ausboss
db7535751d
The image and clip transform nodes could resize their output to a pixel budget; the frame picker, whose single frame often feeds an image or video model, could not. It takes the same appended resize inputs, off by default, and its face and editor show them like the other two.
222 lines
7.9 KiB
Python
222 lines
7.9 KiB
Python
"""Stable V1 widget definitions shared by the three Crop + Rotate + Pad nodes."""
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from __future__ import annotations
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import json
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import re
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from pathlib import Path
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from ._execution_helpers import warn_once
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from ._transform_engine import TransformSpec
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ASPECT_RATIOS = ["free", "source", "1:1", "9:16", "16:9", "2:3", "3:2", "3:4", "4:3", "9:21", "21:9"]
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# Optional user presets: copy ausboss_presets_example.json (repo root) to
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# ausboss_presets.json (gitignored) and edit. Read fresh at INPUT_TYPES time,
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# so a browser reload picks up edits. Any problem warns once (ASCII) and
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# falls back to the built-in list - never breaks node registration.
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PRESETS_PATH = Path(__file__).resolve().parent.parent / "ausboss_presets.json"
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_RATIO_PATTERN = re.compile(r"^[1-9]\d*:[1-9]\d*$")
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# Preset warnings quote what the user wrote, so the set is capped at this
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# many notes rather than kept for the whole session.
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_warned_presets: set[str] = set()
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_PRESET_WARNING_LIMIT = 64
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def load_custom_aspect_ratios(path: Path | None = None) -> list[str]:
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"""Extra crop_aspect_ratio entries from the optional presets file."""
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path = PRESETS_PATH if path is None else Path(path)
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try:
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text = path.read_text(encoding="utf-8")
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except FileNotFoundError:
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return []
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except OSError as exc:
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warn_once(
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f"Presets: could not read {path.name}: {exc}",
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_warned_presets, limit=_PRESET_WARNING_LIMIT,
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)
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return []
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try:
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data = json.loads(text)
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except json.JSONDecodeError as exc:
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warn_once(
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f"Presets: {path.name} is not valid JSON ({exc}); using built-in aspect ratios.",
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_warned_presets, limit=_PRESET_WARNING_LIMIT,
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)
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return []
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entries = data.get("crop_aspect_ratios") if isinstance(data, dict) else None
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if not isinstance(entries, list):
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warn_once(
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f"Presets: {path.name} needs a crop_aspect_ratios list; using built-in aspect ratios.",
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_warned_presets, limit=_PRESET_WARNING_LIMIT,
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)
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return []
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valid: list[str] = []
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skipped: list[str] = []
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for entry in entries:
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candidate = str(entry).strip()
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if _RATIO_PATTERN.match(candidate) or candidate in ("free", "source"):
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if candidate not in valid:
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valid.append(candidate)
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else:
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skipped.append(candidate)
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if skipped:
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safe = ", ".join(item.encode("ascii", "backslashreplace").decode("ascii") for item in skipped)
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warn_once(
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f"Presets: skipped entries that are not W:H integer pairs: {safe}",
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_warned_presets, limit=_PRESET_WARNING_LIMIT,
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)
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return valid
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def aspect_ratio_options(path: Path | None = None) -> list[str]:
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"""Built-in ratios extended with any user presets, order preserved."""
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options = list(ASPECT_RATIOS)
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for entry in load_custom_aspect_ratios(path):
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if entry not in options:
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options.append(entry)
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return options
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def transform_inputs(*, feather: int = 24, fill_color: str = "#808080") -> dict[str, tuple]:
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"""The shared rotate/crop/pad widgets. ``feather`` and ``fill_color`` are
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the defaults a fresh node starts with: the image nodes keep the soft grey
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canvas inpaint models like, the clip node asks for black and a hard edge.
