Add image selection refinement functionality with BEN2 integration

- Implemented viewport.py for handling 3D view projections, gestures, and overlay drawing.
- Created refine_image_selection.py to manage the refinement of gesture masks and output image bounds.
- Added selection module with refine_selection.py to process and crop images based on alpha channel visibility.
- Introduced __init__.py for selection module to expose refine_selection function.

src/anyimage/server/jobs/cutout.py

@@ -1,35 +1,35 @@
-"""Generate optional AI files for one Blender-rasterized Cutout Region."""
+"""Generate optional AI files for one Blender-rasterized Cutout Selection."""
 
 import json
 from pathlib import Path
 
 from ..geometry.prediction_artifacts import generate_moge2_artifacts
-from ..region import refine_region
+from ..selection import refine_selection
 
 
 def run(context, parameters):
-    context.progress(0.05, "Preparing Cutout Region")
+    context.progress(0.05, "Preparing Cutout Selection")
     context.directory.mkdir(parents=True, exist_ok=True)
     input_path = Path(parameters["input"])
-    region_image_path = input_path
+    selection_image_path = input_path
     result = {}
-    if parameters.get("refine_region"):
-        context.progress(0.2, "Refining Region")
-        region_image_path, bounds = refine_region(
+    if parameters.get("refine_selection"):
+        context.progress(0.2, "Refining Selection")
+        selection_image_path, bounds = refine_selection(
             context,
             input_path,
             parameters["refine_model"],
             parameters["device"],
-            context.directory / "region.png",
+            context.directory / "selection.png",
         )
-        bounds_path = context.directory / "region_bounds.json"
+        bounds_path = context.directory / "selection_bounds.json"
         bounds_path.write_text(
             json.dumps(bounds, separators=(",", ":")),
             encoding="utf-8",
         )
         result.update(
-            region_image=region_image_path.name,
-            region_bounds=bounds_path.name,
+            selection_image=selection_image_path.name,
+            selection_bounds=bounds_path.name,
         )
 
     depth_mode = str(parameters.get("depth_mode", "NONE"))
@@ -38,7 +38,7 @@ def run(context, parameters):
         artifacts = generate_moge2_artifacts(
             context,
             parameters,
-            region_image_path,
+            selection_image_path,
             depth_mode=depth_mode,
             normal_mode=normal_mode,
         )

src/anyimage/server/jobs/refine_image_selection.py

@@ -1,18 +1,18 @@
 import json
 import time
 
-from ..region import refine_region
+from ..selection import refine_selection
 
 
 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 Region")
+    context.progress(0.05, "Preparing image Selection")
     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 = refine_region(
+    output_path, bounds = refine_selection(
         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 Region refined in {elapsed_ms:.0f} ms"
+    message = f"Image Selection refined in {elapsed_ms:.0f} ms"
     context.progress(1.0, message)
-    return {"region_image": output_path.name, "region_bounds": bounds_path.name}
+    return {"selection_image": output_path.name, "selection_bounds": bounds_path.name}