feat(cutout_tool): Implement cutout region to shape functionality

- Added interaction helpers for cutout region validation and shape menu interaction.
- Created main operator for converting image regions into cutout shapes, including AI artifact generation.
- Introduced object creation logic for cutout shapes, handling depth and normal textures.
- Defined cutout shape identifiers and node groups for various shape types.
- Implemented depth texture writing and prediction artifact generation for MoGe-2.
- Developed server jobs for generating cutout artifacts, depth planes, and refining image regions.
- Added region refinement logic to enhance gesture masks using BEN2.

src/anyimage/server/jobs/cutout.py

@@ -1,21 +1,21 @@
-"""Generate optional AI data for one Blender-rasterized Cutout Region."""
+"""Generate optional AI files for one Blender-rasterized Cutout Region."""
 
 import json
 from pathlib import Path
 
-from ..geometry.generate_depth import generate_depth
-from ..region import generate_selection
+from ..geometry.prediction_artifacts import generate_moge2_artifacts
+from ..region import refine_region
 
 
 def run(context, parameters):
     context.progress(0.05, "Preparing Cutout Region")
     context.directory.mkdir(parents=True, exist_ok=True)
     input_path = Path(parameters["input"])
-    region_path = input_path
+    region_image_path = input_path
     result = {}
     if parameters.get("refine_region"):
-        context.progress(0.2, "Generating refined Region")
-        region_path, bounds = generate_selection(
+        context.progress(0.2, "Refining Region")
+        region_image_path, bounds = refine_region(
             context,
             input_path,
             parameters["refine_model"],
@@ -28,24 +28,21 @@ def run(context, parameters):
             encoding="utf-8",
         )
         result.update(
-            region=region_path.name,
+            region_image=region_image_path.name,
             region_bounds=bounds_path.name,
         )
 
-    output_depth = bool(parameters.get("output_depth"))
+    depth_mode = str(parameters.get("depth_mode", "NONE"))
     normal_mode = str(parameters.get("normal_mode", "NONE"))
-    if output_depth or normal_mode != "NONE":
-        archive_path, normal_path = generate_depth(
+    if depth_mode != "NONE" or normal_mode != "NONE":
+        artifacts = generate_moge2_artifacts(
             context,
             parameters,
-            region_path,
-            output_depth=output_depth,
+            region_image_path,
+            depth_mode=depth_mode,
             normal_mode=normal_mode,
         )
-        if archive_path is not None:
-            result["image_geometry"] = archive_path.name
-        if normal_path is not None:
-            result["normal"] = normal_path.name
+        result.update({key: path.name for key, path in artifacts.items()})
     context.check_cancelled()
-    context.progress(1.0, "Cutout Region data is ready")
+    context.progress(1.0, "Cutout artifacts are ready")
     return result

src/anyimage/server/jobs/depth_plane.py

@@ -1,6 +1,6 @@
-"""Generate depth data and preserve color for one complete image."""
+"""Generate model-space Z Depth and preserve color for one complete image."""
 
-from ..geometry.generate_depth import generate_depth
+from ..geometry.prediction_artifacts import generate_moge2_artifacts
 from ..media import copy_color_images, input_frames
 
 
@@ -11,12 +11,12 @@ def run(context, parameters):
         if len(images) != 1:
             raise ValueError("Depth Plane currently supports one image")
         copy_color_images(images, context.directory)
-        archive_path, _normal_path = generate_depth(
+        artifacts = generate_moge2_artifacts(
             context,
             parameters,
             images[0],
-            output_depth=True,
+            depth_mode="Z",
         )
     context.check_cancelled()
     context.progress(1.0, "Depth Plane data is ready")
-    return {"image_geometry": archive_path.name}
+    return {key: path.name for key, path in artifacts.items()}

src/anyimage/server/jobs/refine_image_region.py

@@ -1,18 +1,18 @@
 import json
 import time
 
-from ..region import generate_selection
+from ..region import refine_region
 
 
 def run(context, parameters):
     """Refine a gesture mask with BEN2 and return its source-image bounds."""
     started = time.perf_counter()
-    context.progress(0.05, "Preparing image selection")
+    context.progress(0.05, "Preparing image Region")
     context.check_cancelled()
     output_directory = context.directory
     output_directory.mkdir(parents=True, exist_ok=True)
     context.progress(0.2, f"Loading BEN2 for {parameters['device'].upper()}")
-    output_path, bounds = generate_selection(
+    output_path, bounds = refine_region(
         context,
         parameters["input"],
         parameters["model"],
@@ -22,6 +22,6 @@ def run(context, parameters):
     bounds_path = output_directory / "bounds.json"
     bounds_path.write_text(json.dumps(bounds, separators=(",", ":")), encoding="utf-8")
     elapsed_ms = (time.perf_counter() - started) * 1000.0
-    message = f"Image selection refined in {elapsed_ms:.0f} ms"
+    message = f"Image Region refined in {elapsed_ms:.0f} ms"
     context.progress(1.0, message)
-    return {"image": output_path.name, "bounds": bounds_path.name}
+    return {"region_image": output_path.name, "region_bounds": bounds_path.name}