Files
AnyImage/tests/test_geometry_artifacts.py
nan 4c902ed7db feat(node_assets): add image plane geometry nodes and validation scripts
- Implemented `image_plane.py` to build the Image Plane Geometry Nodes group with customizable parameters for geometry, subdivide, and thickness.
- Created `image_plane_validation.py` to validate the functionality of the image plane, ensuring correct geometry generation and material assignment.
- Developed `material_layers.py` to construct shader node groups for image materials, including depth and normal handling.
- Authored `plane_layouts.py` to define node arrangements for image geometry assets.
- Introduced `shadeless.py` to create a shadeless shader node group that displays color without scene lighting while preserving shadows and reflections.
2026-09-08 23:24:27 +08:00

294 lines
10 KiB
Python

import importlib.util
import json
import sys
from types import SimpleNamespace
from unittest.mock import patch
from server_runtime_test_support import ServerTestCase
class GeometryArtifactsTest(ServerTestCase):
def test_depth_artifacts_store_texture_and_compact_metadata(self):
import numpy as np
depth = importlib.import_module("server.geometry.depth_texture")
GeometryFrame = importlib.import_module(
"server.models.geometry"
).GeometryFrame
texture_path = self.storage_root / "depth.exr"
metadata_path = self.storage_root / "depth.json"
validity = np.asarray(
((1.0, 1.0, 0.0), (1.0, 1.0, 1.0)),
dtype=np.float32,
)
calibration = np.asarray(((False, True, True), (False, False, True)))
frame = GeometryFrame(
depth=np.asarray(
((1.0, 2.0, 3.0), (4.0, 5.0, 6.0)),
dtype=np.float32,
),
validity=validity,
points=np.ones((2, 3, 3), dtype=np.float32),
intrinsics=np.eye(3, dtype=np.float32),
)
depth.write_depth_texture(frame, texture_path)
depth.write_depth_metadata(frame, calibration, metadata_path)
self.assertTrue(texture_path.is_file())
self.assertEqual(texture_path.read_bytes()[:4], b"v/1\x01")
metadata = json.loads(metadata_path.read_text(encoding="utf-8"))
self.assertEqual(metadata["image_size"], [3, 2])
self.assertEqual(metadata["intrinsics"], np.eye(3).tolist())
self.assertAlmostEqual(metadata["reference_depth"], 4.0)
def test_object_normal_texture_matches_depth_surface_axes(self):
import numpy as np
from PIL import Image
normal_texture = importlib.import_module("server.geometry.normal_texture")
GeometryFrame = importlib.import_module(
"server.models.geometry"
).GeometryFrame
output_path = self.storage_root / "object-normal.png"
camera_normals = np.asarray(
[[
(0.0, 0.0, -1.0),
(1.0, 0.0, 0.0),
(0.0, 1.0, 0.0),
(0.0, 0.0, -1.0),
]],
dtype=np.float32,
)
valid = np.asarray([[True, True, True, False]], dtype=bool)
frame = GeometryFrame(
depth=np.ones((1, 4), dtype=np.float32),
validity=np.ones((1, 4), dtype=np.float32),
intrinsics=np.eye(3, dtype=np.float32),
normal=camera_normals,
)
normal_texture.write_camera_normal_texture(
frame,
valid,
(0, 0),
(4, 1),
(4, 1),
output_path,
normal_mode="OBJECT",
)
with Image.open(output_path) as opened:
encoded = np.asarray(opened, dtype=np.uint8)
np.testing.assert_array_equal(
encoded,
np.asarray(
[[
(127, 127, 255),
(255, 127, 127),
(127, 0, 127),
(128, 128, 255),
]],
dtype=np.uint8,
),
)
def test_moge_model_input_composites_rgba_over_black(self):
import numpy as np
from PIL import Image
artifacts = sys.modules["server.geometry.prediction_artifacts"]
first_path = self.storage_root / "first.png"
second_path = self.storage_root / "second.png"
first = np.asarray(
[[(240, 120, 60, 0), (200, 100, 50, 128), (9, 8, 7, 255)]],
dtype=np.uint8,
)
second = first.copy()
second[0, 0, :3] = (1, 2, 3)
Image.fromarray(first, mode="RGBA").save(first_path)
Image.fromarray(second, mode="RGBA").save(second_path)
first_output = artifacts._limited_model_input(
first_path,
self.storage_root / "first-model.png",
2048,
)
second_output = artifacts._limited_model_input(
second_path,
self.storage_root / "second-model.png",
2048,
)
with Image.open(first_output) as opened:
first_rgb = np.asarray(opened, dtype=np.uint8)
with Image.open(second_output) as opened:
second_rgb = np.asarray(opened, dtype=np.uint8)
np.testing.assert_array_equal(first_rgb, second_rgb)
np.testing.assert_array_equal(
first_rgb,
