Add new node asset scripts for geometry and shader operations

- Implemented `build_mesh_plane.py` to create a geometry node group for mesh planes with customizable parameters.
- Created `build_shadeless.py` for a shader node group that displays color without scene lighting while preserving shadows and reflections.
- Added `validate.py` to validate the integrity of the newly created node groups and their inputs.
- Introduced `validate_cutout.py` to ensure the functionality of cutout node groups and their dependencies.
- Developed `validate_mesh_plane.py` to test the mesh plane creation and its modifier settings.

src/anyimage/server/jobs/remove_background.py

@@ -0,0 +1,65 @@
+import time
+
+from ..media import input_frames
+from ..models.ben2 import infer_foreground, infer_foreground_frames
+
+
+def run(context, parameters):
+    """Run BEN2 and write transparent foreground images into the Job directory."""
+    total_started = time.perf_counter()
+    context.progress(0.02, "Starting Environment")
+    context.check_cancelled()
+
+    output_directory = context.directory
+    output_directory.mkdir(parents=True, exist_ok=True)
+    device = parameters["device"]
+    model_manager = context.resource("model_manager")
+    model_directory = model_manager.directory(parameters["model"])
+
+    with input_frames(context, parameters) as images:
+        context.progress(0.12, f"Loading BEN2 for {device.upper()}")
+        if len(images) == 1:
+            context.progress(0.35, "Removing background")
+            foreground, load_ms, inference_ms = infer_foreground(
+                images[0],
+                model_directory,
+                device,
+                model_cache=model_manager,
+                cancel_check=context.check_cancelled,
+                preserve_input_alpha=True,
+            )
+            context.check_cancelled()
+            context.progress(0.92, "Writing transparent PNG")
+            output_path = output_directory / "image.0001.png"
+            foreground.convert("RGBA").save(
+                output_path,
+                format="PNG",
+                compress_level=1,
+            )
+            if not output_path.is_file():
+                raise RuntimeError("BEN2 did not write a foreground image")
+        else:
+            load_ms, inference_ms = infer_foreground_frames(
+                images,
+                model_directory,
+                device,
+                output_directory,
+                context.progress,
+                0.12,
+                0.7,
+                model_cache=model_manager,
+                cancel_check=context.check_cancelled,
+                output_prefix="image",
+                preserve_input_alpha=True,
+            )
+
+    context.check_cancelled()
+    total_ms = (time.perf_counter() - total_started) * 1000.0
+    frame_text = "" if len(images) == 1 else f" from {len(images)} frame(s)"
+    message = (
+        f"Background removed{frame_text} in {inference_ms:.0f} ms "
+        f"(model load {load_ms:.0f} ms, total {total_ms:.0f} ms)"
+    )
+    context.log(message)
+    context.progress(1.0, message)
+    return {"image": "."}