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Add tests and implement boundary smoothing and cutout functionality

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- Introduced tests for boundary smoothing in `test_boundary_smoothing.py`, verifying that smoothing reduces stair-step artifacts while preserving boundary integrity.
- Added tests for cutout boundary behavior in `test_cutout_boundary.py`, ensuring proper handling of boundary triangles and normal blending.
- Created `test_temporary_attributes.py` to check the cleanup of temporary attributes across depth modifier branches, ensuring no warnings are raised.
- Implemented point culling functionality in `test_validity.py`, confirming that invalid points are removed without affecting adjacent geometry.
- Developed boundary smoothing logic in `boundary_smoothing.py`, allowing for depth smoothing while maintaining edge integrity.
- Added cutout boundary management in `cutout_boundary.py`, including functions for removing boundary triangles and tapering thickness profiles.
- Implemented validity checks in `validity.py` to ensure proper deletion of invalid vertices and associated wire edges.
This commit is contained in:
马南
2026-09-11 20:37:20 +08:00
parent e8129fe495
commit 31074bd511
85 changed files with 2501 additions and 1451 deletions
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BIN
src/anyimage/assets/O_AnyImage.blend LFS
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29
src/anyimage/operators/clipboard_image/actions.py
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@@ -6,7 +6,7 @@ import bpy
from ...common.material import create_image_material
from ...common.color_image import material_color_image
from ...common.image import image_pixels
from ...common.image import cleanup_image_input, image_pixels, save_packed_image
CLIPBOARD_HASH_PROPERTY = "anyimage_clipboard_sha256"
CLIPBOARD_CONTENT_PROPERTY = "anyimage_clipboard_content_sha256"
@@ -49,6 +49,10 @@ class PasteTargetError(RuntimeError):
pass
class BrushPreviewError(RuntimeError):
pass
def target_for_context(context):
area = getattr(context, "area", None)
area_type = getattr(area, "type", None)
@@ -367,10 +371,31 @@ def set_tool_texture(context, image):
raise PasteTargetError(
f"The active brush could not use the image texture: {error}"
) from error
_redraw_area(context)
try:
if getattr(context, "mode", "") == "PAINT_TEXTURE":
_set_brush_preview(context, brush, image)
finally:
_redraw_area(context)
return texture
def _set_brush_preview(context, brush, image):
preview_path = None
try:
preview_path = save_packed_image(image, context.scene)
with context.temp_override(id=brush):
result = bpy.ops.ed.lib_id_load_custom_preview(filepath=str(preview_path))
if result != {"FINISHED"}:
raise RuntimeError("Blender did not load the custom preview")
except (OSError, RuntimeError, ValueError) as error:
raise BrushPreviewError(
f"Texture pasted, but the brush preview could not be updated: {error}"
) from error
finally:
if preview_path is not None:
cleanup_image_input(preview_path, True)
def _set_unbiased_paint_color(context, brush):
if getattr(context, "mode", "") not in WHITE_BRUSH_COLOR_MODES:
return

4
src/anyimage/operators/clipboard_image/operators.py
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@@ -3,6 +3,7 @@ import sys
import bpy
from .actions import (
BrushPreviewError,
PasteTargetError,
acquire_packed_image,
paste_image,
@@ -134,6 +135,9 @@ class PasteClipboardImage(bpy.types.Operator):
import_as=self.import_as,
shadeless=self.shadeless,
)
except BrushPreviewError as error:
self.report({"WARNING"}, str(error))
return {"FINISHED"}
except (OSError, RuntimeError, PasteTargetError) as error:
if image is not None and not image_reused and image.users == 0:
bpy.data.images.remove(image)

2
src/anyimage/operators/convert_to_panorama/object.py
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@@ -35,7 +35,7 @@ def create_panorama_from_result(context, result, operator):
try:
with material_color_image(input_path=operator.color_path) as color:
metadata = load_panorama_metadata(result.file("depth_metadata"))
group = load_node_group("O Image Depth Panorama")
group = load_node_group("O Image Depth Panorama", asset_revision=14)
depth = load_depth_result_image(result.file("depth"), source, metadata)
material = create_image_material(source.data, color, shadeless=True, scene=context.scene,
texture_extension="REPEAT")

2
src/anyimage/operators/convert_to_plane/object.py
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@@ -62,7 +62,7 @@ def create_depth_plane_object(
node_group = load_node_group({
"DEPTH": "O Image Depth Plane",
"RELIEF": "O Image Relief Plane",
}[plane_type])
}[plane_type], asset_revision=14 if plane_type == "DEPTH" else None)
source_name = source_object.name
bounds = image_empty_bounds(source_object)
mesh = create_image_plane_mesh(source_name, bounds)

