Refactor Cutout and Image Editing Logic

- Renamed "Base Plane Depth" to "Reference Depth" across validate_cutout.py for consistency.
- Introduced a new specification for Cutout mesh sampling to ensure source pixel spacing is preserved and limits are applied correctly.
- Unified naming conventions for image editing results to maintain consistency across Remove Background, Upscale, and Crop operations.
- Updated the handling of Refine Selection to ensure it retains the original bounds and does not apply unnecessary cropping.
- Enhanced material generation logic to connect image color directly to IOR Level, improving the rendering of dark areas.
- Established clear requirements for geometry depth controls and image result materials to ensure consistent behavior across different components.
- Removed outdated logic and ensured all changes are documented and tested for regression.

src/anyimage/operators/cutout_tool/geometry.py

@@ -4,7 +4,6 @@ import math
 from dataclasses import dataclass
 
 from ...preferences import addon_preferences
-from ...server.media.resolution import limited_image_size
 from ...common.image import image_empty_bounds
 
 
@@ -1342,10 +1341,12 @@ def crop_plane_bounds(source_object, crop_bounds, source_size):
 
 def extract_cutout_contours(
     content_values,
-    mesh_resolution,
+    point_spacing,
     threshold=CUTOUT_ALPHA_THRESHOLD,
 ):
-    contour_resolution = max(512, min(int(mesh_resolution) * 8, 1024))
+    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,
         max_resolution=contour_resolution,
@@ -1353,24 +1354,28 @@ def extract_cutout_contours(
     )
 
 
-def limit_cutout_mesh_resolution(mesh_resolution, crop_size, max_input_size):
+def limit_cutout_point_spacing(point_spacing, crop_size, max_mesh_resolution):
     crop_width, crop_height = (int(value) for value in crop_size)
-    limited_width, limited_height = limited_image_size(
-        (crop_width, crop_height),
-        max_input_size,
-    )
-    scale = max(limited_width, limited_height) / max(crop_width, crop_height)
-    return max(4, min(1024, round(int(mesh_resolution) * scale)))
+    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 cutout_sampling_spacing(source_object, mesh_resolution):
+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))
-    return max(width, height) / max(int(mesh_resolution), 8)
+    image_width, image_height = (int(value) for value in source_object.data.size)
+    return max(width / image_width, height / image_height) * float(point_spacing)
 
 
 def selection_calibration(content_values, target_shape, threshold=CUTOUT_ALPHA_THRESHOLD):
@@ -1397,7 +1402,7 @@ def selection_calibration(content_values, target_shape, threshold=CUTOUT_ALPHA_T
 def build_base_shape(
     context,
     source_object,
-    mesh_resolution,
+    point_spacing,
     content_values,
     content_bounds,
 ):
@@ -1410,7 +1415,7 @@ def build_base_shape(
     )
     selection_contours = extract_cutout_contours(
         content_values,
-        mesh_resolution,
+        point_spacing,
         threshold=CUTOUT_ALPHA_THRESHOLD,
     )
     world_metric, world_z_scale = world_plane_metric(source_object.matrix_world)
@@ -1418,7 +1423,7 @@ def build_base_shape(
         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, mesh_resolution)
+    point_spacing = cutout_sampling_spacing(source_object, point_spacing)
     domain = cutout_domain(
         selection_contours,
         bounds,