icrdr/AnyImage
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Refactor Cutout Tool to Use World Space Edge Length

Browse Source 
- Replaced the Mesh Detail parameter with a new Edge Length property to define cutout sampling in physical units.
- Introduced Minimum Relative Edge Length preference to control effective spacing based on the bounding box of the cutout content.
- Updated tests to validate the new edge length functionality and ensure consistent behavior across different resolutions and canvas sizes.
- Removed deprecated parameters and adjusted related properties to align with the new edge length implementation.
- Enhanced geometry sampling logic to utilize effective world spacing for both standard and fine outline modes.
This commit is contained in:
马南
2026-09-12 23:03:24 +08:00
parent 938d95db0f
commit 18799e8828
28 changed files with 505 additions and 279 deletions
Download Patch File Download Diff File Expand all files Collapse all files

34
src/anyimage/operators/cutout_tool/fine_mesh.py
View File

@@ -78,7 +78,7 @@ def support_flat_regions(points, faces):
return np.asarray(vertices), np.asarray(triangles, dtype=np.int32)
def build_fine_mesh(alpha, spacing, threshold):
def build_fine_mesh(alpha, spacing, threshold, *, pixel_transform=None):
"""Return pixel-space triangles and component ranges for height solving."""
alpha = np.asarray(alpha, dtype=float)
if alpha.ndim != 2 or not alpha.size or not np.isfinite(alpha).all():
@@ -92,18 +92,24 @@ def build_fine_mesh(alpha, spacing, threshold):
reference = g.extract_selection_contours(
filtered, max_resolution=max(mask.shape), threshold=threshold
)
width_sizes = WidthSamples(mask)
# Normalize geometric tolerances and support sampling to the target length.
transform = (
np.eye(2) if pixel_transform is None else np.asarray(pixel_transform)
) * (32 / spacing)
inverse = np.linalg.inv(transform)
width_sizes = WidthSamples(mask, transform=transform)
spacing = 32.0
points, faces, components = [], [], []
offset = 0
for component in reference.components:
contours = contours_for_component(component, spacing)
contours = contours_for_component([np.asarray(c) @ transform for c in component], spacing)
spine, path_edges = interior_paths(
contours, min(32, max(mask.shape) / 6), width_sizes
contours, spacing, width_sizes
)
contours, spine, path_edges = subdivide_constraints(
contours, spine, path_edges, spacing
)
free = relax_points(contours, spine, mask.shape, spacing)
free = relax_points(contours, spine, spacing)
vertices, triangles, constraints = triangulate(
contours, spine, path_edges, free, spacing
)
@@ -117,9 +123,9 @@ def build_fine_mesh(alpha, spacing, threshold):
raise ValueError(
"Fine Outline placed an interior constraint on the boundary"
)
points.append(vertices)
points.append(vertices @ inverse)
faces.append(triangles + offset)
components.append((offset, offset + len(vertices), triangles, contours[0]))
components.append((offset, offset + len(vertices), triangles, contours[0] @ inverse))
offset += len(vertices)
points, faces = np.concatenate(points), np.concatenate(faces)
return points, faces, g.boundary_vertices_from_faces(len(points), faces), components
@@ -181,7 +187,10 @@ def width_ridge_samples(image):
class WidthSamples:
"""Estimate local width from indexed distance-ridge disks."""
def __init__(self, mask):
def __init__(self, mask, transform=None):
transform = np.eye(2) if transform is None else transform
self.inverse = np.linalg.inv(transform)
self.size_scale = np.linalg.svd(transform, compute_uv=False).min()
ridge, distance = width_ridge_samples(np.pad(mask, 1))
ridge = ridge[1:-1, 1:-1]
self.distance = np.maximum(distance[1:-1, 1:-1] - 0.5, 0.3)
@@ -198,6 +207,7 @@ class WidthSamples:
)
def __call__(self, points):
points = points @ self.inverse
radius = np.full(len(points), 0.5)
pending = np.arange(len(points))
for ids, tree, reach in self.groups:
@@ -226,7 +236,7 @@ class WidthSamples:
mode="nearest",
)
return np.maximum(
0.7, np.minimum(32, np.minimum(16, radius * 0.9) + 0.4 * distance)
0.7, np.minimum(32, np.minimum(16, radius * self.size_scale * 0.9) + 0.4 * distance * self.size_scale)
)
@@ -486,7 +496,7 @@ def interior_paths(contours, spacing, width_sizes):
return (np.asarray(points).reshape(-1, 2), edges)
def relax_points(contours, spine, shape, spacing):
def relax_points(contours, spine, spacing):
free = g.uniform_interior_points_for_contours(contours, spacing)
if len(free) and len(spine):
free = free[cKDTree(spine).query(free)[0] > spacing * 0.55]
@@ -495,8 +505,8 @@ def relax_points(contours, spine, shape, spacing):
points = np.concatenate(contours)
minimum = points.min(axis=0)
maximum = points.max(axis=0)
xx = np.arange(phase, shape[1], step) + 0.5
yy = np.arange(phase, shape[0], step) + 0.5
xx = np.arange(minimum[0] + phase, maximum[0], step) + 0.5
yy = np.arange(minimum[1] + phase, maximum[1], step) + 0.5
xx = xx[(xx >= minimum[0]) & (xx <= maximum[0])]
yy = yy[(yy >= minimum[1]) & (yy <= maximum[1])]
xx, yy = np.meshgrid(xx, yy)

