nan
ab282e4fdf
- Introduced a new proposal for depth cutout symmetry, allowing for the reuse of depth replacement and geometry operations. - Added requirements for maintaining default thickness values for cutout nodes and ensuring proper initialization during object creation. - Enhanced symmetry node to handle existing geometry, including alignment, mirroring, and boundary filling. - Implemented fill smoothing to control the geometry of generated walls while preserving original surfaces. - Created tests to validate the functionality of the new symmetry features against baseline geometry. - Updated existing assets and node groups to support the new symmetry capabilities without introducing additional dependencies.
255 lines
11 KiB
Python
255 lines
11 KiB
Python
"""Contracts for smooth depth volume, editable presets and normal masks."""
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import bpy
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import numpy as np
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import pytest
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from tools.nodes.groups.image_depth_cutout import build_volume_fields
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from anyimage.common.object import modifier_input_identifier, set_modifier_input
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def store_test_fields(group, geometry, fields):
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"""Expose evaluated fields only in the test output mesh."""
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for name, field in fields.items():
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store = group.nodes.new("GeometryNodeStoreNamedAttribute")
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store.domain = "POINT"
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store.data_type = "FLOAT_VECTOR" if field.type == "VECTOR" else "FLOAT"
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store.inputs["Name"].default_value = name
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group.links.new(geometry, store.inputs["Geometry"])
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group.links.new(field, store.inputs["Value"])
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geometry = store.outputs["Geometry"]
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return geometry
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@pytest.mark.parametrize("mode", [0, 1])
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def test_normal_smooth_changes_thickness_direction_without_moving_zero_thickness(mode):
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from tests.support.depth_surface import surface, evaluated
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obj, set_value = surface(step=1, resolution=10)
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xy = np.array([v.co[:2] for v in obj.data.vertices])
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profile = .3 * np.sin(np.pi * xy[:, 0] / 2) * np.sin(np.pi * xy[:, 1])
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profile[abs(profile) < 1e-7] = 0
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obj.data.attributes.new("o_balloon", "FLOAT", "POINT").data.foreach_set("value", profile)
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set_value("Mode", mode)
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set_value("Front Inflation", .2)
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modifier = obj.modifiers[0]
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thickness = modifier_input_identifier(modifier.node_group, "Thickness", subtype="DISTANCE" if mode else "NONE")
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def result(amount, smoothing):
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set_modifier_input(modifier, thickness, amount)
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set_value("Normal Smooth", smoothing)
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return evaluated(obj)
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raw, faces = result(0, 16)
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smooth, smooth_faces = result(0, 512)
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np.testing.assert_array_equal(raw, smooth)
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assert faces == smooth_faces
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raw, faces = result(1, 16)
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smooth, smooth_faces = result(1, 512)
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assert faces == smooth_faces
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assert np.isfinite(smooth).all()
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assert np.max(np.abs(raw - smooth)) > 1e-5
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def test_thin_shell_normal_smoothing_is_independent_of_thickness_and_reference():
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from tests.support.depth_surface import surface, evaluated
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obj, set_value = surface(step=0, resolution=12)
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image = bpy.data.images['Camera']
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pixels = np.array(image.pixels[:], dtype=np.float32).reshape(32, 64, 4)
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pixels[..., 2] = 1 + .15 * np.sin(pixels[..., 0] * 6) * np.cos(pixels[..., 1] * 5)
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image.pixels.foreach_set(pixels.ravel())
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image.update()
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set_value('Reference Depth', 10.)
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set_value('Thickness', 0.)
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front, _ = evaluated(obj)
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def offsets(thickness, smoothing, reference=10.):
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set_value('Thickness', thickness)
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set_value('Normal Smooth', smoothing)
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set_value('Reference Depth', reference)
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points, faces = evaluated(obj)
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adjusted_front = front + (0, 0, reference - 10.)
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from scipy.spatial import cKDTree
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distances, indices = cKDTree(adjusted_front).query(points)
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np.testing.assert_allclose(np.sort(distances)[:len(front)], 0, atol=2e-6)
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rear = distances > thickness * .5
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assert rear.sum() == len(front)
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order = np.argsort(indices[rear])
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return ((points[rear] - adjusted_front[indices[rear]]) / thickness)[order], faces
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raw, _ = offsets(.02, 16)
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smooth, faces = offsets(.02, 512)
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assert np.max(np.linalg.norm(raw - smooth, axis=1)) > .05
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thinner, thinner_faces = offsets(.01, 512)
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distant, _ = offsets(.02, 512, 20.)