np.asarray([[(0, 0, 0), (100, 50, 25), (9, 8, 7)]], dtype=np.uint8),
)
def test_geometry_writers_reject_missing_or_non_finite_fields(self):
import numpy as np
depth = importlib.import_module("server.geometry.depth_texture")
normal = importlib.import_module("server.geometry.normal_texture")
GeometryFrame = importlib.import_module(
"server.models.geometry"
).GeometryFrame
base = {
"depth": np.ones((1, 2), dtype=np.float32),
"validity": np.ones((1, 2), dtype=np.float32),
"intrinsics": np.eye(3, dtype=np.float32),
}
with self.assertRaisesRegex(ValueError, "point field"):
depth.write_depth_texture(
GeometryFrame(**base),
self.storage_root / "missing-points.exr",
)
point_frame = GeometryFrame(
**base,
points=np.asarray([[(0.0, 0.0, 1.0), (np.nan, 0.0, 1.0)]], dtype=np.float32),
)
with self.assertRaisesRegex(ValueError, "Point field"):
depth.write_depth_texture(
point_frame,
self.storage_root / "nan-points.exr",
)
depth_frame = GeometryFrame(
**base, points=np.asarray([[(0, 0, 1), (0, 0, np.inf)]], dtype=np.float32),
)
with self.assertRaisesRegex(ValueError, "Point field"):
depth.write_depth_texture(
depth_frame,
self.storage_root / "inf-depth.exr",
)
with self.assertRaisesRegex(ValueError, "normal field"):
normal.write_camera_normal_texture(
GeometryFrame(**base),
np.ones((1, 2), dtype=bool),
(0, 0),
(2, 1),
(2, 1),
self.storage_root / "missing-normal.png",
)
normal_frame = GeometryFrame(
**base,
normal=np.asarray(
[[(0.0, 0.0, 1.0), (0.0, np.nan, 1.0)]],
dtype=np.float32,
),
)
with self.assertRaisesRegex(ValueError, "Normal field"):
normal.write_camera_normal_texture(
normal_frame,
np.ones((1, 2), dtype=bool),
(0, 0),
(2, 1),
(2, 1),
self.storage_root / "nan-normal.png",
)
self.assertFalse(any(self.storage_root.glob("*.exr")))
self.assertFalse(any(self.storage_root.glob("*-normal.png")))
def test_moge_artifact_orchestration_uses_one_geometry_frame(self):
import numpy as np
from PIL import Image
artifacts = sys.modules["server.geometry.prediction_artifacts"]
GeometryFrame = importlib.import_module(
"server.models.geometry"
).GeometryFrame
input_path = self.storage_root / "selection.png"
Image.new("RGBA", (2, 2), (255, 128, 64, 255)).save(input_path)
output_directory = self.storage_root / "job"
output_directory.mkdir()
context = SimpleNamespace(
directory=output_directory,
resource=lambda _name: object(),
progress=lambda *_args: None,
check_cancelled=lambda: None,
)
frame = GeometryFrame(
depth=np.ones((2, 2), dtype=np.float32),
validity=np.ones((2, 2), dtype=np.float32),
intrinsics=np.eye(3, dtype=np.float32),
normal=np.zeros((2, 2, 3), dtype=np.float32),
points=np.ones((2, 2, 3), dtype=np.float32),
)
with patch.object(artifacts.moge2, "infer", return_value=[frame]) as infer:
result = artifacts.generate_moge2_artifacts(
context,
{"max_input_size": 2048},
input_path,
generate_depth=True,
normal_mode="OBJECT",
)
infer.assert_called_once()
self.assertEqual(
set(result),
{"depth", "depth_metadata", "object_normal"},
)
self.assertFalse((output_directory / "model-input.png").exists())
self.assertTrue(all(path.is_file() for path in result.values()))
self.assertTrue(infer.call_args.kwargs["include_points"])
def test_generate_cutout_artifacts_only_returns_requested_outputs(self):
job = sys.modules["server.jobs.cutout"]
input_path = self.storage_root / "input.png"
input_path.write_bytes(b"selection")
context = SimpleNamespace(
directory=self.storage_root / "job",
progress=lambda *_args: None,
check_cancelled=lambda: None,
)
depth_texture = context.directory / "depth.exr"
metadata = context.directory / "depth.json"
normal = context.directory / "object-normal.png"
with patch.object(
job,
"generate_moge2_artifacts",
return_value={
"depth": depth_texture,
"depth_metadata": metadata,
"object_normal": normal,
},
) as generate:
result = job.run(
context,
{
"input": str(input_path),
"generate_depth": True,
"normal_mode": "OBJECT",
},
)
self.assertEqual(
result,
{
"depth": "depth.exr",
"depth_metadata": "depth.json",
"object_normal": "object-normal.png",
},
)
generate.assert_called_once_with(
context,
{
"input": str(input_path),
"generate_depth": True,
"normal_mode": "OBJECT",
},
input_path,
generate_depth=True,
normal_mode="OBJECT",
correct_edge_depth=True,
alpha_threshold=0.9,
)