nodes_upscale extracted
This commit is contained in:
Lex Darlog (DRL)
@@ -3,6 +3,7 @@
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"""
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from .nodes_simple import *
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from .nodes_upscale import *
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NODE_CLASS_MAPPINGS = {
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"BestResolutionFromArea": BestResolutionFromArea,
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+7
-100
@@ -1,6 +1,6 @@
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# encoding: utf-8
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"""
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The actual nodes defined by the package.
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Simple (aka no-upscale) versions of nodes.
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"""
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import typing as _t
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@@ -13,8 +13,6 @@ from frozendict import deepfreeze, frozendict
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from comfy.comfy_types.node_typing import IO as _IO
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from .node_types import *
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from .enums import *
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from ._funcs import (
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aspect_ratios_sorted as _aspect_ratios_sorted,
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number_to_int as _number_to_int,
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@@ -22,9 +20,12 @@ from ._funcs import (
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simple_result_from_approx_wh as _simple_result_from_approx_wh,
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upscale_result_from_approx_wh as _upscale_result_from_approx_wh
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)
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from .enums import *
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from .node_types import *
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# ----------------------------------------------------------
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# Tiny optimization by reusing the same immutable dict:
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# A tiny optimization by reusing the same immutable dict:
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_input_types_simple = deepfreeze({
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'required': {
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'width': (_IO.INT, dict(type_dict_res, **{'tooltip': "Approximate width"})),
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@@ -88,6 +89,7 @@ class BestResolutionSimple:
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unique_id=unique_id, target_square_size=_sqrt(width * height)
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)
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# ----------------------------------------------------------
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_tooltip_aspect = (
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"Two aspects together define an aspect ratio (16:9, 4:3, etc).\n"
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@@ -173,6 +175,7 @@ class BestResolutionFromAspectRatio:
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unique_id=unique_id, target_square_size=_sqrt(width_f * height_f)
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)
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# ----------------------------------------------------------
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_input_types_area = deepfreeze({
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'required': {
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@@ -237,99 +240,3 @@ class BestResolutionFromArea:
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# show,
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unique_id=unique_id, target_square_size=square_size
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)
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_return_types_upscale = (_IO.INT, _IO.INT, _IO.INT, _IO.INT)
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_return_ttips_upscale = frozendict({
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'orig_w': "Width for original image",
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'orig_h': "Height for original image",
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'up_w': "Width for upscaled image",
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'up_h': "Height for upscaled image"
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})
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_return_names_upscale = tuple(_return_ttips_upscale.keys())
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# __priority_type = (_IO.BOOLEAN, {
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# 'default': True, 'label_on': 'upscaled', 'label_off': 'original',
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# 'tooltip': (
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# "Which of the resolutions is more important to be as close to the desired as possible:\n\n"
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# "When ON, the rounded with/height are first calculated for the UPSCALED resolution - and "
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# "only then the original ones are back-tracked from them.\n"
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# "When OFF, they're first calculated for the ORIGINAL resolution - and "
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# "the upscaled ones are tracked forward from them."
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# )
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# })
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__priority_type = (
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RoundingPriority.all_values(),
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{
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'default': RoundingPriority.DESIRED.value,
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'tooltip': (
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"Defines what resolution to prioritize, as well as which order to perform rounding in:\n\n"
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"• desired - first, approximate resolutions are calculated for both initial and upscaled size; "
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"then, both are rounded. In both cases, the rounded resolution is closest to the desired one, "
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"but aspect ratio might differ the most between sizes.\n\n"
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"• original - first, initial resolution is calculated and rounded; then, upscaled one is detected from it. "
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"Upscaled resolution might differ the most from the desired aspect ratio, but it follows the ratio from "
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"initial size as much as possible.\n\n"
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"• upscaled - vice versa: first, the rounded upscaled resolution is calculated; then, the initial one "
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"back-tracked from it."
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)
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}
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)
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__extra_inputs_for_upscale_only = {
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'priority': __priority_type,
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'upscale': (_IO.FLOAT, {
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'default': 1.5, 'min': 1.0, 'max': _sys.float_info.max, 'step': 0.25, 'round': 0.001,
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# 'tooltip': "", # TODO
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}),
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'up_step': (_IO.INT, dict(type_dict_step_upscale1, **{
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'tooltip': "Same as the main `step`, but for the upscaled resolution.",
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})),
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}
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_input_types_area_upscale = deepfreeze({
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'required': dict(
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(k_v for k_v in _input_types_area['required'].items() if k_v[0] != 'show'),
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**__extra_inputs_for_upscale_only,
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# show=_input_types_area['required']['show'],
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),
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'hidden': {
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'unique_id': 'UNIQUE_ID',
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},
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# 'optional': {},
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})
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class BestResolutionFromAreaUpscale:
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NODE_NAME = 'BestResolutionFromAreaUpscale'
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CATEGORY = "utils/resolution"
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DESCRIPTION = _cleandoc(__doc__)
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OUTPUT_NODE = True
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FUNCTION = 'main'
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RETURN_TYPES = _return_types_upscale
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RETURN_NAMES = _return_names_upscale
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RETURN_TYPES_TOOLTIPS = _return_ttips_upscale
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@classmethod
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def INPUT_TYPES(cls):
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return _input_types_area_upscale
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def main(
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self, square_size: int, step: int, landscape: bool, aspect_a: float, aspect_b: float,
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priority: _t.Union[RoundingPriority, str], upscale: float, up_step:int,
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# show: bool,
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unique_id: str = None
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):
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square_size: int = _number_to_int(square_size)
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width_f, height_f = _float_width_height_from_area(square_size, landscape, aspect_a, aspect_b)
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return _upscale_result_from_approx_wh(
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width_f, height_f, step,
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priority, upscale, up_step,
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# show,
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unique_id=unique_id, target_square_size=square_size
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)
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@@ -0,0 +1,122 @@
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# encoding: utf-8
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"""
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Advanced versions of nodes - with upscale.
