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.
37 lines
1.5 KiB
Python
37 lines
1.5 KiB
Python
from unittest.mock import patch
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import numpy as np
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from PIL import Image
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import pytest
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from server.jobs import remove_background
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from server.models import onnx_ben2
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from tests.anyimage.server.support import FakeJobContext
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@pytest.mark.parametrize("failure", ["cancel", "prediction", "sequence", "output_kind"])
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def test_alpha_job_failure_does_not_write_result(tmp_path, failure):
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source = tmp_path / "input.png"
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Image.new("RGB", (2, 2)).save(source)
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context = FakeJobContext(tmp_path / "job", "remove-background")
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parameters = {"input": str(source), "model": "BEN2_BASE", "device": "cpu", "output_kind": "alpha"}
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if failure == "sequence":
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frames = tmp_path / "frames"
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frames.mkdir()
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for i in (1, 2):
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Image.new("RGB", (2, 2)).save(frames / f"{i}.png")
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parameters["input"] = str(frames)
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if failure == "output_kind":
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parameters["output_kind"] = "invalid"
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def infer(*args, **kwargs):
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if failure == "prediction":
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raise RuntimeError("Prediction failed")
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context.check_cancelled = lambda: (_ for _ in ()).throw(RuntimeError("Cancelled"))
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return np.ones((2, 2), np.float32)
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with patch.object(onnx_ben2, "create_session", return_value=object()), patch.object(onnx_ben2, "infer_alpha", side_effect=infer):
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with pytest.raises((RuntimeError, ValueError)):
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remove_background.run(context, parameters)
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assert not (context.directory / "alpha.npy").exists()
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