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from modules.processing import StableDiffusionProcessingTxt2Img as txt2img
from modules.processing import StableDiffusionProcessingImg2Img as img2img
from modules.sd_samplers_kdiffusion import KDiffusionSampler as KSampler
from modules.script_callbacks import on_script_unloaded
from modules.ui_components import InputAccordion
from modules import scripts
from lib_resharpen.scaling import apply_scaling
from lib_resharpen.param import ReSharpenParams
from lib_resharpen.xyz import xyz_support
from functools import wraps
from typing import Callable
import gradio as gr
import torch
original_callback: Callable = KSampler.callback_state
@torch.inference_mode()
@wraps(original_callback)
def hijack_callback(self, d: dict):
if getattr(self.p, "_ad_inner", False):
return original_callback(self, d)
params: ReSharpenParams = getattr(self, "resharpen_params", None)
if not params:
return original_callback(self, d)
if params.cache is not None:
delta: torch.Tensor = d["x"].detach().clone() - params.cache
d["x"] += delta * apply_scaling(
params.scaling, params.strength, d["i"], params.total_step
)
params.cache = d["x"].detach().clone()
return original_callback(self, d)
KSampler.callback_state = hijack_callback
class ReSharpen(scripts.Script):
def __init__(self):
self.XYZ_CACHE = {}
xyz_support(self.XYZ_CACHE)
def title(self):
return "ReSharpen"
def show(self, is_img2img):
return scripts.AlwaysVisible
def ui(self, is_img2img):
with InputAccordion(value=False, label=self.title()) as enable:
gr.Markdown(
'<h3 style="float: left;">Softer</h3> <h3 style="float: right;">Sharper</h3>'
)
with gr.Group(elem_classes="resharpen"):
decay = gr.Slider(
label="Sharpness", minimum=-1.0, maximum=1.0, step=0.1, value=0.0
)
scaling = gr.Radio(
["Flat", "Cos", "Sin", "1 - Cos", "1 - Sin"],
label="Scaling Settings",
value="Flat",
)
with gr.Group(elem_classes=["resharpen", "hr"], visible=(not is_img2img)):
hr_decay = gr.Slider(
label="Hires. Fix Sharpness",
minimum=-1.0,
maximum=1.0,
step=0.1,
value=0.0,
)
hr_scaling = gr.Radio(
["Flat", "Cos", "Sin", "1 - Cos", "1 - Sin"],
label="Scaling Settings",
value="Flat",
)
self.paste_field_names = []
self.infotext_fields = [
(enable, "Resharpen Enabled"),
(decay, "Resharpen Sharpness"),
(scaling, "Resharpen Scaling"),
(hr_decay, "Resharpen Sharpness Hires"),
(hr_scaling, "Resharpen Scaling Hires"),
]
for comp, name in self.infotext_fields:
comp.do_not_save_to_config = True
self.paste_field_names.append(name)
return [enable, decay, scaling, hr_decay, hr_scaling]
def process(
self,
p,
enable: bool,
decay: float,
scaling: str,
hr_decay: float,
hr_scaling: str,
*args,
**kwargs,
):
if not enable:
if hasattr(KSampler, "resharpen_params"):
delattr(KSampler, "resharpen_params")
self.XYZ_CACHE.clear()
return p
if p.sampler_name.strip() == "Euler a":
print("\n[ReSharpen] has little effect with Ancestral samplers!\n")
decay = float(self.XYZ_CACHE.pop("decay", decay))
scaling = str(self.XYZ_CACHE.pop("scaling", scaling))
p.extra_generation_params.update(
{
"Resharpen Enabled": enable,
"Resharpen Sharpness": decay,
"Resharpen Scaling": scaling,
}
)
params = ReSharpenParams(
enable,
scaling,
decay / -10.0,
0,
None,
)
setattr(KSampler, "resharpen_params", params)
if isinstance(p, img2img):
self.XYZ_CACHE.clear()
return p
assert isinstance(p, txt2img)
if not getattr(p, "enable_hr", False):
self.XYZ_CACHE.clear()
return p
hr_decay = float(self.XYZ_CACHE.get("hr_decay", hr_decay))
hr_scaling = str(self.XYZ_CACHE.get("hr_scaling", hr_scaling))
p.extra_generation_params.update(
{
"Resharpen Sharpness Hires": hr_decay,
"Resharpen Scaling Hires": hr_scaling,
}
)
return p
def process_before_every_sampling(self, p, enable, *args, **kwargs):
if enable:
KSampler.resharpen_params.total_step = (
getattr(p, "firstpass_steps", 0) or p.steps
)
def before_hr(
self,
p,
enable: bool,
decay: float,
scaling: str,
hr_decay: float,
hr_scaling: str,
*args,
**kwargs,
):
if not enable:
return p
hr_decay = float(self.XYZ_CACHE.pop("hr_decay", hr_decay))
hr_scaling = str(self.XYZ_CACHE.pop("hr_scaling", hr_scaling))
params = ReSharpenParams(
enable,
hr_scaling,
hr_decay / -10.0,
getattr(p, "hr_second_pass_steps", 0) or p.steps,
None,
)
setattr(KSampler, "resharpen_params", params)
self.XYZ_CACHE.clear()
return p
def restore_callback():
KSampler.callback_state = original_callback
on_script_unloaded(restore_callback)
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