Files
AnyImage/tests/anyimage/server/test_prediction_artifacts.py
nan 591e62085a feat(cutout): implement boundary padding for cutout textures
- 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.
2026-09-15 00:40:24 +08:00

105 lines
3.2 KiB
Python

from types import SimpleNamespace
from unittest.mock import patch
import numpy as np
import pytest
from PIL import Image
from server.geometry import prediction_artifacts as artifacts
from server.models.geometry import GeometryFrame
from server.models.onnx_moge2 import depth_to_points
def make_frame(depth):
depth = np.asarray(depth, dtype=np.float32)
height, width = depth.shape
normalized = np.array([[1.2, 0, 0.4], [0, 1.4, 0.6], [0, 0, 1]], np.float32)
intrinsics = normalized.copy()
intrinsics[0] *= width
intrinsics[1] *= height
return GeometryFrame(
depth=depth,
validity=np.ones_like(depth),
intrinsics=intrinsics,
points=depth_to_points(depth, normalized),
normal=np.zeros((*depth.shape, 3), np.float32),
)
def silhouette():
alpha = np.zeros((25, 35), np.float32)
alpha[4:21, 4:22] = 1
alpha[4:21, 22:25] = 0.2
depth = np.full(alpha.shape, 20, np.float32)
depth[alpha == 1] = 2
return make_frame(depth), alpha
def test_alpha_resize_retains_threshold_values(tmp_path):
rgba = np.zeros((1, 4, 4), np.uint8)
rgba[0, :, 3] = [25, 26, 242, 243]
path = tmp_path / "alpha.png"
Image.fromarray(rgba).save(path)
alpha = artifacts._image_alpha(path, (2, 8))
np.testing.assert_array_equal(
alpha >= 0.1, [[False] * 2 + [True] * 6] * 2
)
np.testing.assert_array_equal(
alpha >= 0.95, [[False] * 6 + [True] * 2] * 2
)
@pytest.mark.parametrize(
"generate_depth,normal_mode",
[
(True, "OBJECT"),
(True, "TANGENT"),
(True, "NONE"),
(False, "OBJECT"),
],
)
def test_artifacts_write_raw_requested_depth_and_preserve_normals(
tmp_path, generate_depth, normal_mode
):
frame, alpha = silhouette()
rgba = np.full((*alpha.shape, 4), 255, np.uint8)
rgba[..., 3] = np.round(alpha * 255).astype(np.uint8)
path = tmp_path / "source.png"
Image.fromarray(rgba).save(path)
context = SimpleNamespace(
directory=tmp_path,
resource=lambda _: None,
progress=lambda *_: None,
check_cancelled=lambda: None,
)
with (
patch.object(artifacts.moge, "infer", return_value=frame) as infer,
patch.object(
artifacts, "write_depth_texture",
return_value=tmp_path / "depth.exr",
) as depth,
patch.object(
artifacts, "write_depth_metadata", return_value=tmp_path / "depth.json"
) as metadata,
patch.object(
artifacts, "_write_normal", return_value=tmp_path / "normal.png"
) as normal,
):
artifacts.generate_moge_artifacts(
context, {}, path, generate_depth=generate_depth, normal_mode=normal_mode,
)
infer.assert_called_once()
if normal_mode != "NONE":
assert normal.call_args.args[0] is frame
else:
normal.assert_not_called()
if generate_depth:
written_frame = depth.call_args.args[0]
np.testing.assert_array_equal(depth.call_args.kwargs["alpha"], alpha)
assert metadata.call_args.args[0] is written_frame
assert written_frame is frame
assert frame.depth[12, 24] == 20
else:
metadata.assert_not_called()
depth.assert_not_called()