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.
66 lines
2.3 KiB
Python
66 lines
2.3 KiB
Python
from unittest.mock import patch
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import numpy as np
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from anyimage.server.models import moge as moge2_model
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from anyimage.server.models.geometry import GeometryFrame
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def test_geometry_frame_requires_matching_float32_fields():
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with np.testing.assert_raises_regex(ValueError, "validity"):
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GeometryFrame(
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depth=np.ones((2, 2), dtype=np.float32),
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validity=np.ones((1, 2), dtype=np.float32),
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intrinsics=np.eye(3, dtype=np.float32),
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)
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with np.testing.assert_raises_regex(ValueError, "normal"):
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GeometryFrame(
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depth=np.ones((2, 2), dtype=np.float32),
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validity=np.ones((2, 2), dtype=np.float32),
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intrinsics=np.eye(3, dtype=np.float32),
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normal=np.ones((2, 2, 2), dtype=np.float32),
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)
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def test_moge_infer_returns_geometry_frames_with_model_validity():
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mask = np.asarray(((1.0, 0.2), (0.7, 0.0)), dtype=np.float32)
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prediction = {
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"depth": np.ones((2, 2), dtype=np.float32),
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"normal": np.zeros((2, 2, 3), dtype=np.float32),
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"mask": mask,
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"intrinsics": np.asarray(
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((1.0, 0.0, 0.5), (0.0, 1.0, 0.5), (0.0, 0.0, 1.0)),
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dtype=np.float32,
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),
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"points": np.ones((2, 2, 3), dtype=np.float32),
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}
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with patch.object(moge2_model, "infer_one", return_value=prediction):
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frames = moge2_model.infer(None, {}, ["image"], include_points=True)
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assert len(frames) == 1
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frame = frames[0]
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assert np.array_equal(frame.validity, mask.astype(np.float32))
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assert np.array_equal(frame.normal, prediction["normal"])
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assert np.array_equal(frame.points, prediction["points"])
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assert np.array_equal(
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frame.intrinsics,
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np.asarray(((2.0, 0.0, 1.0), (0.0, 2.0, 1.0), (0.0, 0.0, 1.0))),
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)
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def test_moge_z_depth_frame_does_not_require_points():
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prediction = {
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"depth": np.ones((2, 2), dtype=np.float32),
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"normal": np.zeros((2, 2, 3), dtype=np.float32),
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"mask": np.ones((2, 2), dtype=bool),
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"intrinsics": np.eye(3, dtype=np.float32),
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"points": np.ones((2, 2, 3), dtype=np.float32),
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}
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with patch.object(moge2_model, "infer_one", return_value=prediction):
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frame = moge2_model.infer(None, {}, ["image"], include_points=False)[0]
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assert frame.points is None
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assert frame.validity.all()
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