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/operators/__init__.py

@@ -4,12 +4,7 @@ from .balloon import (
     ExtractBalloon,
     AnalyzeBalloon,
 )
-from .debug import (
-    DebugBen2,
-    DebugDa3,
-    DebugMoge2,
-    DebugRealesrganGeneralX4v3,
-)
+from .debug import DebugBen2, DebugDa3, DebugMoge2, DebugUpscale
 from .image_edit import CLASSES as IMAGE_EDIT_CLASSES
 from .depth_plane import (
     ConvertToDepthPlane,
@@ -27,6 +22,7 @@ from .models import (
 )
 from .mesh_plane import ConvertToMeshPlane
 from .surface import ConvertToSurface, GenerateDa3Surface, GenerateMoge2Surface
+from .upscale import UpscaleImage
 
 
 CLASSES = (
@@ -37,7 +33,7 @@ CLASSES = (
     DebugDa3,
     DebugMoge2,
     DebugBen2,
-    DebugRealesrganGeneralX4v3,
+    DebugUpscale,
     GenerateDa3Depth,
     GenerateMoge2Depth,
     GenerateDa3Surface,
@@ -51,6 +47,7 @@ CLASSES = (
     AnalyzeBalloon,
     ActivateBalloonTool,
     RemoveImageBackground,
+    UpscaleImage,
     ConvertToMeshPlane,
     ConvertToDepthPlane,
     ConvertToSurface,