nan
31074bd511
- Introduced tests for boundary smoothing in `test_boundary_smoothing.py`, verifying that smoothing reduces stair-step artifacts while preserving boundary integrity. - Added tests for cutout boundary behavior in `test_cutout_boundary.py`, ensuring proper handling of boundary triangles and normal blending. - Created `test_temporary_attributes.py` to check the cleanup of temporary attributes across depth modifier branches, ensuring no warnings are raised. - Implemented point culling functionality in `test_validity.py`, confirming that invalid points are removed without affecting adjacent geometry. - Developed boundary smoothing logic in `boundary_smoothing.py`, allowing for depth smoothing while maintaining edge integrity. - Added cutout boundary management in `cutout_boundary.py`, including functions for removing boundary triangles and tapering thickness profiles. - Implemented validity checks in `validity.py` to ensure proper deletion of invalid vertices and associated wire edges.
195 lines
10 KiB
Python
195 lines
10 KiB
Python
"""Verify the public panorama entry and transactional Blender result handling."""
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import json
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from types import SimpleNamespace
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from unittest.mock import Mock, patch
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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 PIL import Image
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from mathutils import Matrix
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from anyimage.operators.convert_to_panorama import operators, object as conversion
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from server.geometry.depth_texture import write_float_exr
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from anyimage.common.color_image import prepare_material_color_input, cleanup_material_color_input
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@pytest.fixture
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def source():
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bpy.ops.wm.read_factory_settings(use_empty=True)
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image = bpy.data.images.new("Current panorama", width=32, height=16, alpha=True)
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rgba = np.ones((16, 32, 4), np.float32)
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rgba[:8, :, 3] = 0
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rgba[8:12, :, 3] = 0.5
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image.pixels.foreach_set(rgba.ravel())
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obj = bpy.data.objects.new("Panorama Empty", None)
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obj.empty_display_type = "IMAGE"
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obj.data = image
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bpy.context.collection.objects.link(obj)
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obj.select_set(True)
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bpy.context.view_layer.objects.active = obj
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return obj
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def test_entry_submits_current_alpha_preferences_and_cleans_cancelled_input(source, monkeypatch):
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submitted = {}
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def submit(**parameters):
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submitted.update(parameters)
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with Image.open(parameters["input_path"]) as image:
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alpha = np.asarray(image)[..., 3]
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assert not alpha[8:].any()
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assert np.all(abs(alpha[4:8].astype(float) - 128) <= 1)
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return {"CANCELLED"}
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monkeypatch.setattr(operators, "invoke_ai_setup_if_needed", lambda _operator: None)
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monkeypatch.setattr(operators, "addon_preferences", lambda _: SimpleNamespace(geometry_model="MOGE2_VITB", geometry_resolution_level=2))
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monkeypatch.setattr(operators, "configured_geometry_model", lambda _: "MOGE2_VITB_NORMAL")
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monkeypatch.setattr(operators, "configured_max_ai_input_size", lambda _: 1024)
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monkeypatch.setattr(operators, "bpy", SimpleNamespace(ops=SimpleNamespace(anyimage=SimpleNamespace(generate_panorama=submit))))
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operator = SimpleNamespace(mesh_detail=4, report=Mock())
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assert operators.ConvertToPanorama.execute(operator, bpy.context) == {"CANCELLED"}
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assert submitted["model"] == "MOGE2_VITB_NORMAL" and submitted["resolution_level"] == 2
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assert submitted["max_input_size"] == 1024 and submitted["mesh_detail"] == 4
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assert submitted["color_path"] == submitted["input_path"]
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from pathlib import Path
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assert not Path(submitted["input_path"]).exists()
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assert bpy.data.objects.get(source.name) == source
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@pytest.mark.parametrize("image_source,size", [("MOVIE", (32, 16)), ("SEQUENCE", (32, 16)), ("FILE", (32, 32))])
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def test_invalid_input_is_rejected_before_setup(image_source, size, monkeypatch):
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setup = Mock()
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monkeypatch.setattr(operators, "invoke_ai_setup_if_needed", setup)
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obj = SimpleNamespace(data=SimpleNamespace(source=image_source, size=size))
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assert operators.ConvertToPanorama.execute(SimpleNamespace(report=Mock()), SimpleNamespace(object=obj)) == {"CANCELLED"}
