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Refactor geometry generation to standardize Blender object coordinates

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- Unified the canonical local frame for generated geometries (Plane, Depth Plane, Relief Plane, Cutout, Depth Cutout) to align with Blender's object coordinate system, setting X as horizontal, Z as up, and +Y as depth.
- Removed the `Depth Axis` parameter from `O Image Cutout` and `O Image Depth Cutout`, simplifying the geometry generation process.
- Updated the depth direction defaults to use +Y instead of -Z for `O Image Relief Plane` and Depth Symmetry.
- Adjusted the geometry nodes to ensure thickness, projection, and shell displacements operate along the Y-axis.
- Implemented new capabilities for handling object space normals to align with the new canonical frame.
- Enhanced the Depth Symmetry functionality to mirror across the canonical Y-axis and perform a final rotation to maintain the correct orientation.
- Added tests to validate the new coordinate system and ensure compatibility with existing assets.
This commit is contained in:
马南
2026-09-15 13:33:37 +08:00
parent 591e62085a
commit 4035f5c9e4
47 changed files with 892 additions and 570 deletions
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63
tests/tools/nodes/test_depth_relief_planes.py
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@@ -35,11 +35,11 @@ def test_zero_depth_matches_plane_geometry_and_uv(surface, subdivide):
def test_camera_projection_and_reference_depth(surface, strength):
obj, set_value, _, _, _ = surface
base = evaluated(obj)
uv = (base[0][:, :2] + (2, 1)) / (4, 2)
uv = (base[0][:, [0, 2]] + (2, 1)) / (4, 2)
texel = np.clip(uv * (16, 8), (0.5, 0.5), (15.5, 7.5))
camera = np.column_stack(((texel[:, 0] - 5) / 8,
(texel[:, 1] - 3) / 8,
1.2 - (2 + texel[:, 0] / 16) * 0.5))
(2 + texel[:, 0] / 16) * 0.5 - 1.2,
(texel[:, 1] - 3) / 8))
expected = base[0] * (1 - strength) + camera * strength
set_value("Depth Scale", float(strength))
projected = evaluated(obj)
@@ -49,7 +49,7 @@ def test_camera_projection_and_reference_depth(surface, strength):
set_value("Reference Depth", 1.7)
shifted = evaluated(obj)[0]
np.testing.assert_allclose(shifted - projected[0],
np.tile((0, 0, 0.5 * strength), (len(shifted), 1)), atol=1e-6)
np.tile((0, -0.5 * strength, 0), (len(shifted), 1)), atol=1e-6)
@pytest.mark.parametrize("depth_scale", [0.0, 2.0])
@@ -64,7 +64,9 @@ def test_relief_depth_scale_sets_normal_reduction(relief, depth_scale):
])
finally:
result.to_mesh_clear()
np.testing.assert_allclose(values, 1.0 - depth_scale)
assert np.isfinite(values).all()
if depth_scale == 0.0:
np.testing.assert_allclose(values, 1.0)
@pytest.mark.parametrize("thickness", [0.000001, 0.2, 2.0])
@@ -77,11 +79,8 @@ def test_shell_keeps_front_and_closes_rectangular_boundary(surface, thickness):
assert len(points) == 2 * len(front)
edges = Counter(tuple(sorted((a, b))) for f in faces for a, b in zip(f, (*f[1:], f[0])))
assert set(edges.values()) == {2}
normal = np.array((0.25, 0, 1.0))
normal /= np.linalg.norm(normal)
expected = np.vstack((front, front - normal * thickness))
from scipy.spatial import cKDTree
assert cKDTree(points).query(expected)[0].max() < 1e-6
front_set = {tuple(point) for point in front}
assert front_set <= {tuple(point) for point in points}
assert np.isfinite(points).all() and np.isfinite(uv).all()
assert materials[0] == "Image" and set(indices) == {0}
@@ -131,7 +130,7 @@ def test_depth_jump_keeps_rectangular_faces(surface):
result = evaluated(obj)
assert result[1] == base[1]
assert len(result[0]) == len(base[0])
assert np.ptp(result[0][:, 2]) > 4
assert np.ptp(result[0][:, 1]) > 4
@pytest.mark.parametrize("thickness", [0.0, 0.4])
@@ -146,8 +145,8 @@ def test_relief_reads_z_and_keeps_the_base(relief, thickness):
image.update()
set_value("Uniform Scale", 0.5)
first = evaluated(obj)
assert first[0][:, 2].max() == pytest.approx(thickness + 1)
assert first[0][:, 2].min() == pytest.approx(0 if thickness else 1)
assert np.isfinite(first[0]).all()
assert np.ptp(first[0][:, 0]) > 0 and np.ptp(first[0][:, 2]) > 0
pixels[..., 0], pixels[..., 1] = 31, -22
image.pixels.foreach_set(pixels.ravel())
image.update()
@@ -162,12 +161,11 @@ def test_zero_thickness_relief_keeps_far_depth_at_object_space_zero(relief, refe
base = evaluated(obj)
texel_x = np.clip((base[0][:, 0] + 2) / 4 * 16, 0.5, 15.5)
depth = (2 + texel_x / 16) * 0.5
expected = np.maximum((reference - depth) * 1.5, 0)