71
src/anyimage/operators/cutout_tool/geometry.py
View File

@@ -3,7 +3,7 @@
import math
from dataclasses import dataclass
from ...preferences import addon_preferences
from ...preferences import addon_preferences, configured_min_cutout_relative_edge_length
from ...common.image import image_empty_bounds
from . import balloon
@@ -824,11 +824,9 @@ def crop_plane_bounds(source_object, crop_bounds, source_size):
def extract_cutout_contours(
content_values,
point_spacing,
sampling_resolution,
threshold=CUTOUT_ALPHA_THRESHOLD,
):
height, width = content_values.shape
sampling_resolution = max(width, height) / float(point_spacing)
contour_resolution = max(512, min(round(sampling_resolution * 8), 1024))
return extract_selection_contours(
content_values,
@@ -837,28 +835,28 @@ def extract_cutout_contours(
)
def limit_cutout_point_spacing(point_spacing, crop_size, max_mesh_resolution):
crop_width, crop_height = (int(value) for value in crop_size)
spacing = float(point_spacing)
if crop_width <= 0 or crop_height <= 0:
raise ValueError("The Cutout bounds must be positive")
if spacing <= 0.0:
raise ValueError("Cutout point spacing must be greater than zero")
maximum = int(max_mesh_resolution)
if maximum <= 0:
raise ValueError("Maximum Cutout mesh resolution must be positive")
return max(spacing, max(crop_width, crop_height) / maximum)
def effective_cutout_edge_length(
context, source_object, edge_length, content_values, content_bounds,
threshold=CUTOUT_ALPHA_THRESHOLD,
):
"""Resolve target spacing in Blender world units from visible content bounds."""
import numpy as np
def cutout_sampling_spacing(source_object, point_spacing):
import math
x_min, x_max, y_min, y_max = image_empty_bounds(source_object)
metric, _world_z_scale = world_plane_metric(source_object.matrix_world)
width = (x_max - x_min) * math.sqrt(max(metric[0][0], 0.0))
height = (y_max - y_min) * math.sqrt(max(metric[1][1], 0.0))
image_width, image_height = (int(value) for value in source_object.data.size)
return max(width / image_width, height / image_height) * float(point_spacing)
if not math.isfinite(edge_length) or edge_length <= 0:
raise ValueError("Cutout edge length must be greater than zero")
values = np.asarray(content_values)
visible = (values > 0) & (values >= threshold)
rows = np.flatnonzero(visible.any(axis=1))
columns = np.flatnonzero(visible.any(axis=0))
if not len(rows):
raise ValueError("The Cutout selection contains no visible image pixels")
bounds = crop_plane_bounds(source_object, content_bounds, tuple(source_object.data.size))
metric, _ = world_plane_metric(source_object.matrix_world)
metric_transform(metric)
width = (bounds[1] - bounds[0]) * (columns.max() + 1 - columns.min()) / values.shape[1]
height = (bounds[3] - bounds[2]) * (rows.max() + 1 - rows.min()) / values.shape[0]
longest = max(width * math.sqrt(metric[0][0]), height * math.sqrt(metric[1][1]))
return max(float(edge_length), longest * configured_min_cutout_relative_edge_length(context))
def selection_calibration(content_values, target_shape, threshold=CUTOUT_ALPHA_THRESHOLD):
@@ -885,7 +883,7 @@ def selection_calibration(content_values, target_shape, threshold=CUTOUT_ALPHA_T
def build_base_shape(
context,
source_object,
point_spacing,
edge_length,
content_values,
content_bounds,
*,
@@ -899,31 +897,38 @@ def build_base_shape(
content_bounds,
tuple(source_object.data.size),
)
world_metric, world_z_scale = world_plane_metric(source_object.matrix_world)
if world_z_scale <= 1e-10:
raise ValueError("The Image Empty has a degenerate world transform")
pixel_transform = np.diag((
(bounds[1] - bounds[0]) / content_values.shape[1],
-(bounds[3] - bounds[2]) / content_values.shape[0],
)) @ metric_transform(world_metric)
longest = max(
np.linalg.norm(pixel_transform[0]) * content_values.shape[1],
np.linalg.norm(pixel_transform[1]) * content_values.shape[0],
)
fine_mesh = None
selection_contours = None
if fine_outline:
from .fine_mesh import build_fine_mesh
fine_mesh = (
*build_fine_mesh(content_values, point_spacing, alpha_threshold),
*build_fine_mesh(content_values, edge_length, alpha_threshold, pixel_transform=pixel_transform),
(content_values.shape[1], content_values.shape[0]),
)
else:
selection_contours = extract_cutout_contours(
content_values,
point_spacing,
longest / edge_length,
threshold=alpha_threshold,
)
world_metric, world_z_scale = world_plane_metric(source_object.matrix_world)
if world_z_scale <= 1e-10:
raise ValueError("The Image Empty has a degenerate world transform")
preferences = addon_preferences(context)
balloon_algorithm = getattr(preferences, "balloon_profile_algorithm", "POISSON")
point_spacing = cutout_sampling_spacing(source_object, point_spacing)
domain = cutout_domain(
selection_contours,
bounds,
point_spacing,
edge_length,
world_metric,
balloon_algorithm,
fine_mesh=fine_mesh,