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setup.assert_not_called()
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@pytest.fixture
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def artifacts(tmp_path, source):
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rgba = np.ones((16, 32, 4), np.float32)
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rgba[..., :3] = 3
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write_float_exr(rgba, tmp_path / "depth.exr")
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(tmp_path / "depth.json").write_text(json.dumps({"projection": "equirectangular", "image_size": [32, 16], "reference_distance": 3}))
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result = SimpleNamespace(directory=tmp_path, file=lambda key: tmp_path / {"depth": "depth.exr", "depth_metadata": "depth.json"}[key])
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operator = SimpleNamespace(source_object_name=source.name, source_identity=str(source.as_pointer()),
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image_identity=str(source.data.as_pointer()), mesh_detail=2,
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color_path=str(prepare_material_color_input(source.data)))
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yield result, operator
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cleanup_material_color_input(operator.color_path)
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def test_result_replaces_source_with_zero_rotation_and_shadeless_material(source, artifacts, monkeypatch):
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result, operator = artifacts
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saved = bpy.data.node_groups.new("O Image Depth Panorama", "GeometryNodeTree")
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saved["anyimage_asset_revision"] = 11
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matrix = Matrix.Translation((2, -3, 4)) @ Matrix.Rotation(0.6, 4, "Y") @ Matrix.Diagonal((2, 3, 4, 1))
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source.matrix_world = matrix
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source.empty_image_offset = (0.3, -0.8)
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undo = Mock(return_value={"FINISHED"})
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monkeypatch.setattr(conversion, "bpy", SimpleNamespace(data=bpy.data, ops=SimpleNamespace(ed=SimpleNamespace(undo_push=undo))))
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obj = conversion.create_panorama_from_result(bpy.context, result, operator)
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assert obj.modifiers[0].node_group != saved
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assert obj.modifiers[0].node_group["anyimage_asset_revision"] == 14
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assert saved in bpy.data.node_groups.values() and saved["anyimage_asset_revision"] == 11
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assert obj.name == operator.source_object_name and obj.type == "MESH"
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np.testing.assert_allclose(obj.location, matrix.translation, atol=1e-6)
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np.testing.assert_allclose(obj.scale, matrix.to_scale(), atol=1e-6)
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np.testing.assert_array_equal(obj.rotation_euler, (0, 0, 0))
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material = obj.data.materials[0]
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assert any(n.type == "GROUP" and n.node_tree.name == "O Shadeless" for n in material.node_tree.nodes)
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assert [n.node_tree.name for n in material.node_tree.nodes if n.type == "GROUP"] == ["O Shadeless"]
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texture = next(n for n in material.node_tree.nodes if n.type == "TEX_IMAGE")
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assert texture.extension == "REPEAT"
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assert bpy.context.view_layer.objects.active == obj
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assert all(image.packed_file for image in bpy.data.images if image.name.endswith(("_color.png", "_depth.exr")))
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graph = bpy.context.evaluated_depsgraph_get()
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mesh = obj.evaluated_get(graph).to_mesh()
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try:
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assert len(mesh.polygons) == 96 and mesh.uv_layers.active
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assert mesh.materials[0].original == material
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assert all(face.material_index == 0 and face.use_smooth for face in mesh.polygons)
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finally:
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obj.evaluated_get(graph).to_mesh_clear()
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undo.assert_called_once_with(message="Convert to Panorama")
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@pytest.mark.parametrize("shared", [False, True])
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def test_panorama_preserves_hdr_pixels_color_space_and_alpha(source, artifacts, monkeypatch, shared):
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result, operator = artifacts
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hdr = bpy.data.images.new("Original HDR", width=32, height=16, alpha=True, float_buffer=True)
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hdr.alpha_mode = "PREMUL"
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rgba = np.ones((16, 32, 4), np.float32)
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rgba[..., :3] = (4.0, 2.0, 0.5)
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rgba[..., 3] = 0.5
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hdr.pixels.foreach_set(rgba.ravel())
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source.data = hdr
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operator.image_identity = str(hdr.as_pointer())
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cleanup_material_color_input(operator.color_path)
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operator.color_path = str(prepare_material_color_input(hdr))
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if shared:
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other = source.copy()
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bpy.context.collection.objects.link(other)
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original_space, original_alpha = hdr.colorspace_settings.name, hdr.alpha_mode
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monkeypatch.setattr(conversion, "bpy", SimpleNamespace(data=bpy.data, ops=SimpleNamespace(ed=SimpleNamespace(undo_push=lambda **kw: {"FINISHED"})) ))
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obj = conversion.create_panorama_from_result(bpy.context, result, operator)
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color = next(n.image for n in obj.data.materials[0].node_tree.nodes if n.type == "TEX_IMAGE")
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assert color != hdr
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assert color.is_float and color.packed_file
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assert (color.colorspace_settings.name, color.alpha_mode) == (original_space, original_alpha)
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np.testing.assert_allclose(color.pixels[:], rgba.ravel(), atol=1e-6)
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assert (hdr.colorspace_settings.name, hdr.alpha_mode) == (original_space, original_alpha)
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library = result.directory / "hdr-copy.blend"
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bpy.data.libraries.write(str(library), {color})
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with bpy.data.libraries.load(str(library)) as (saved, loaded):
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loaded.images = saved.images
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restored = loaded.images[0]
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assert restored.is_float
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assert (restored.colorspace_settings.name, restored.alpha_mode) == (original_space, original_alpha)
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np.testing.assert_allclose(restored.pixels[:], rgba.ravel(), atol=1e-6)
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@pytest.mark.parametrize("failure", ["modifier", "depth_size", "stale", "replaced_image", "finalize"])
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def test_failed_response_keeps_source_and_cleans_owned_data(source, artifacts, monkeypatch, failure):
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result, operator = artifacts
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before = {name: set(getattr(bpy.data, name)) for name in ("images", "objects", "meshes", "materials")}
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if failure == "modifier":
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monkeypatch.setattr(conversion, "set_modifier_input", Mock(side_effect=RuntimeError("Failed modifier")))
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elif failure == "finalize":
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monkeypatch.setattr(conversion, "finalize_object_result", Mock(side_effect=RuntimeError("Failed finalize")))
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elif failure == "stale":
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operator.source_identity = "replaced"
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elif failure == "replaced_image":
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operator.image_identity = "replaced"
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else:
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(result.directory / "depth.json").write_text(json.dumps({"projection": "equirectangular", "image_size": [16, 8], "reference_distance": 3}))
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with pytest.raises((RuntimeError, ValueError)):
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conversion.create_panorama_from_result(bpy.context, result, operator)
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for name, values in before.items():
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assert set(getattr(bpy.data, name)) == values
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def test_panorama_conversion_undo_restores_empty(source, artifacts):
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result, operator = artifacts
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name = source.name
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image_name = source.data.name
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original_space, original_alpha = source.data.colorspace_settings.name, source.data.alpha_mode
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bpy.context.preferences.edit.use_global_undo = True
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def execute(self, context):
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conversion.create_panorama_from_result(context, result, operator)
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return {"FINISHED"}
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with patch.object(operators.GeneratePanorama, "execute", execute):
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bpy.utils.register_class(operators.GeneratePanorama)
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try:
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bpy.ops.ed.undo_push(message="Before Panorama")
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assert bpy.ops.anyimage.generate_panorama("EXEC_DEFAULT") == {"FINISHED"}
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assert bpy.data.objects[name].type == "MESH"
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assert bpy.ops.ed.undo() == {"FINISHED"}
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assert bpy.data.objects[name].type == "EMPTY"
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assert (bpy.data.images[image_name].colorspace_settings.name,
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bpy.data.images[image_name].alpha_mode) == (original_space, original_alpha)
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assert bpy.ops.ed.redo() == {"FINISHED"}
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assert bpy.data.objects[name].type == "MESH"
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finally:
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bpy.utils.unregister_class(operators.GeneratePanorama)
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