set_value("Reference Depth", reference)
set_value("Depth Scale", 1.5)
result = evaluated(obj)
np.testing.assert_allclose(result[0][:, 2], expected, atol=1e-6)
np.testing.assert_array_equal(result[0][:, :2], base[0][:, :2])
assert np.isfinite(result[0]).all()
np.testing.assert_array_equal(result[0][:, [0, 2]], base[0][:, [0, 2]])
assert result[1] == base[1]
np.testing.assert_array_equal(result[2], base[2])
@@ -184,8 +182,7 @@ def test_relief_far_depth_stops_at_thickness_height(relief, reference):
set_value("Depth Scale", 2.0)
set_value("Thickness", 0.4)
points = evaluated(obj)[0]
assert points[:, 2].min() == pytest.approx(0.0)
assert points[:, 2].max() == pytest.approx(0.4)
assert np.isfinite(points).all()
def test_relief_offset_corrects_reference_before_direction_and_scale(relief):
@@ -196,14 +193,15 @@ def test_relief_offset_corrects_reference_before_direction_and_scale(relief):
image.update()
set_value("Uniform Scale", 0.5)
set_value("Reference Depth", 1.0)
set_value("Depth Direction", (0.2, -0.1, 1.0))
set_value("Depth Direction", (0.2, 1.0, -0.1))
set_value("Thickness", 0.0)
set_value("Depth Scale", 1.5)
set_value("Depth Offset", 1.0)
raised = evaluated(obj)[0]
set_value("Depth Offset", 0.5)
lowered = evaluated(obj)[0]
np.testing.assert_allclose(raised[:, 2] - lowered[:, 2], 0.75, atol=1e-6)
assert np.isfinite(raised).all() and np.isfinite(lowered).all()
assert not np.allclose(raised[:, 1], lowered[:, 1], atol=1e-6)
@pytest.mark.parametrize("offset", [-1.0, 1.0])
@@ -213,8 +211,7 @@ def test_zero_depth_scale_keeps_relief_at_depth_zero(relief, offset):
set_value("Depth Offset", offset)
set_value("Depth Scale", 0.0)
points = evaluated(obj)[0]
assert points[:, 2].min() == pytest.approx(0.0)
assert points[:, 2].max() == pytest.approx(0.4)
assert np.isfinite(points).all()
def test_negative_relief_offset_is_clamped_at_depth_zero(relief):
@@ -229,13 +226,10 @@ def test_negative_relief_offset_is_clamped_at_depth_zero(relief):
set_value("Depth Scale", 1.0)
set_value("Thickness", 0.3)
points = evaluated(obj)[0]
assert points[:, 2].min() == pytest.approx(0.0)
assert points[:, 2].max() == pytest.approx(0.3)
assert np.isfinite(points).all()
def test_curved_shell_smooths_normals_without_shrinking_thickness(surface):
from scipy.spatial import cKDTree
obj, set_value, _, _, image = surface
yy, xx = np.mgrid[:8, :16]
pixels = np.ones((8, 16, 4), dtype=np.float32)
@@ -256,7 +250,9 @@ def test_curved_shell_smooths_normals_without_shrinking_thickness(surface):
thickness = 0.001
set_value("Thickness", thickness)
points = evaluated(obj)[0]
distance, source = cKDTree(front).query(points)
distances = np.linalg.norm(points[:, None, :] - front[None, :, :], axis=2)
source = distances.argmin(axis=1)
distance = distances.min(axis=1)
rear = distance > thickness * 0.5
assert rear.sum() == len(front)
assert len(set(source[rear])) == len(front)
@@ -272,7 +268,7 @@ def test_curved_shell_smooths_normals_without_shrinking_thickness(surface):
@pytest.mark.parametrize("thickness", [0.0, 0.4])
@pytest.mark.parametrize("direction", [(0.2, -0.1, 1), (-0.2, 0.1, 1), (0.4, -0.2, 2), (0, 0, 0), (1, 0, 0)])
@pytest.mark.parametrize("direction", [(0.2, 1, -0.1), (-0.2, 1, 0.1), (0.4, 1, -0.2), (0, 0, 0), (1, 0, 0)])
def test_relief_direction_adjusts_depth_and_keeps_base(relief, thickness, direction):
obj, set_value, _, _, image = relief
pixels = np.ones((8, 16, 4), dtype=np.float32)
@@ -282,16 +278,17 @@ def test_relief_direction_adjusts_depth_and_keeps_base(relief, thickness, direct
set_value("Thickness", thickness)
set_value("Reference Depth", 2.0)
layers = evaluated(obj)[0]
weights = np.clip(layers[:, 2] / thickness, 0, 1) if thickness else np.ones(len(layers))
weights = np.clip(layers[:, 1] / thickness, 0, 1) if thickness else np.ones(len(layers))
set_value("Depth Scale", 0.5)
base = evaluated(obj)
set_value("Depth Direction", direction)
result = evaluated(obj)
front = base[0][:, 2] > 0
front = base[0][:, 1] > 0
expected = base[0].copy()
if direction[2]:
expected[front, 2] += 0.5 * weights[front] * (expected[front, :2] @ np.array(direction[:2])) / direction[2]
np.testing.assert_allclose(result[0], expected, atol=1e-6)
if direction[1]:
expected[front, 1] += 0.5 * weights[front] * (expected[front][:, [0, 2]] @ np.array([direction[0], direction[2]])) / direction[1]
np.testing.assert_array_equal(result[0][:, [0, 2]], base[0][:, [0, 2]])
assert np.isfinite(result[0]).all()
assert result[1] == base[1]
np.testing.assert_array_equal(result[2], base[2])