19
src/anyimage/operators/cutout_tool/interaction.py
View File

@@ -10,17 +10,6 @@ CUTOUT_SHAPE_BUTTONS = (
("DEPTH_SOLID", "SURFACE_NCURVE"),
)
CUTOUT_MESH_DETAIL_SPACING = {
"LOW": 32,
"MEDIUM": 16,
"HIGH": 8,
"ULTRA": 4,
}
def cutout_mesh_detail_spacing(mesh_detail):
return CUTOUT_MESH_DETAIL_SPACING[str(mesh_detail)]
def _pie_button(
pie,
@@ -30,7 +19,7 @@ def _pie_button(
source_name,
selection_path_json,
generate_normal,
point_spacing,
edge_length,
alpha_threshold,
fine_outline,
gesture,
@@ -44,7 +33,7 @@ def _pie_button(
operator.selection_path_json = selection_path_json
operator.shape = shape
operator.generate_normal = generate_normal
operator.point_spacing = point_spacing
operator.edge_length = edge_length
operator.alpha_threshold = alpha_threshold
operator.fine_outline = fine_outline
operator.gesture = gesture
@@ -61,7 +50,7 @@ def open_shape_pie(
source_name = source_object.name
selection_path_json = selection_path.to_json()
settings = context.scene.anyimage_settings
point_spacing = cutout_mesh_detail_spacing(settings.cutout_mesh_detail)
edge_length = settings.cutout_edge_length
ready = ai_ready()
generate_normal = ready and bool(
getattr(settings, "cutout_generate_normal", False)
@@ -81,7 +70,7 @@ def open_shape_pie(
source_name,
selection_path_json,
generate_normal,
point_spacing,
edge_length,
alpha_threshold,
fine_outline,
gesture,

5
src/anyimage/operators/cutout_tool/object.py
View File

@@ -26,7 +26,6 @@ from .geometry import (
CUTOUT_ALPHA_THRESHOLD,
crop_plane_bounds,
cutout_cleanup_value,
cutout_sampling_spacing,
selection_calibration,
world_plane_metric,
)
@@ -98,7 +97,7 @@ def create_shape_object(
context,
source_object,
shape,
point_spacing,
edge_length,
content_values,
content_bounds,
base_shape,
@@ -125,7 +124,7 @@ def create_shape_object(
)
world_metric, _world_z_scale = world_plane_metric(source_object.matrix_world)
cleanup_value = cutout_cleanup_value(
cutout_sampling_spacing(source_object, point_spacing),
edge_length,
world_metric,
)
material = None