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np.testing.assert_allclose(thinner, smooth, atol=2e-4)
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np.testing.assert_allclose(distant, smooth, atol=2e-4)
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assert thinner_faces == faces
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def set_test_structure(monkeypatch, value):
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"""Control structural amplitude without depending on storage nodes."""
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from tools.nodes.groups import image_depth_cutout
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build = image_depth_cutout.build_front_fields
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def fields(group, volume, normal, normal_weight):
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result = build(group, volume, normal, normal_weight)
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structure = group.nodes.new("ShaderNodeValue")
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structure.outputs[0].default_value = value
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result["structure"] = structure.outputs[0]
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return result
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monkeypatch.setattr(image_depth_cutout, "build_front_fields", fields)
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def test_shell_thickness_extends_behind_the_tilted_front():
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from scipy.spatial import cKDTree
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from tests.support.depth_surface import surface, evaluated, assert_closed
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obj, set_value = surface(step=0, resolution=4)
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image = bpy.data.images["Camera"]
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pixels = np.array(image.pixels[:], dtype=np.float32).reshape(32, 64, 4)
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pixels[..., 2] = 1 + 0.4 * pixels[..., 0]
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image.pixels.foreach_set(pixels.ravel())
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image.update()
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obj.update_tag(refresh={"DATA"})
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bpy.context.view_layer.update()
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front, _ = evaluated(obj)
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set_value("Thickness", 0.2)
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set_value("Front Inflation", 0.5)
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points, faces = evaluated(obj)
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expected = front - 0.2 * np.array((0.4, 0, 1)) / np.sqrt(1.16)
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assert cKDTree(points).query(expected)[0].max() < 1e-5
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assert cKDTree(points).query(front)[0].max() < 1e-5
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assert_closed(faces)
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def test_balloon_shell_converges_to_front_with_thickness():
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from scipy.spatial import cKDTree
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from tests.support.depth_surface import surface, evaluated, assert_closed
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obj, set_value = surface(step=1, resolution=10)
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xy = np.array([v.co[:2] for v in obj.data.vertices])
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profile = 0.3 * np.sin(np.pi * xy[:, 0] / 2) * np.sin(np.pi * xy[:, 1])
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profile[abs(profile) < 1e-7] = 0
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obj.data.attributes.new("o_balloon", "FLOAT", "POINT").data.foreach_set("value", profile)
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set_value("Mode", 0)
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modifier = obj.modifiers[0]
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thickness = modifier_input_identifier(modifier.node_group, "Thickness", subtype="NONE")
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def amount(value):
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set_modifier_input(modifier, thickness, value)
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obj.update_tag(refresh={"DATA"})
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bpy.context.view_layer.update()
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return evaluated(obj)
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front, _ = amount(0)
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tree = cKDTree(front)
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gaps = []
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for value in (0.01, 0.001, 0.0001):
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points, faces = amount(value)
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assert_closed(faces)
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gaps.append(tree.query(points)[0].max())
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np.testing.assert_allclose(np.array(gaps[1:]) / gaps[:-1], 0.1, rtol=0.02)
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def test_smooth_back_rejects_front_noise_and_preserves_center_depth():
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bpy.ops.wm.read_factory_settings(use_empty=True)
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n = 41
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points = np.array([(x, y) for y in np.linspace(-1, 1, n) for x in np.linspace(-1, 1, n)])
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profile = np.sqrt(np.maximum(0, np.cos(points[:, 0]*np.pi/2)*np.cos(points[:, 1]*np.pi/2))) * 0.6
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boundary = np.max(abs(points), axis=1) > 0.999
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profile[boundary] = 0
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center = 0.3*points[:, 0] + 0.6*points[:, 1]
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noise = 0.08*np.sin(points[:, 0]*23)*np.sin(points[:, 1]*19)
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noise[boundary] = 0
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faces = [(y*n+x, y*n+x+1, (y+1)*n+x+1) for y in range(n-1) for x in range(n-1)]
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faces += [(y*n+x, (y+1)*n+x+1, (y+1)*n+x) for y in range(n-1) for x in range(n-1)]
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mesh = bpy.data.meshes.new("Noisy front")
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mesh.from_pydata(np.column_stack((points, center + profile + noise)), [], faces)
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mesh.attributes.new("o_balloon", "FLOAT", "POINT").data.foreach_set("value", profile.astype(np.float32))
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obj = bpy.data.objects.new("Noisy front", mesh)
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bpy.context.collection.objects.link(obj)
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group = bpy.data.node_groups.new("Volume field test", "GeometryNodeTree")
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for name, kind in (("Geometry", "NodeSocketGeometry"), ("Thickness", "NodeSocketFloat")):
