Refactor depth reference handling and cleanup

- Unified reference depth calculation to use a single implementation in common/depth.py.
- Removed server-side reference depth computation and adjusted depth.json to only include image_size and intrinsics.
- Updated depth texture handling to ignore transparent, invalid, and non-positive pixels when calculating reference depth.
- Changed reference depth calculation to use the 95th percentile of valid depth values.
- Adjusted depth direction fitting to return a flat direction when no samples are available.
- Removed cleanup threshold parameters from Cutout and related nodes, simplifying the interface.
- Updated tests to verify new reference depth logic and ensure compatibility with existing functionality.

tests/support/depth_surface.py

@@ -8,7 +8,7 @@ import numpy as np
 from tests.support.nodes import CUTOUT_BUILDERS
 
 
-def surface(*, step=6.0, size=1.0, resolution=2, wrapper=False):
+def surface(*, step=6.0, size=1.0, resolution=2):
     bpy.ops.wm.read_factory_settings(use_empty=True)
     group = CUTOUT_BUILDERS["DEPTH_SOLID"]()
     # Two columns with a complete depth jump along their common boundary.
@@ -70,8 +70,6 @@ def surface(*, step=6.0, size=1.0, resolution=2, wrapper=False):
         ("Boundary Smooth", 0),
     ):
         set_value(name, value)
-    if wrapper:
-        set_value("Cleanup Threshold", 0.0)
     return obj, set_value
 
 

tests/support/image_objects.py

@@ -60,7 +60,6 @@ def _create_cutout_shape(
         bpy.context,
         source,
         shape,
-        edge_length,
         selection_mask.values,
         selection_mask.bounds,
         base_shape,
@@ -71,13 +70,13 @@ def _create_cutout_shape(
     )
 
 
-def _depth_image(points, valid, name="Depth"):
+def _depth_image(points, alpha, name="Depth"):
     points = np.asarray(points, dtype=np.float32)
-    valid = np.asarray(valid, dtype=bool)
-    height, width = valid.shape
+    alpha = np.asarray(alpha, dtype=np.float32)
+    height, width = alpha.shape
     pixels = np.zeros((height, width, 4), dtype=np.float32)
     pixels[..., :3] = points
-    pixels[..., 3] = valid
+    pixels[..., 3] = alpha
     image = bpy.data.images.new(
         name,
         width=width,
@@ -92,11 +91,10 @@ def _depth_image(points, valid, name="Depth"):
     return image
 
 
-def _depth_metadata(intrinsics, image_size, reference_depth):
+def _depth_metadata(intrinsics, image_size):
     return {
         "intrinsics": tuple(tuple(float(value) for value in row) for row in intrinsics),
         "image_size": tuple(int(value) for value in image_size),
-        "reference_depth": float(reference_depth),
     }
 
 
@@ -115,11 +113,6 @@ def _add_cutout_modifier(obj, shape):
     modifier.node_group = group
     if shape in {"FLAT", "DEPTH_SOLID"}:
         object_data.set_modifier_input(modifier, object_data.modifier_input_identifier(group, "Mode"), 1)
-    object_data.set_modifier_input(
-        modifier,
-        object_data.modifier_input_identifier(group, "Cleanup Threshold"),
-        0.0,
-    )
     if shape == "DEPTH_SOLID":
         object_data.set_modifier_input(
             modifier,
@@ -129,73 +122,3 @@ def _add_cutout_modifier(obj, shape):
     return modifier
 
 
-def _depth_surface_step_object():
-    vertices = [(float(x), float(y), 0.0) for y in range(3) for x in range(3)]
-    faces = []
-    for y in range(2):
-        for x in range(2):
-            a = y * 3 + x
-            faces.extend(((a, a + 1, a + 4), (a, a + 4, a + 3)))
-    data = bpy.data.meshes.new("Depth Surface Step")
-    data.from_pydata(vertices, (), faces)
-    uv_layer = data.uv_layers.new(name="UVMap")
-    for loop in data.loops:
-        coordinate = data.vertices[loop.vertex_index].co
-        uv_layer.data[loop.index].uv = (coordinate.x * 0.5, coordinate.y * 0.5)
-    obj = bpy.data.objects.new("Depth Surface Step", data)
-    bpy.context.collection.objects.link(obj)
-    modifier = _add_cutout_modifier(obj, "DEPTH_SOLID")
-
-    points = np.empty((3, 3, 3), dtype=np.float32)
-    for y in range(3):
-        for x in range(3):
-            points[y, x] = (float(x), -float(y), 1.0)
-    points[0, 0, 2] = 6.0
-    depth_image = _depth_image(points, np.ones((3, 3), dtype=bool))
-    for name, value in (
-        ("Depth Image", depth_image),
-        ("Depth Scale", 1.0),
-        ("Uniform Scale", 1.0),
-        ("Reference Depth", 1.0),
-        ("Thickness", 0.0),
-    ):
-        object_data.set_modifier_input(
-            modifier,
-            object_data.modifier_input_identifier(
-                modifier.node_group, name,
-                subtype="DISTANCE" if name == "Thickness" else None,
-            ),
-            value,
-        )
-    return obj, modifier
-
-
-def _evaluated_topology(obj):
-    evaluated = obj.evaluated_get(bpy.context.evaluated_depsgraph_get())
-    result = evaluated.to_mesh()
-    try:
-        face_edges = {
-            tuple(sorted((start, end)))
-            for polygon in result.polygons
-            for start, end in zip(
-                polygon.vertices,
-                (*polygon.vertices[1:], polygon.vertices[0]),
-            )
-        }
-        mesh_edges = {
-            tuple(sorted(edge.vertices))
-            for edge in result.edges
-        }
-        face_vertices = {
-            vertex
-            for polygon in result.polygons
-            for vertex in polygon.vertices
-        }
-        return (
-            len(result.vertices),
-            len(result.polygons),
-            mesh_edges - face_edges,
-            set(range(len(result.vertices))) - face_vertices,
-        )
-    finally:
-        evaluated.to_mesh_clear()