Files
AnyImage/tests/anyimage/operators/test_panorama_conversion.py
nan a0dd6e4a88 feat: Add restore cutout depth extension with edge depth correction
- Introduced a new extension for restoring cutout depth with edge correction.
- Implemented edge depth extension algorithm in `edge_depth.py` to enhance depth accuracy near cutout edges.
- Updated `generate_moge_artifacts` to include an option for extending depth edges during depth generation.
- Modified cutout job processing to enable edge depth extension based on depth request.
- Added comprehensive tests for edge depth functionality, ensuring correct behavior under various scenarios.
- Updated existing node loading functions to remove asset revision dependencies, simplifying the loading process.
- Created new design and proposal documentation outlining the goals and decisions for the extension.
2026-09-13 20:36:52 +08:00

194 lines
10 KiB
Python

"""Verify the public panorama entry and transactional Blender result handling."""
import json
from types import SimpleNamespace
from unittest.mock import Mock, patch
import bpy
import numpy as np
import pytest
from PIL import Image
from mathutils import Matrix
from anyimage.operators.convert_to_panorama import operators, object as conversion
from server.geometry.depth_texture import write_float_exr
from anyimage.common.color_image import prepare_material_color_input, cleanup_material_color_input
@pytest.fixture
def source():
bpy.ops.wm.read_factory_settings(use_empty=True)
image = bpy.data.images.new("Current panorama", width=32, height=16, alpha=True)
rgba = np.ones((16, 32, 4), np.float32)
rgba[:8, :, 3] = 0
rgba[8:12, :, 3] = 0.5
image.pixels.foreach_set(rgba.ravel())
obj = bpy.data.objects.new("Panorama Empty", None)
obj.empty_display_type = "IMAGE"
obj.data = image
bpy.context.collection.objects.link(obj)
obj.select_set(True)
bpy.context.view_layer.objects.active = obj
return obj
def test_entry_submits_current_alpha_preferences_and_cleans_cancelled_input(source, monkeypatch):
submitted = {}
def submit(**parameters):
submitted.update(parameters)
with Image.open(parameters["input_path"]) as image:
alpha = np.asarray(image)[..., 3]
assert not alpha[8:].any()
assert np.all(abs(alpha[4:8].astype(float) - 128) <= 1)
return {"CANCELLED"}
monkeypatch.setattr(operators, "invoke_ai_setup_if_needed", lambda _operator: None)
monkeypatch.setattr(operators, "addon_preferences", lambda _: SimpleNamespace(geometry_model="MOGE2_VITB", geometry_resolution_level=2))
monkeypatch.setattr(operators, "configured_geometry_model", lambda _: "MOGE2_VITB_NORMAL")
monkeypatch.setattr(operators, "configured_max_ai_input_size", lambda _: 1024)
monkeypatch.setattr(operators, "bpy", SimpleNamespace(ops=SimpleNamespace(anyimage=SimpleNamespace(generate_panorama=submit))))
operator = SimpleNamespace(mesh_detail=4, report=Mock())
assert operators.ConvertToPanorama.execute(operator, bpy.context) == {"CANCELLED"}
assert submitted["model"] == "MOGE2_VITB_NORMAL" and submitted["resolution_level"] == 2
assert submitted["max_input_size"] == 1024 and submitted["mesh_detail"] == 4
assert submitted["color_path"] == submitted["input_path"]
from pathlib import Path
assert not Path(submitted["input_path"]).exists()
assert bpy.data.objects.get(source.name) == source
@pytest.mark.parametrize("image_source,size", [("MOVIE", (32, 16)), ("SEQUENCE", (32, 16)), ("FILE", (32, 32))])
def test_invalid_input_is_rejected_before_setup(image_source, size, monkeypatch):
setup = Mock()
monkeypatch.setattr(operators, "invoke_ai_setup_if_needed", setup)
obj = SimpleNamespace(data=SimpleNamespace(source=image_source, size=size))
assert operators.ConvertToPanorama.execute(SimpleNamespace(report=Mock()), SimpleNamespace(object=obj)) == {"CANCELLED"}
setup.assert_not_called()
@pytest.fixture
def artifacts(tmp_path, source):
rgba = np.ones((16, 32, 4), np.float32)
rgba[..., :3] = 3
write_float_exr(rgba, tmp_path / "depth.exr")
(tmp_path / "depth.json").write_text(json.dumps({"projection": "equirectangular", "image_size": [32, 16]}))
result = SimpleNamespace(directory=tmp_path, file=lambda key: tmp_path / {"depth": "depth.exr", "depth_metadata": "depth.json"}[key])
operator = SimpleNamespace(source_object_name=source.name, source_identity=str(source.as_pointer()),
image_identity=str(source.data.as_pointer()), mesh_detail=2,
color_path=str(prepare_material_color_input(source.data)))
yield result, operator
cleanup_material_color_input(operator.color_path)
def test_result_replaces_source_with_zero_rotation_and_shadeless_material(source, artifacts, monkeypatch):
result, operator = artifacts
from anyimage.common.node import load_node_group
saved = load_node_group("O Image Depth Panorama")
matrix = Matrix.Translation((2, -3, 4)) @ Matrix.Rotation(0.6, 4, "Y") @ Matrix.Diagonal((2, 3, 4, 1))
source.matrix_world = matrix
source.empty_image_offset = (0.3, -0.8)
undo = Mock(return_value={"FINISHED"})
monkeypatch.setattr(conversion, "bpy", SimpleNamespace(data=bpy.data, ops=SimpleNamespace(ed=SimpleNamespace(undo_push=undo))))
obj = conversion.create_panorama_from_result(bpy.context, result, operator)
assert obj.modifiers[0].node_group == saved
assert saved.name == "O Image Depth Panorama"
assert obj.name == operator.source_object_name and obj.type == "MESH"
np.testing.assert_allclose(obj.location, matrix.translation, atol=1e-6)
np.testing.assert_allclose(obj.scale, matrix.to_scale(), atol=1e-6)
np.testing.assert_array_equal(obj.rotation_euler, (0, 0, 0))
material = obj.data.materials[0]
assert any(n.type == "GROUP" and n.node_tree.name == "O Shadeless" for n in material.node_tree.nodes)
assert [n.node_tree.name for n in material.node_tree.nodes if n.type == "GROUP"] == ["O Shadeless"]
texture = next(n for n in material.node_tree.nodes if n.type == "TEX_IMAGE")
assert texture.extension == "REPEAT"
assert bpy.context.view_layer.objects.active == obj
assert all(image.packed_file for image in bpy.data.images if image.name.endswith(("_color.png", "_depth.exr")))
graph = bpy.context.evaluated_depsgraph_get()
mesh = obj.evaluated_get(graph).to_mesh()
try:
assert len(mesh.polygons) == 96 and mesh.uv_layers.active
assert mesh.materials[0].original == material
assert all(face.material_index == 0 and face.use_smooth for face in mesh.polygons)
finally:
obj.evaluated_get(graph).to_mesh_clear()
undo.assert_called_once_with(message="Convert to Panorama")
@pytest.mark.parametrize("shared", [False, True])
def test_panorama_preserves_hdr_pixels_color_space_and_alpha(source, artifacts, monkeypatch, shared):
result, operator = artifacts
hdr = bpy.data.images.new("Original HDR", width=32, height=16, alpha=True, float_buffer=True)
hdr.alpha_mode = "PREMUL"
rgba = np.ones((16, 32, 4), np.float32)
rgba[..., :3] = (4.0, 2.0, 0.5)
rgba[..., 3] = 0.5
hdr.pixels.foreach_set(rgba.ravel())
source.data = hdr
operator.image_identity = str(hdr.as_pointer())
cleanup_material_color_input(operator.color_path)
operator.color_path = str(prepare_material_color_input(hdr))
if shared:
other = source.copy()
bpy.context.collection.objects.link(other)
original_space, original_alpha = hdr.colorspace_settings.name, hdr.alpha_mode
monkeypatch.setattr(conversion, "bpy", SimpleNamespace(data=bpy.data, ops=SimpleNamespace(ed=SimpleNamespace(undo_push=lambda **kw: {"FINISHED"})) ))
obj = conversion.create_panorama_from_result(bpy.context, result, operator)
color = next(n.image for n in obj.data.materials[0].node_tree.nodes if n.type == "TEX_IMAGE")
assert color != hdr
assert color.is_float and color.packed_file
assert (color.colorspace_settings.name, color.alpha_mode) == (original_space, original_alpha)
np.testing.assert_allclose(color.pixels[:], rgba.ravel(), atol=1e-6)
assert (hdr.colorspace_settings.name, hdr.alpha_mode) == (original_space, original_alpha)
library = result.directory / "hdr-copy.blend"
bpy.data.libraries.write(str(library), {color})
with bpy.data.libraries.load(str(library)) as (saved, loaded):
loaded.images = saved.images
restored = loaded.images[0]
assert restored.is_float
assert (restored.colorspace_settings.name, restored.alpha_mode) == (original_space, original_alpha)
np.testing.assert_allclose(restored.pixels[:], rgba.ravel(), atol=1e-6)
@pytest.mark.parametrize("failure", ["modifier", "depth_size", "stale", "replaced_image", "finalize"])
def test_failed_response_keeps_source_and_cleans_owned_data(source, artifacts, monkeypatch, failure):
result, operator = artifacts
before = {name: set(getattr(bpy.data, name)) for name in ("images", "objects", "meshes", "materials")}
if failure == "modifier":
monkeypatch.setattr(conversion, "set_modifier_input", Mock(side_effect=RuntimeError("Failed modifier")))
elif failure == "finalize":
monkeypatch.setattr(conversion, "finalize_object_result", Mock(side_effect=RuntimeError("Failed finalize")))
elif failure == "stale":
operator.source_identity = "replaced"
elif failure == "replaced_image":
operator.image_identity = "replaced"
else:
(result.directory / "depth.json").write_text(json.dumps({"projection": "equirectangular", "image_size": [16, 8]}))
with pytest.raises((RuntimeError, ValueError)):
conversion.create_panorama_from_result(bpy.context, result, operator)
for name, values in before.items():
assert set(getattr(bpy.data, name)) == values
def test_panorama_conversion_undo_restores_empty(source, artifacts):
result, operator = artifacts
name = source.name
image_name = source.data.name
original_space, original_alpha = source.data.colorspace_settings.name, source.data.alpha_mode
bpy.context.preferences.edit.use_global_undo = True
def execute(self, context):
conversion.create_panorama_from_result(context, result, operator)
return {"FINISHED"}
with patch.object(operators.GeneratePanorama, "execute", execute):
bpy.utils.register_class(operators.GeneratePanorama)
try:
bpy.ops.ed.undo_push(message="Before Panorama")
assert bpy.ops.anyimage.generate_panorama("EXEC_DEFAULT") == {"FINISHED"}
assert bpy.data.objects[name].type == "MESH"
assert bpy.ops.ed.undo() == {"FINISHED"}
assert bpy.data.objects[name].type == "EMPTY"
assert (bpy.data.images[image_name].colorspace_settings.name,
bpy.data.images[image_name].alpha_mode) == (original_space, original_alpha)
assert bpy.ops.ed.redo() == {"FINISHED"}
assert bpy.data.objects[name].type == "MESH"
finally:
bpy.utils.unregister_class(operators.GeneratePanorama)