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"""
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return {
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"rotation_degrees": (
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"FLOAT",
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{
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"default": 0.0,
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"min": -180.0,
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"max": 180.0,
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"step": 0.1,
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"tooltip": "Clockwise rotation applied before crop and padding.",
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},
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),
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"crop_aspect_ratio": (
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aspect_ratio_options(),
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{"default": "free", "tooltip": "Locks crop handles to a ratio; free allows any rectangle."},
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),
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"crop_x": (
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"INT",
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{"default": 0, "min": 0, "max": 65536, "step": 1, "tooltip": "Left edge of the crop in pixels, measured on the rotated image."},
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),
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"crop_y": (
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"INT",
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{"default": 0, "min": 0, "max": 65536, "step": 1, "tooltip": "Top edge of the crop in pixels, measured on the rotated image."},
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),
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"crop_width": (
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"INT",
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{"default": 0, "min": 0, "max": 65536, "step": 1, "tooltip": "0 keeps the full available width."},
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),
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"crop_height": (
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"INT",
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{"default": 0, "min": 0, "max": 65536, "step": 1, "tooltip": "0 keeps the full available height."},
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),
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"pad_left": (
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"INT",
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{"default": 0, "min": 0, "max": 32768, "step": 1, "tooltip": "Fill-color pixels added on the left; padding lands in the output mask."},
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),
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"pad_top": (
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"INT",
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{"default": 0, "min": 0, "max": 32768, "step": 1, "tooltip": "Fill-color pixels added on top; padding lands in the output mask."},
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),
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"pad_right": (
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"INT",
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{"default": 0, "min": 0, "max": 32768, "step": 1, "tooltip": "Fill-color pixels added on the right; padding lands in the output mask."},
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),
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"pad_bottom": (
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"INT",
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{"default": 0, "min": 0, "max": 32768, "step": 1, "tooltip": "Fill-color pixels added on the bottom; padding lands in the output mask."},
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),
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"feather": (
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"INT",
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{
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"default": int(feather),
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"min": 0,
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"max": 4096,
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"step": 1,
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"tooltip": "Feathers the mask into kept pixels and fades the image edge into the fill color.",
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},
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),
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"canvas_multiple": (
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"INT",
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{
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"default": 1,
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"min": 1,
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"max": 4096,
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"step": 1,
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"tooltip": "Rounds output up by adding the minimum extra pixels to right and bottom.",
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},
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),
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"fill_color": (
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"STRING",
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{
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"default": str(fill_color),
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"tooltip": (
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"Color for rotation voids and padding; accepts #RGB/#RRGGBB hex, "
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"R, G, B (0-255 or 0..1 floats), one grayscale number, or a CSS "
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"color name. Unparseable values fall back to mid-gray."
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),
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},
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),
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}
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# Every transform node, appended after its other widgets: resize the
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# transformed output to a pixel budget, core ImageScaleToTotalPixels-style.
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RESIZE_METHODS = ["lanczos", "area", "bicubic", "bilinear", "nearest-exact"]
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def resize_inputs() -> dict[str, tuple]:
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return {
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"resize_to_megapixels": (
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"BOOLEAN",
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{
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"default": False,
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"tooltip": "Resize the output to the megapixel budget below, aspect preserved.",
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},
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),
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"megapixels": (
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"FLOAT",
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{
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"default": 1.0,
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"min": 0.01,
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"max": 16.0,
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"step": 0.01,
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"tooltip": (
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"Output pixel budget in megapixels (x 1024x1024, matching "
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"the core Scale Image to Total Pixels node)."
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),
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},
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),
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"resize_method": (
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RESIZE_METHODS,
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{
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"default": "lanczos",
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"tooltip": "Sampling filter for the resize; lanczos is the sharp default.",
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},
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),
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"resolution_steps": (
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"INT",
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{
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"default": 1,
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"min": 1,
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"max": 256,
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"tooltip": (
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"Rounds each resized dimension to a multiple of this - "
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"8 or 64 keeps VAE-friendly sizes."
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),
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},
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),
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}
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def spec_from_values(**values) -> TransformSpec:
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names = TransformSpec.__dataclass_fields__.keys()
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return TransformSpec(**{name: values[name] for name in names if name in values}).normalized()
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