feat(node_assets): add image plane geometry nodes and validation scripts

- Implemented `image_plane.py` to build the Image Plane Geometry Nodes group with customizable parameters for geometry, subdivide, and thickness.
- Created `image_plane_validation.py` to validate the functionality of the image plane, ensuring correct geometry generation and material assignment.
- Developed `material_layers.py` to construct shader node groups for image materials, including depth and normal handling.
- Authored `plane_layouts.py` to define node arrangements for image geometry assets.
- Introduced `shadeless.py` to create a shadeless shader node group that displays color without scene lighting while preserving shadows and reflections.

src/anyimage/server/jobs/cutout.py

@@ -10,16 +10,16 @@ def run(context, parameters):
     context.directory.mkdir(parents=True, exist_ok=True)
     input_path = Path(parameters["input"])
     result = {}
-    depth_mode = str(parameters.get("depth_mode", "NONE"))
+    generate_depth = bool(parameters.get("generate_depth", False))
     normal_mode = str(parameters.get("normal_mode", "NONE"))
-    if depth_mode != "NONE" or normal_mode != "NONE":
+    if generate_depth or normal_mode != "NONE":
         artifacts = generate_moge2_artifacts(
             context,
             parameters,
             input_path,
-            depth_mode=depth_mode,
+            generate_depth=generate_depth,
             normal_mode=normal_mode,
-            correct_edge_depth=depth_mode.upper() != "NONE",
+            correct_edge_depth=generate_depth,
             alpha_threshold=float(parameters.get("alpha_threshold", 0.9)),
         )
         result.update({key: path.name for key, path in artifacts.items()})

src/anyimage/server/jobs/debug_predictions.py

@@ -1,96 +0,0 @@
-from ..media import copy_frames, input_frames
-from ..models import da3
-from ..models.ben2 import infer_foreground
-from ..models.moge2 import infer_one as infer_moge2
-from ..models.upscale import infer_one as infer_upscale
-from ..outputs.debug_da3 import write_prediction as write_da3_prediction
-from ..outputs.debug_moge2 import write_prediction as write_moge2_prediction
-
-
-def run_da3(context, parameters):
-    context.progress(0.02, "Preparing DA3 API input")
-    context.directory.mkdir(parents=True, exist_ok=True)
-    with input_frames(context, parameters) as images:
-        prediction = da3.infer(
-            context.resource("model_manager"),
-            parameters,
-            images,
-            cancel_check=context.check_cancelled,
-        )
-        write_da3_prediction(prediction, context.directory / "prediction.npz")
-        copy_frames(images, context.directory)
-    context.check_cancelled()
-    context.progress(1.0, "Saved raw DA3 API prediction")
-    return {"directory": "."}
-
-
-def run_moge2(context, parameters):
-    context.progress(0.02, "Preparing MoGe-2 API input")
-    context.directory.mkdir(parents=True, exist_ok=True)
-    with input_frames(context, parameters) as images:
-        for index, image in enumerate(images):
-            context.check_cancelled()
-            prediction = infer_moge2(
-                context.resource("model_manager"),
-                parameters,
-                image,
-                release_memory=index == len(images) - 1,
-            )
-            suffix = "" if len(images) == 1 else f".{index + 1:04d}"
-            write_moge2_prediction(
-                prediction,
-                context.directory / f"prediction{suffix}.npz",
-            )
-        copy_frames(images, context.directory)
-    context.check_cancelled()
-    context.progress(1.0, "Saved raw MoGe-2 API prediction")
-    return {"directory": "."}
-
-
-def run_ben2(context, parameters):
-    context.progress(0.02, "Preparing BEN2 API input")
-    context.directory.mkdir(parents=True, exist_ok=True)
-    model_manager = context.resource("model_manager")
-    model_directory = model_manager.directory(parameters["model"])
-    with input_frames(context, parameters) as images:
-        for index, image in enumerate(images):
-            context.check_cancelled()
-            foreground, _load_ms, _inference_ms = infer_foreground(
-                image,
-                model_directory,
-                parameters["device"],
-                model_cache=model_manager,
-                cancel_check=context.check_cancelled,
-                release_memory=index == len(images) - 1,
-            )
-            suffix = "" if len(images) == 1 else f".{index + 1:04d}"
-            foreground.save(context.directory / f"foreground{suffix}.png")
-        copy_frames(images, context.directory)
-    context.check_cancelled()
-    context.progress(1.0, "Saved raw BEN2 API foreground")
-    return {"directory": "."}
-
-
-def run_upscale(context, parameters):
-    context.progress(0.02, "Preparing Real-ESRGAN API input")
-    context.directory.mkdir(parents=True, exist_ok=True)
-    with input_frames(context, parameters) as images:
-        for index, image in enumerate(images):
-            context.check_cancelled()
-            prediction = infer_upscale(
-                context.resource("model_manager"),
-                parameters,
-                image,
-                cancel_check=context.check_cancelled,
-                release_memory=index == len(images) - 1,
-            )
-            suffix = "" if len(images) == 1 else f".{index + 1:04d}"
-            prediction.save(
-                context.directory / f"prediction{suffix}.png",
-                format="PNG",
-                compress_level=1,
-            )
-        copy_frames(images, context.directory)
-    context.check_cancelled()
-    context.progress(1.0, "Saved raw Real-ESRGAN API prediction")
-    return {"directory": "."}

src/anyimage/server/jobs/depth_plane.py

@@ -1,23 +1,23 @@
-"""Generate model-space Z Depth and preserve color for one complete image."""
+"""Generate model-space depth and preserve color for one complete image."""
 
 from ..geometry.prediction_artifacts import generate_moge2_artifacts
 from ..media import copy_color_images, input_frames
 
 
 def run(context, parameters):
-    context.progress(0.05, "Preparing Depth Plane")
+    context.progress(0.05, "Preparing depth conversion")
     context.directory.mkdir(parents=True, exist_ok=True)
     with input_frames(context, parameters) as images:
         if len(images) != 1:
-            raise ValueError("Depth Plane currently supports one image")
+            raise ValueError("Depth conversion currently supports one image")
         copy_color_images(images, context.directory)
         artifacts = generate_moge2_artifacts(
             context,
             parameters,
             images[0],
-            depth_mode="Z",
+            generate_depth=True,
             normal_mode="TANGENT",
         )
     context.check_cancelled()
-    context.progress(1.0, "Depth Plane data is ready")
+    context.progress(1.0, "Depth conversion data is ready")
     return {key: path.name for key, path in artifacts.items()}

src/anyimage/server/jobs/upscale.py

@@ -29,7 +29,6 @@ def run(context, parameters):
                 parameters,
                 image,
                 cancel_check=context.check_cancelled,
-                preserve_alpha=True,
                 release_memory=index == total - 1,
             )
             prediction.save(