nan
591e62085a
- Introduced a new `Boundary Padding` preference in the Cutout Tool with a default of 2 px and a configurable range of 1-4 px. - Updated the Cutout client to establish inward mapping from the final Mask, sampling in a fixed direction and processing independent material RGBA and Depth. - Enhanced the handling of RGBA and Depth during cutout operations, ensuring proper mapping and preservation of source data. - Added tests to validate the new boundary padding functionality and its integration with existing cutout processes. feat(geometry): remove overall mesh smoothing from geometry nodes - Removed the `Smooth` input from several geometry node groups to eliminate unnecessary overall mesh smoothing. - Retained `Smooth Weight` for depth nodes while removing it from Cutout and Relief Plane nodes. - Ensured that boundary, normal, and fill smoothing behaviors remain intact and consistent. - Updated tests and documentation to reflect the changes in node interfaces and behaviors. feat(normals): scale tangent normals with depth - Reused the existing `o_normal_reduction` attribute to adjust Tangent Normal strength based on the geometry's `Depth Scale`. - Ensured that Tangent Normal strength is consistent with the geometry depth, preserving full strength for materials that do not provide the attribute. - Updated tests to verify the correct behavior of normal strength adjustments in both Tangent and Object Space.
436 lines
17 KiB
Python
436 lines
17 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",
|
|
boundary_padding=2.0,
|
|
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_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
|
|
operator.boundary_padding = 3.5
|
|
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)
|
|
self.assertEqual(create_shape.call_args.kwargs["boundary_padding"], 3.5)
|