nan
489003c2cc
- Introduced color_image.py for preparing standalone color images for tests. - Added hdr_image.py to create HDR textures for testing. - Implemented test_image_depth_panorama.py to evaluate panorama topology, UVs, and depth discontinuities. - Created test_shadeless.py to validate the opacity and HDR color endpoints of the Shadeless group. - Developed moge3_export.py for exporting dynamic MoGe-3 backbone and ONNX graphs. - Added material.py to inherit material slots onto generated geometry. - Built image_depth_panorama.py to construct a quad panorama with depth separation and sampling.
97 lines
5.6 KiB
Python
97 lines
5.6 KiB
Python
import tempfile
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from contextlib import ExitStack
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from pathlib import Path
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from types import SimpleNamespace
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from unittest.mock import Mock, patch
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from tests.support.blender import BlenderTestCase
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class AiInputFailuresTest(BlenderTestCase):
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def test_image_edits_reject_same_input_before_submission(self):
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with tempfile.TemporaryDirectory() as directory:
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path = Path(directory) / "input.tiff"
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path.touch()
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messages = []
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for module, operator_type in (
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(self.upscale, self.upscale.UpscaleImage),
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(self.remove_background, self.remove_background.RunBackgroundRemoval),
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):
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operator = operator_type()
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operator.report = Mock()
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target = Mock(image=SimpleNamespace(size=(16, 16)), start_frame=1)
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target.prepare.return_value = (path, False)
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context = SimpleNamespace(scene=SimpleNamespace(
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anyimage_settings=SimpleNamespace(video_frames=1)))
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with ExitStack() as stack:
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stack.enter_context(patch.object(module.ImageEditTarget, "capture", return_value=target))
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stack.enter_context(patch.object(module, "require_environment"))
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stack.enter_context(patch.object(module, "require_model"))
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stack.enter_context(patch.object(self.runtime.runtime, "active_job", None))
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submit = stack.enter_context(patch.object(self.runtime.runtime, "begin_job"))
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if module == self.upscale:
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stack.enter_context(patch.object(module, "configured_upscale_model", return_value="SAFMN_REAL_X4"))
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stack.enter_context(patch.object(module, "configured_max_ai_input_size", return_value=2048))
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self.assertEqual(operator.execute(context), {"CANCELLED"})
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submit.assert_not_called()
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messages.append(operator.report.call_args.args[1])
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self.assertIsNone(operator._image_target)
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self.assertTrue(path.exists())
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self.assertEqual(messages[0], messages[1])
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self.assertIn("Unsupported input format: .tiff", messages[0])
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def test_remove_background_catches_nested_error(self):
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operator = self.remove_background.RemoveImageBackground()
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operator.report = Mock()
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ops = SimpleNamespace(anyimage=SimpleNamespace(
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run_background_removal=Mock(side_effect=RuntimeError("Error: invalid input\n"))))
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with patch.object(self.remove_background.bpy, "ops", ops, create=True):
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self.assertEqual(operator.execute(None), {"CANCELLED"})
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operator.report.assert_called_once_with({"ERROR"}, "invalid input")
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def test_setup_failures_cancel_at_each_boundary(self):
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for ready in (True, False):
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operator = self.ai_setup.SetupAIEnvironment()
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operator.use_mirror = False
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operator.report = Mock()
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failing = Mock(side_effect=RuntimeError("Error: setup failed\n"))
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ops = SimpleNamespace(anyimage=SimpleNamespace(
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download_required_models=failing, install_environment=failing))
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with (
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patch.object(self.ai_setup, "ai_status", return_value={"ready": False, "environment_ready": ready}),
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patch.object(self.ai_setup.bpy, "ops", ops, create=True),
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):
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self.assertEqual(operator.execute(None), {"CANCELLED"})
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operator.report.assert_called_once_with({"ERROR"}, "setup failed")
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owner = SimpleNamespace(report=Mock())
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with (
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patch.object(self.ai, "ai_ready", return_value=False),
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patch.object(self.ai.bpy, "ops", SimpleNamespace(anyimage=SimpleNamespace(
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setup_ai_environment=Mock(side_effect=RuntimeError("Error: setup failed\n")))), create=True),
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):
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self.assertEqual(self.ai.invoke_ai_setup_if_needed(owner), {"CANCELLED"})
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owner.report.assert_called_once_with({"ERROR"}, "setup failed")
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def test_depth_and_relief_cleanup_on_nested_failure(self):
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module = self.convert_to_plane
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for plane_type in ("DEPTH", "RELIEF"):
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for failure in (RuntimeError("Error: invalid input\n"), None):
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with tempfile.TemporaryDirectory() as directory:
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path = Path(directory) / "prepared" / "input.png"
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path.parent.mkdir()
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path.touch()
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operator = SimpleNamespace(mesh_detail=4, report=Mock())
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context = SimpleNamespace(object=SimpleNamespace(name="source", as_pointer=lambda: 1,
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data=SimpleNamespace(as_pointer=lambda: 2)), scene=object())
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generate = Mock(side_effect=failure, return_value={"CANCELLED"})
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with (
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patch.object(module, "invoke_ai_setup_if_needed", return_value=None),
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patch.object(module, "prepare_material_color_input", return_value=path),
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patch.object(module, "material_analysis_input", return_value=path),
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patch.object(module, "depth_plane_settings", return_value=("model", 5)),
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patch.object(module, "configured_max_ai_input_size", return_value=2048),
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patch.object(module.bpy, "ops", SimpleNamespace(anyimage=SimpleNamespace(generate_depth_plane=generate)), create=True),
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):
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self.assertEqual(module.start_depth_plane_job(operator, context, plane_type), {"CANCELLED"})
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self.assertFalse(path.parent.exists())
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