nan
2dfa9b2add
- Unified reference depth calculation to use a single implementation in common/depth.py. - Removed server-side reference depth computation and adjusted depth.json to only include image_size and intrinsics. - Updated depth texture handling to ignore transparent, invalid, and non-positive pixels when calculating reference depth. - Changed reference depth calculation to use the 95th percentile of valid depth values. - Adjusted depth direction fitting to return a flat direction when no samples are available. - Removed cleanup threshold parameters from Cutout and related nodes, simplifying the interface. - Updated tests to verify new reference depth logic and ensure compatibility with existing functionality.
47 lines
1.6 KiB
Python
47 lines
1.6 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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def test_moge_infer_returns_geometry_frame_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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frame = moge2_model.infer(None, {}, "image", include_points=True)
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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_frame_omits_points_when_not_requested():
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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)
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assert frame.points is None
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assert frame.validity.all()
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