2
src/anyimage/operators/cutout_tool/object.py
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@@ -99,7 +99,7 @@ def _assign_float_point_attribute(mesh, name, values):
def load_cutout_node_group(shape):
return load_node_group(CUTOUT_NODE_GROUP_NAMES[shape], asset_revision=11)
return load_node_group(CUTOUT_NODE_GROUP_NAMES[shape], asset_revision=18 if shape == "DEPTH_SOLID" else 11)
def _connect_cutout_normal_scale(material):

8
src/anyimage/preferences.py
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@@ -26,13 +26,13 @@ MAX_FRAME_RESOLUTION = 8192
ADDON_PACKAGE = __package__
DEFAULT_STORAGE_ROOT = Path.home() / ".anyimage"
UPSCALE_MODEL_ITEMS = tuple(
(model.key, model.label, model.description, number)
for model, number in zip(UPSCALE_MODELS.values(), (0, 2, 4))
(model.key, f"{tier} | {model.label}", model.description, number)
for model, tier, number in zip(UPSCALE_MODELS.values(), ("Fast", "Base", "Pro"), (0, 2, 4))
)
BACKGROUND_MODEL_ITEMS = tuple(
(model.key, model.label, model.description, number)
for model, number in zip(BACKGROUND_MODELS.values(), (1, 0, 2))
(model.key, f"{tier} | {model.label}", model.description, number)
for model, tier, number in zip(BACKGROUND_MODELS.values(), ("Fast", "Base", "Pro"), (1, 0, 2))
)
BALLOON_PROFILE_ALGORITHM_ITEMS = (

4
src/anyimage/properties.py
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@@ -122,11 +122,11 @@ def _model_items(models):
return [
(
model["key"],
model["label"],
f"{tier} | {model['label']}",
f"{model['description']}; license: {model['license']}",
numbers[model["key"]],
)
for model in models
for model, tier in zip(models, ("Fast", "Base", "Pro"))
]

79
src/anyimage/server/geometry/edge_depth.py
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@@ -1,79 +0,0 @@
"""Extend reliable depth along each visible component's silhouette."""
from dataclasses import replace
def extend_edge_depth(frame, alpha, alpha_threshold=0.9):
"""Return edge-corrected geometry while preserving reliable camera points."""
import numpy as np
from scipy import ndimage
from ..models.onnx_moge2 import depth_to_points
depth = frame.depth
alpha = np.asarray(alpha, dtype=np.float32)
if alpha.shape != depth.shape:
raise ValueError("Edge Alpha must match the depth dimensions")
if np.all(alpha == 1.0):
return frame
visible = (alpha > 0.0) & (alpha >= alpha_threshold)
opaque = visible & (alpha >= 0.95)
candidates = (
opaque
& (frame.validity > 0.5)
& np.isfinite(depth)
& (depth > 0.0)
)
if not candidates.any():
return frame
interior_distance = ndimage.distance_transform_edt(
np.pad(opaque, 3, mode="edge")
)[3:-3, 3:-3]
interior = opaque & (interior_distance > 2.0)
core = candidates & interior
del interior_distance
labels, _ = ndimage.label(visible, structure=np.ones((3, 3), dtype=bool))
corrected = depth.copy()
background_distance = np.full(depth.shape, np.inf, dtype=np.float32)
for component_id, bounds in enumerate(ndimage.find_objects(labels), start=1):
region = tuple(
slice(max(0, bound.start - 7), min(size, bound.stop + 7))
for bound, size in zip(bounds, depth.shape)
)
component = labels[region] == component_id
donors = core[region] & component
if not donors.any():
donors = candidates[region] & component
if not donors.any():
continue
indices = ndimage.distance_transform_edt(
~donors, return_distances=False, return_indices=True
)
extended = depth[region][tuple(indices)]
smoothed = ndimage.gaussian_filter(extended, sigma=0.8, radius=3)
distance = ndimage.distance_transform_edt(~component)
background = (
~visible[region]
& (distance <= 4.0)
& (distance < background_distance[region])
)
target = (component & ~interior[region] & ~donors) | background
corrected[region][target] = smoothed[target]
background_distance[region][background] = distance[background]
changed = corrected != depth
if not changed.any():
return frame
points = frame.points
if points is not None:
height, width = depth.shape
intrinsics = frame.intrinsics.copy()
intrinsics[0] /= width
intrinsics[1] /= height
projected = depth_to_points(corrected, intrinsics)
points = points.copy()
points[changed] = projected[changed]
return replace(frame, depth=corrected, points=points)