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"""
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import typing as _t
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from inspect import cleandoc as _cleandoc
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from math import sqrt as _sqrt
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import sys as _sys
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from frozendict import deepfreeze, frozendict
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from comfy.comfy_types.node_typing import IO as _IO
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from ._funcs import (
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aspect_ratios_sorted as _aspect_ratios_sorted,
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number_to_int as _number_to_int,
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float_width_height_from_area as _float_width_height_from_area,
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simple_result_from_approx_wh as _simple_result_from_approx_wh,
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upscale_result_from_approx_wh as _upscale_result_from_approx_wh
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)
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from .enums import *
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from .node_types import *
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from .nodes_simple import _input_types_area
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# ----------------------------------------------------------
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_return_types_upscale = (_IO.INT, _IO.INT, _IO.INT, _IO.INT)
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_return_ttips_upscale = frozendict({
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'orig_w': "Width for original image",
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'orig_h': "Height for original image",
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'up_w': "Width for upscaled image",
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'up_h': "Height for upscaled image"
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})
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_return_names_upscale = tuple(_return_ttips_upscale.keys())
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# __priority_type = (_IO.BOOLEAN, {
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# 'default': True, 'label_on': 'upscaled', 'label_off': 'original',
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# 'tooltip': (
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# "Which of the resolutions is more important to be as close to the desired as possible:\n\n"
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# "When ON, the rounded with/height are first calculated for the UPSCALED resolution - and "
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# "only then the original ones are back-tracked from them.\n"
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# "When OFF, they're first calculated for the ORIGINAL resolution - and "
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# "the upscaled ones are tracked forward from them."
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# )
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# })
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__priority_type = (
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RoundingPriority.all_values(),
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{
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'default': RoundingPriority.DESIRED.value,
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'tooltip': (
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"Defines what resolution to prioritize, as well as which order to perform rounding in:\n\n"
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"• desired - first, approximate resolutions are calculated for both initial and upscaled size; "
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"then, both are rounded. In both cases, the rounded resolution is closest to the desired one, "
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"but aspect ratio might differ the most between sizes.\n\n"
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"• original - first, initial resolution is calculated and rounded; then, upscaled one is detected from it. "
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"Upscaled resolution might differ the most from the desired aspect ratio, but it follows the ratio from "
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"initial size as much as possible.\n\n"
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"• upscaled - vice versa: first, the rounded upscaled resolution is calculated; then, the initial one "
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"back-tracked from it."
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)
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}
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)
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__extra_inputs_for_upscale_only = {
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'priority': __priority_type,
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'upscale': (_IO.FLOAT, {
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'default': 1.5, 'min': 1.0, 'max': _sys.float_info.max, 'step': 0.25, 'round': 0.001,
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# 'tooltip': "", # TODO
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}),
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'up_step': (_IO.INT, dict(type_dict_step_upscale1, **{
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'tooltip': "Same as the main `step`, but for the upscaled resolution.",
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})),
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}
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_input_types_area_upscale = deepfreeze({
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'required': dict(
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(k_v for k_v in _input_types_area['required'].items() if k_v[0] != 'show'),
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**__extra_inputs_for_upscale_only,
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# show=_input_types_area['required']['show'],
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),
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'hidden': {
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'unique_id': 'UNIQUE_ID',
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},
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# 'optional': {},
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})
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class BestResolutionFromAreaUpscale:
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NODE_NAME = 'BestResolutionFromAreaUpscale'
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CATEGORY = "utils/resolution"
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DESCRIPTION = _cleandoc(__doc__)
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OUTPUT_NODE = True
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FUNCTION = 'main'
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RETURN_TYPES = _return_types_upscale
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RETURN_NAMES = _return_names_upscale
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RETURN_TYPES_TOOLTIPS = _return_ttips_upscale
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@classmethod
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def INPUT_TYPES(cls):
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return _input_types_area_upscale
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def main(
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self, square_size: int, step: int, landscape: bool, aspect_a: float, aspect_b: float,
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priority: _t.Union[RoundingPriority, str], upscale: float, up_step:int,
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# show: bool,
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unique_id: str = None
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):
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square_size: int = _number_to_int(square_size)
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width_f, height_f = _float_width_height_from_area(square_size, landscape, aspect_a, aspect_b)
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return _upscale_result_from_approx_wh(
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width_f, height_f, step,
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priority, upscale, up_step,
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# show,
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unique_id=unique_id, target_square_size=square_size
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)
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