nan
938d95db0f
- Implemented a preview tool for rectifying images with interactive aspect controls in `preview.py`. - Added tests for depth metadata loading to ensure consistent schema usage in `test_depth_metadata.py`. - Developed comprehensive tests for cutout calibration processes in `test_cutout_calibration.py`, including stability checks and depth calibration. - Created tests for frame compositing operations in `test_frame_compositing.py`, ensuring correct handling of depth and transparency. - Introduced material slot inheritance functionality in `material_slots.py` to manage geometry material assignments. - Built shared shader nodes for material processing in `shader.py`, including roughness and bump mapping setups.
188 lines
8.3 KiB
Python
188 lines
8.3 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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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, rim, normal, normal_weight):
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result = build(group, rim, 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_scale"]
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assert attribute.domain == "FACE"
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weights = [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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