, 1)
 
     sketch, original_shape = pad_image(resize((int(h*r), int(w*r)))(sketch), th, tw)
-    if new:
-        sketch = ((sketch + 1) / 2.).clamp(0, 1)
-        white_sketch = 1 - sketch
-    else:
-        white_sketch = -sketch
+    white_sketch = -sketch
     return sketch, original_shape, white_sketch
 
 
@@ -100,14 +96,13 @@ def preprocessing_inputs(
         resolution: tuple[int, int],
         extractor: nn.Module,
         pad_scale: float = 1.,
-        new = False
 ):
     extractor = extractor.cuda()
     h, w = resolution
     if exists(sketch):
-        sketch, original_shape, white_sketch = preprocess_sketch(sketch, resolution, preprocess, extractor, new)
+        sketch, original_shape, white_sketch = preprocess_sketch(sketch, resolution, preprocess, extractor)
     else:
-        sketch = torch.zeros([1, 3, h, w], device="cuda") if new else -torch.ones([1, 3, h, w], device="cuda")
+        sketch = -torch.ones([1, 3, h, w], device="cuda")
         white_sketch = None
         original_shape = (0, 0, h, w)
 
@@ -134,9 +129,9 @@ def preprocessing_inputs(
     return sketch, reference, background, original_shape, inject_xr, inject_xs, white_sketch
 
 def postprocess(results, sketch, reference, background, crop, original_shape,
-                mask_guided, smask, rmask, bgmask, mask_ts, mask_ss, new=False):
+                mask_guided, smask, rmask, bgmask, mask_ts, mask_ss):
     results = to_numpy(results)
-    sketch = to_numpy(sketch, not new)[0]
+    sketch = to_numpy(sketch, True)[0]
 
     results_list = []
     for result in results: