Files
AnyImage/tests/anyimage/operators/test_cutout_operators.py
nan 18799e8828 Refactor Cutout Tool to Use World Space Edge Length
- Replaced the Mesh Detail parameter with a new Edge Length property to define cutout sampling in physical units.
- Introduced Minimum Relative Edge Length preference to control effective spacing based on the bounding box of the cutout content.
- Updated tests to validate the new edge length functionality and ensure consistent behavior across different resolutions and canvas sizes.
- Removed deprecated parameters and adjusted related properties to align with the new edge length implementation.
- Enhanced geometry sampling logic to utilize effective world spacing for both standard and fine outline modes.
2026-09-12 23:03:24 +08:00

449 lines
18 KiB
Python

from contextlib import nullcontext
import importlib
import json
from pathlib import Path
from types import SimpleNamespace
from unittest.mock import Mock, patch
from tests.support.blender import BlenderTestCase
class CutoutOperatorsTest(BlenderTestCase):
def test_cutout_gestures_start_on_empty_pick_and_lasso_finishes_on_release(self):
viewport = importlib.import_module("anyimage.common.viewport")
source = SimpleNamespace(name="Source", matrix_world="matrix", data=object())
context = SimpleNamespace(
area=SimpleNamespace(as_pointer=lambda: 1, tag_redraw=Mock()),
region=SimpleNamespace(as_pointer=lambda: 2),
workspace=SimpleNamespace(status_text_set=Mock()),
window_manager=SimpleNamespace(modal_handler_add=Mock()),
scene=SimpleNamespace(anyimage_settings=SimpleNamespace(mask_gesture="BRUSH")),
)
event = SimpleNamespace(type="LEFTMOUSE", value="PRESS", mouse_region_x=12, mouse_region_y=18)
with (
patch.object(viewport, "resolve_image_edit_click", return_value=(source, True)),
patch.object(viewport, "is_animated_image", return_value=False),
patch.object(viewport, "serialize_matrix", return_value="matrix"),
patch.object(viewport, "active_view3d_tool_id", return_value=None),
patch.object(self.fake_bpy.types, "SpaceView3D", SimpleNamespace(draw_handler_add=Mock()), create=True),
):
for gesture in ("LASSO", "POLYLINE"):
with self.subTest(gesture=gesture):
context.scene.anyimage_settings.cutout_gesture = gesture
operator = self.cutout_main.SelectCutoutSelection()
operator.report = Mock()
self.assertEqual(operator.invoke(context, event), {"RUNNING_MODAL"})
self.assertEqual(operator._path, [(12.0, 18.0)])
self.assertEqual(operator.gesture, gesture)
self.assertEqual(context.scene.anyimage_settings.mask_gesture, "BRUSH")
operator._complete = Mock(return_value={"FINISHED"})
release = SimpleNamespace(type="LEFTMOUSE", value="RELEASE", mouse_region_x=20, mouse_region_y=30)
result = operator.modal(context, release)
if gesture == "LASSO":
self.assertEqual(result, {"FINISHED"})
operator._complete.assert_called_once_with(context)
else:
operator._complete.assert_not_called()
status = context.workspace.status_text_set.call_args.args[0]
self.assertIn("Polyline", status)
self.assertIn("Backspace", status)
def test_flat_and_solid_without_ai_build_locally(self):
import numpy as np
source = SimpleNamespace(
data=SimpleNamespace(size=(10, 10)), select_set=lambda _value: None
)
context = SimpleNamespace(
view_layer=SimpleNamespace(objects=SimpleNamespace(active=None))
)
selection_mask = self.image_selection.SelectionMask(
np.ones((8, 8), dtype=np.float32), (1, 1, 9, 9)
)
source_rgba = np.ones((10, 10, 4), dtype=np.float32)
for shape in ("FLAT", "SOLID"):
with self.subTest(shape=shape):
operator = SimpleNamespace(
source_object_name="Source",
selection_path_json=json.dumps(
{"points": [[1, 1], [9, 1], [9, 9], [1, 9]]}
),
shape=shape,
gesture="POLYLINE",
edge_length=0.1,
alpha_threshold=0.25,
fine_outline=False,
generate_normal=False,
report=lambda *_args: None,
_needs_generation=lambda: False,
)
with (
patch.object(
self.cutout_main,
"require_image_empty",
return_value=source,
),
patch.object(
self.cutout_main, "is_animated_image", return_value=False
),
patch.object(
self.cutout_main, "image_rgba", return_value=source_rgba
) as read_rgba,
patch.object(
self.cutout_main,
"rasterize_selection_path",
return_value=selection_mask,
) as rasterize,
patch.object(
self.cutout_main,
"configured_max_ai_input_size",
return_value=2048,
),
patch.object(
self.cutout_main,
"_cutout_content_values",
return_value=selection_mask.values,
),
patch.object(
self.cutout_main,
"material_color_image",
return_value=nullcontext("Color"),
),
patch.object(
self.cutout_main, "create_cutout_shape"
) as convert,
):
result = self.cutout_main.CutoutSelectionToShape.execute(
operator, context
)
self.assertEqual(result, {"FINISHED"})
read_rgba.assert_called_once_with(source.data)
rasterize.assert_called_once()
convert.assert_called_once_with(
context,
source,
shape,
0.1,
selection_mask.values,
selection_mask.bounds,
alpha_threshold=0.25,
fine_outline=False,
color_image="Color",
gesture="POLYLINE",
report=operator.report,
)
def test_ai_cutout_writes_the_selection_bounds_image(self):
import numpy as np
source = SimpleNamespace(
data=SimpleNamespace(size=(4096, 2048)),
select_set=lambda _value: None,
)
context = SimpleNamespace(
view_layer=SimpleNamespace(objects=SimpleNamespace(active=None))
)
source_rgba = np.ones((4, 8, 4), dtype=np.float32)
selection_mask = self.image_selection.SelectionMask(
np.ones((2, 6), dtype=np.float32),
(1, 1, 7, 3),
)
operator = self.cutout_main.CutoutSelectionToShape()
operator.alpha_threshold = 0.25
operator.fine_outline = False
operator.source_object_name = "Source"
operator.selection_path_json = json.dumps(
{"points": [[1, 1], [7, 1], [7, 3], [1, 3]]}
)
operator.shape = "DEPTH_SOLID"
operator.report = lambda *_args: None
operator.edge_length = 0.1
operator.generate_normal = False
operator.report = lambda *_args: None
with (
patch.object(
self.cutout_main,
"require_image_empty",
return_value=source,
),
patch.object(self.cutout_main, "is_animated_image", return_value=False),
patch.object(
self.cutout_main,
"image_rgba",
return_value=source_rgba,
) as read_rgba,
patch.object(
self.cutout_main,
"rasterize_selection_path",
return_value=selection_mask,
) as rasterize,
patch.object(
self.cutout_main,
"configured_max_ai_input_size",
return_value=2048,
),
patch.object(
self.cutout_main,
"invoke_ai_setup_if_needed",
return_value=None,
),
patch.object(
self.cutout_main,
"cutout_geometry_settings",
return_value=("MODEL", 5),
),
patch.object(
self.cutout_main,
"prepare_material_color_input",
return_value=Path(__file__),
) as prepare_input,
patch.object(self.cutout_main, "material_analysis_input", return_value=Path(__file__)),
patch.object(
self.cutout_main.JobOperatorBase,
"execute",
return_value={"FINISHED"},
),
):
result = operator.execute(context)
self.assertEqual(result, {"FINISHED"})
read_rgba.assert_called_once_with(source.data)
rasterize.assert_called_once()
prepare_input.assert_called_once_with(
source.data,
selection_mask.bounds,
source_rgba,
)
def test_empty_cutout_selection_is_rejected_after_shape_choice(self):
source = SimpleNamespace(
data=SimpleNamespace(size=(4096, 2048)),
select_set=lambda _value: None,
)
context = SimpleNamespace(
view_layer=SimpleNamespace(objects=SimpleNamespace(active=None))
)
reports = []
operator = SimpleNamespace(
source_object_name="Source",
selection_path_json=json.dumps(
{"points": [[1, 1], [7, 1], [7, 3], [1, 3]]}
),
shape="FLAT",
edge_length=0.1,
generate_normal=False,
report=lambda level, message: reports.append((level, message)),
)
with (
patch.object(
self.cutout_main,
"require_image_empty",
return_value=source,
),
patch.object(self.cutout_main, "is_animated_image", return_value=False),
patch.object(self.cutout_main, "image_rgba"),
patch.object(
self.cutout_main,
"rasterize_selection_path",
side_effect=self.image_selection.ImageEditWarning(
"The selection contains no visible image pixels"
),
),
patch.object(self.cutout_main, "create_cutout_shape") as create_shape,
):
result = self.cutout_main.CutoutSelectionToShape.execute(
operator,
context,
)
self.assertEqual(result, {"CANCELLED"})
create_shape.assert_not_called()
self.assertEqual(
reports,
[
(
{"WARNING"},
"The selection contains no visible image pixels",
)
],
)
def test_cutout_request_describes_ai_capabilities(self):
operator = self.cutout_main.CutoutSelectionToShape()
operator.alpha_threshold = 0.25
operator.fine_outline = False
operator.input_path = __file__
operator.color_path = __file__
operator.source_object_name = "Source"
operator.shape = "DEPTH_SOLID"
operator.model = self.anyimage.preferences.DEFAULT_GEOMETRY_MODEL_KEY
operator.resolution_level = 5
operator.max_ai_input_size = 2048
operator.generate_normal = True
context = SimpleNamespace(
scene=SimpleNamespace(anyimage_settings=SimpleNamespace())
)
with (
patch.object(self.cutout_main, "require_environment"),
patch.object(self.cutout_main, "require_model") as require_model,