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socket = group.interface.new_socket(name=name, in_out="INPUT", socket_type=kind)
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if name == "Thickness":
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socket.default_value = 1
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group.interface.new_socket(name="Geometry", in_out="OUTPUT", socket_type="NodeSocketGeometry")
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source = group.nodes.new("NodeGroupInput")
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fields = build_volume_fields(group)
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result = store_test_fields(group, source.outputs["Geometry"], {"thickness": fields["thickness"]})
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group.links.new(result, group.nodes.new("NodeGroupOutput").inputs["Geometry"])
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obj.modifiers.new("Volume", "NODES").node_group = group
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bpy.context.view_layer.update()
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evaluated = obj.evaluated_get(bpy.context.evaluated_depsgraph_get())
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result = evaluated.to_mesh()
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try:
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thickness = np.array([item.value for item in result.attributes["thickness"].data])
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rear = center + profile + noise - thickness
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error = rear - (center - profile)
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assert max(abs(error)) < 1e-5
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assert np.sqrt(np.mean(error**2)) < np.sqrt(np.mean(noise**2))*0.01
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assert max(abs(thickness[boundary])) == 0
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finally:
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evaluated.to_mesh_clear()
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def test_depth_cutout_normal_map_only_affects_front_faces():
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from tests.support.depth_surface import surface
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obj, set_value = surface()
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set_value("Thickness", 0.3)
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bpy.context.view_layer.update()
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evaluated = obj.evaluated_get(bpy.context.evaluated_depsgraph_get())
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mesh = evaluated.to_mesh()
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try:
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attribute = mesh.attributes["o_normal_reduction"]
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assert attribute.domain == "FACE"
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weights = [1.0 - item.value for item in attribute.data]
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assert weights.count(1) == len(obj.data.polygons)
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assert weights.count(0) == len(mesh.polygons) - len(obj.data.polygons)
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finally:
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evaluated.to_mesh_clear()
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@pytest.mark.parametrize("thickness,inflation", [
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(0.0, 1.0), (0.02, 0.0), (0.02, 0.0001),
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(0.02, 0.5), (0.1, 0.5), (0.1, 1.0),
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])
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def test_shell_ignores_front_inflation(thickness, inflation):
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from tests.support.depth_surface import surface, evaluated, assert_closed
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obj, set_value = surface(step=0, resolution=10)
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xy = np.array([v.co[:2] for v in obj.data.vertices])
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profile = 0.3 * np.sin(np.pi * xy[:, 0] / 2) * np.sin(np.pi * xy[:, 1])
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profile[abs(profile) < 1e-7] = 0
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obj.data.attributes.new("o_balloon", "FLOAT", "POINT").data.foreach_set("value", profile)
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set_value("Thickness", thickness)
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set_value("Front Inflation", 0.0)
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baseline, faces = evaluated(obj)
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set_value("Front Inflation", inflation)
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inflated, inflated_faces = evaluated(obj)
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assert faces == inflated_faces
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np.testing.assert_array_equal(inflated, baseline)
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if thickness:
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assert_closed(inflated_faces)
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def test_balloon_suppression_is_stronger_without_a_startup_threshold(monkeypatch):
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from tests.support.depth_surface import surface, evaluated
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set_test_structure(monkeypatch, 1)
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obj, set_value = surface(step=0, resolution=10)
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xy = np.array([v.co[:2] for v in obj.data.vertices])
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profile = 0.3 * np.sin(np.pi * xy[:, 0] / 2) * np.sin(np.pi * xy[:, 1])
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profile[abs(profile) < 1e-7] = 0
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obj.data.attributes.new("o_balloon", "FLOAT", "POINT").data.foreach_set("value", profile)
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group = obj.modifiers[0].node_group
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set_value("Mode", 0)
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thickness_id = modifier_input_identifier(group, "Thickness", subtype="NONE")
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previous = 0
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for thickness in (0.001, 0.01, 0.1, 0.5, 1):
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set_modifier_input(obj.modifiers[0], thickness_id, thickness)
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set_value("Front Inflation", 0)
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baseline, _ = evaluated(obj)
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set_value("Front Inflation", 1)
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inflated, _ = evaluated(obj)
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growth = np.linalg.norm(inflated - baseline, axis=1).max() / profile.max()
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assert growth > previous
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previous = growth
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assert growth == pytest.approx(0.323, abs=0.001)
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