6
src/anyimage/server/geometry/prediction_artifacts.py
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@@ -8,7 +8,6 @@ from .depth_texture import (
write_depth_texture,
)
from .normal_texture import write_camera_normal_texture
from .edge_depth import extend_edge_depth
def _limited_model_input(source_path, output_path, max_input_size):
@@ -79,12 +78,11 @@ def generate_moge_artifacts(
if generate_depth:
context.progress(0.45, "Generating depth texture")
alpha = _image_alpha(input_path, frame.depth.shape)
depth_frame = extend_edge_depth(frame, alpha, alpha_threshold)
result["depth"] = write_depth_texture(
depth_frame, context.directory / "depth.exr", alpha=alpha,
frame, context.directory / "depth.exr", alpha=alpha,
)
result["depth_metadata"] = write_depth_metadata(
depth_frame,
frame,
(alpha > 0.0) & (alpha >= alpha_threshold),
context.directory / "depth.json",
)

18
src/anyimage/server/model_catalog.py
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@@ -18,7 +18,7 @@ class ModelSpec:
BIREFNET_LITE = ModelSpec(
key="BIREFNET_LITE",
label="Fast | BiRefNet Lite",
label="BiRefNet Lite",
directory_name="birefnet-lite",
repository="ZhengPeng7/BiRefNet_lite",
license_name="MIT",
@@ -35,7 +35,7 @@ BIREFNET_LITE = ModelSpec(
BEN2_MODEL = ModelSpec(
key="BEN2_BASE",
label="General | BEN2 Base",
label="BEN2 Base",
directory_name="BEN2-ONNX",
repository="onnx-community/BEN2-ONNX",
license_name="Apache 2.0",
@@ -54,7 +54,7 @@ BEN2_MODEL = ModelSpec(
REALESRGAN_GENERAL_WDN_X4V3 = ModelSpec(
key="REALESRGAN_GENERAL_WDN_X4V3",
label="Fast | Real-ESRGAN General WDN x4v3",
label="Real-ESRGAN General WDN x4v3",
directory_name="realesr-general-wdn-x4v3",
repository="xinntao/Real-ESRGAN",
license_name="BSD 3-Clause",
@@ -72,7 +72,7 @@ REALESRGAN_GENERAL_WDN_X4V3 = ModelSpec(
REALESRGAN_X4PLUS = ModelSpec(
key="REALESRGAN_X4PLUS",
label="General | Real-ESRGAN x4plus",
label="Real-ESRGAN x4plus",
directory_name="realesrgan-x4plus",
repository="jonathanst29/tinier-upscale-models",
license_name="BSD 3-Clause",
@@ -93,7 +93,7 @@ REALESRGAN_X4PLUS = ModelSpec(
HAT_GAN_X4_SHARPER = ModelSpec(
key="HAT_GAN_X4_SHARPER",
label="Detailed | HAT Sharper",
label="HAT Sharper",
directory_name="hat-gan-x4-sharper",
repository="XPixelGroup/HAT",
license_name="Apache 2.0",
@@ -124,7 +124,7 @@ DEFAULT_UPSCALE_MODEL_KEY = REALESRGAN_GENERAL_WDN_X4V3.key
MOGE2_MODELS = {
"MOGE2_VITS_NORMAL": ModelSpec(
key="MOGE2_VITS_NORMAL",
label="Fast | MoGe-2 ViT-S Normal",
label="MoGe-2 ViT-S Normal",
directory_name="moge-2-vits-normal-onnx",
repository="Ruicheng/moge-2-vits-normal-onnx",
license_name="MIT",
@@ -141,7 +141,7 @@ MOGE2_MODELS = {
),
"MOGE2_VITB_NORMAL": ModelSpec(
key="MOGE2_VITB_NORMAL",
label="Balanced | MoGe-2 ViT-B Normal",
label="MoGe-2 ViT-B Normal",
directory_name="moge-2-vitb-normal-onnx",
repository="Ruicheng/moge-2-vitb-normal-onnx",
license_name="MIT",
@@ -159,7 +159,7 @@ MOGE2_MODELS = {
}
MOGE3_VITL = ModelSpec(
key="MOGE3_VITL",
label="Detailed | MoGe-3 ViT-L",
label="MoGe-3 ViT-L",
directory_name="moge-3-vitl-onnx",
repository="Ruicheng/moge-3-vitl",
license_name="MIT",
@@ -176,7 +176,7 @@ MOGE3_VITL = ModelSpec(
MOGE_MODELS = {**MOGE2_MODELS, MOGE3_VITL.key: MOGE3_VITL}
BIREFNET_HR_MATTING = ModelSpec(
key="BIREFNET_HR_MATTING",
label="Detailed | BiRefNet HR-matting (CPU)",
label="BiRefNet HR-matting (CPU)",
directory_name="birefnet-hr-matting",
repository="ZhengPeng7/BiRefNet_HR-matting",
license_name="MIT",