patch.object(self.cutout_main, "require_input_path", return_value=Path("input.png")),
patch.object(
self.cutout_main, "production_device", return_value="CPU"
),
patch.object(
self.cutout_main,
"moge2_parameters",
return_value={"model": operator.model, "resolution_level": 5},
),
):
parameters = operator.request(context)
self.assertEqual(
[call.args[0] for call in require_model.call_args_list],
[operator.model],
)
self.assertTrue(parameters["generate_depth"])
self.assertEqual(parameters["alpha_threshold"], 0.25)
self.assertEqual(parameters["normal_mode"], "OBJECT")
def test_cutout_geometry_settings_use_configured_moge(self):
preferences = SimpleNamespace(
geometry_model="MOGE2_VITB_NORMAL",
geometry_resolution_level=7,
)
with patch.object(self.cutout_main, "addon_preferences", return_value=preferences), patch.object(
self.anyimage.preferences, "addon_preferences", return_value=preferences
):
settings = self.cutout_main.cutout_geometry_settings(None)
self.assertEqual(
settings,
("MOGE2_VITB_NORMAL", 7),
)
def test_cutout_tool_settings_gate_normal_generation(self):
class Row:
def __init__(self, events):
self.events = events
self.enabled = True
def prop(self, _owner, name, **_options):
self.events.append(("prop", name, self.enabled))
class Layout:
def __init__(self):
self.events = []
def operator(self, identifier, **_options):
self.events.append(("operator", identifier, True))
def row(self):
return Row(self.events)
def prop(self, _owner, name, **_options):
self.events.append(("prop", name, True))
context = SimpleNamespace(
scene=SimpleNamespace(anyimage_settings=SimpleNamespace())
)
missing = {
"environment_ready": False,
"missing_models": (),
"ready": False,
}
setup = ("operator", "anyimage.setup_ai_environment", True)
with patch.object(self.ai, "ai_status", return_value=missing):
cutout_tool = importlib.import_module(
"anyimage.operators.cutout_tool"
).CutoutTool
layout = Layout()
cutout_tool.draw_settings(context, layout, None)
self.assertEqual(
layout.events,
[
("prop", "cutout_gesture", True),
("prop", "cutout_edge_length", True),
("prop", "cutout_fine_outline", True),
("prop", "cutout_alpha_threshold", True),
setup,
("prop", "cutout_generate_normal", False),
],
)
ready = {"environment_ready": True, "missing_models": (), "ready": True}
with patch.object(self.ai, "ai_status", return_value=ready):
layout = Layout()
cutout_tool.draw_settings(context, layout, None)
self.assertNotIn(setup, layout.events)
self.assertTrue(all(event[2] for event in layout.events))
def test_cutout_ai_response_reuses_bounds_color_and_gesture_snapshot(self):
import numpy as np
source = SimpleNamespace(data=SimpleNamespace())
color_image = SimpleNamespace(users=0)
pure_values = np.ones((3, 4), dtype=np.float32)
pure_values[:, 0] = 0.0
selection_mask = self.image_selection.SelectionMask(
pure_values,
(10, 20, 14, 23),
)
operator = self.cutout_main.CutoutSelectionToShape()
operator.alpha_threshold = 0.25
operator.fine_outline = False
operator.source_object_name = "Source"
operator.selection_bounds_json = "[10,20,14,23]"
operator.input_path = __file__
operator.color_path = __file__
operator.shape = "FLAT"
operator.gesture = "POLYLINE"
operator.report = lambda *_args: None
operator.edge_length = 0.1
operator.generate_normal = True
operator._selection_mask = selection_mask
result = SimpleNamespace(value={}, file=lambda _key: Path(__file__))
with (
patch.object(
self.cutout_main,
"require_image_empty",
return_value=source,
),
patch.object(
self.cutout_main,
"_generated_color_result",
return_value=(
color_image,
np.ones((3, 4), dtype=np.float32),
selection_mask.bounds,
),
) as color_result,
patch.object(self.cutout_main, "create_cutout_shape") as create_shape,
):
context = SimpleNamespace(scene=SimpleNamespace(
anyimage_settings=SimpleNamespace(cutout_gesture="LASSO")
))
message = operator.response(context, result)
color_result.assert_called_once_with(
__file__,
selection_mask.bounds,
)
self.assertEqual(message, "Flat is ready")
self.assertEqual(create_shape.call_args.kwargs["gesture"], "POLYLINE")
content_values = create_shape.call_args.args[4]
np.testing.assert_array_equal(content_values, pure_values)
self.assertEqual(create_shape.call_args.args[5], selection_mask.bounds)
self.assertIs(create_shape.call_args.kwargs["color_image"], color_image)
self.assertEqual(create_shape.call_args.kwargs["alpha_threshold"], 0.25)
self.assertIs(create_shape.call_args.kwargs["fine_outline"], False)