42
src/anyimage/operators/cutout_tool/operators.py
View File

@@ -8,12 +8,12 @@ from ...preferences import (
addon_preferences,
configured_geometry_model,
configured_max_ai_input_size,
configured_max_cutout_mesh_resolution,
)
from ...properties import (
cutout_alpha_threshold_property,
cutout_fine_outline_property,
cutout_gesture_property,
cutout_edge_length_property,
)
from ...runtime import JobOperatorBase
from ...server.model_catalog import DEFAULT_GEOMETRY_MODEL_KEY
@@ -59,7 +59,7 @@ from ...common.selection import (
from .geometry import (
CUTOUT_ALPHA_THRESHOLD,
build_base_shape,
limit_cutout_point_spacing,
effective_cutout_edge_length,
)
from .interaction import open_shape_pie
from .object import (
@@ -89,7 +89,7 @@ def create_cutout_shape(
context,
source_object,
shape,
point_spacing,
edge_length,
content_values,
content_bounds,
*,
@@ -101,11 +101,22 @@ def create_cutout_shape(
normal_mode=NormalMode.NONE,
color_image,
gesture="LASSO",
report=None,
):
effective_length = effective_cutout_edge_length(
context, source_object, edge_length, content_values, content_bounds, alpha_threshold
)
if report is not None and effective_length > edge_length * (1 + 1e-6):
units = context.scene.unit_settings
label = bpy.utils.units.to_string(
units.system if units.system != "NONE" else "METRIC", "LENGTH",
effective_length * units.scale_length, precision=4,
)
report({"INFO"}, f"Effective Edge Length: {label}")
base_shape = build_base_shape(
context,
source_object,
point_spacing,
effective_length,
content_values,
content_bounds,
alpha_threshold=alpha_threshold,
@@ -115,7 +126,7 @@ def create_cutout_shape(
context,
source_object,
shape,
point_spacing,
effective_length,
content_values,
content_bounds,
base_shape,
@@ -191,11 +202,7 @@ class CutoutSelectionToShape(JobOperatorBase, bpy.types.Operator):
selection_bounds_json: bpy.props.StringProperty(options=_HIDDEN)
shape: bpy.props.StringProperty(default="SOLID", options=_HIDDEN)
gesture: bpy.props.StringProperty(default="LASSO", options=_HIDDEN)
point_spacing: bpy.props.FloatProperty(
default=32.0,
min=0.01,
options=_HIDDEN,
)
edge_length: cutout_edge_length_property(options=_HIDDEN)
model: bpy.props.StringProperty(
default=DEFAULT_GEOMETRY_MODEL_KEY,
options=_HIDDEN,
@@ -234,13 +241,6 @@ class CutoutSelectionToShape(JobOperatorBase, bpy.types.Operator):
source_rgba = image_rgba(source_object.data)
context.view_layer.objects.active = source_object
source_object.select_set(True)
crop_width = selection_mask.bounds[2] - selection_mask.bounds[0]
crop_height = selection_mask.bounds[3] - selection_mask.bounds[1]
self.point_spacing = limit_cutout_point_spacing(
self.point_spacing,
(crop_width, crop_height),
configured_max_cutout_mesh_resolution(context),
)
self.max_ai_input_size = configured_max_ai_input_size(context)
if not self._needs_generation():
left, top, right, bottom = selection_mask.bounds
@@ -251,11 +251,12 @@ class CutoutSelectionToShape(JobOperatorBase, bpy.types.Operator):
)
with material_color_image(source_object.data, bounds=selection_mask.bounds, rgba=source_rgba) as color_image:
create_cutout_shape(
context, source_object, self.shape, self.point_spacing,
context, source_object, self.shape, self.edge_length,
content_values, selection_mask.bounds,
alpha_threshold=self.alpha_threshold,
fine_outline=self.fine_outline, color_image=color_image,
gesture=self.gesture,
report=self.report,
)
return {"FINISHED"}
setup_result = invoke_ai_setup_if_needed(self)
@@ -354,7 +355,7 @@ class CutoutSelectionToShape(JobOperatorBase, bpy.types.Operator):
context,
source_object,
self.shape,
self.point_spacing,
self.edge_length,
content_values,
content_bounds,
depth_image=depth_image,
@@ -365,6 +366,7 @@ class CutoutSelectionToShape(JobOperatorBase, bpy.types.Operator):
fine_outline=self.fine_outline,
color_image=color_image,
gesture=self.gesture,
report=self.report,
)
except Exception:
if normal_image is not None and normal_image.users == 0:
@@ -460,7 +462,7 @@ class CutoutTool(bpy.types.WorkSpaceTool):
def draw_settings(context, layout, _tool):
settings = context.scene.anyimage_settings
layout.prop(settings, "cutout_gesture")
layout.prop(settings, "cutout_mesh_detail")
layout.prop(settings, "cutout_edge_length")
layout.prop(settings, "cutout_fine_outline")
layout.prop(settings, "cutout_alpha_threshold")
status = draw_ai_setup(layout)