feat: Implement upscale functionality with ONNX models

- Added upscale operator to handle image upscaling by 4x using AI models.
- Introduced new jobs for upscale processing in the server, including debug and standard upscale jobs.
- Created a new ONNX model handler for upscale operations, supporting tiled inference and resource management.
- Updated tests to cover new upscale functionality, including input validation and output verification.
- Added documentation for the upscale feature, detailing usage and model options.

src/anyimage/preferences.py

@@ -1,16 +1,46 @@
+from pathlib import Path
+
 import bpy
 
-from .runtime import DEFAULT_STORAGE_ROOT, runtime
-from .properties import (
-    ai_setup_label,
-    ai_status,
-    device_enum_items,
-    model_catalog,
+from .server.model_catalog import DEFAULT_UPSCALE_MODEL_KEY, UPSCALE_MODELS
+
+
+
+ADDON_PACKAGE = __package__
+DEFAULT_STORAGE_ROOT = Path.home() / ".anyimage"
+DEFAULT_UPSCALE_MAX_OUTPUT_SIZE = 4096
+MAX_UPSCALE_OUTPUT_SIZE = 8192
+UPSCALE_MODEL_ITEMS = tuple(
+    (model.key, model.label, model.description, index)
+    for index, model in enumerate(UPSCALE_MODELS.values())
 )
 
 
+def addon_preferences(context=None):
+    preference_context = (
+        context
+        if getattr(context, "preferences", None) is not None
+        else bpy.context
+    )
+    addon = preference_context.preferences.addons.get(ADDON_PACKAGE)
+    return getattr(addon, "preferences", None)
+
+
+def configured_storage_root():
+    configured = getattr(addon_preferences(), "storage_root", "")
+    if configured:
+        return Path(bpy.path.abspath(configured))
+    return DEFAULT_STORAGE_ROOT
+
+
+def device_items(owner, context):
+    from .properties import device_enum_items
+
+    return device_enum_items(owner, context)
+
+
 class AnyImagePreferences(bpy.types.AddonPreferences):
-    bl_idname = __package__
+    bl_idname = ADDON_PACKAGE
 
     storage_root: bpy.props.StringProperty(
         name="Storage Root",
@@ -27,14 +57,37 @@ class AnyImagePreferences(bpy.types.AddonPreferences):
             "Inference device used by production tasks; only devices supported "
             "on this machine are listed"
         ),
-        items=device_enum_items,
+        items=device_items,
         default=0,
     )
+    upscale_model: bpy.props.EnumProperty(
+        name="Default Upscale Model",
+        description="Model used when starting a new Upscale operation",
+        items=UPSCALE_MODEL_ITEMS,
+        default=DEFAULT_UPSCALE_MODEL_KEY,
+    )
+    upscale_max_output_size: bpy.props.IntProperty(
+        name="Maximum Upscale Size",
+        description=(
+            "Maximum output long edge; larger inputs are resized before 4x "
+            "upscaling to keep memory use bounded"
+        ),
+        default=DEFAULT_UPSCALE_MAX_OUTPUT_SIZE,
+        min=1024,
+        max=MAX_UPSCALE_OUTPUT_SIZE,
+        step=256,
+        subtype="PIXEL",
+    )
 
     def draw(self, _context):
+        from .properties import ai_setup_label, ai_status, model_catalog
+        from .runtime import runtime
+
         layout = self.layout
         layout.prop(self, "storage_root")
         layout.prop(self, "device")
+        layout.prop(self, "upscale_model")
+        layout.prop(self, "upscale_max_output_size")
         layout.separator()
         status = ai_status()
         layout.label(text=f"Environment: {runtime.environment_directory()}")
@@ -74,6 +127,8 @@ class AnyImagePreferences(bpy.types.AddonPreferences):
         )
 
     def _draw_model(self, layout, model):
+        from .runtime import runtime
+
         row = layout.row(align=True)
         row.label(text=model["label"])
         if model.get("ready"):