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try:
import pag_nodes
if pag_nodes.BACKEND in {"Forge", "reForge"}:
import gradio as gr
from modules import scripts
from modules.ui_components import InputAccordion
opSEG = pag_nodes.SmoothedEnergyGuidanceAdvanced()
class SmoothedEnergyGuidanceScript(scripts.Script):
def title(self):
return "Smoothed Energy Guidance"
def show(self, is_img2img):
return scripts.AlwaysVisible
def ui(self, *args, **kwargs):
with gr.Accordion(open=False, label=self.title()):
enabled = gr.Checkbox(label="Enabled", value=False)
scale = gr.Slider(label="SEG Scale", minimum=0.0, maximum=30.0, step=0.01, value=3.0)
with gr.Row():
rescale_seg = gr.Slider(label="Rescale SEG", minimum=0.0, maximum=1.0, step=0.01, value=0.0)
rescale_mode = gr.Dropdown(choices=["full", "partial", "snf"], value="full", label="Rescale Mode")
blur_sigma = gr.Slider(label="Blur Sigma", minimum=-1.0, maximum=9999.0, step=0.01, value=-1.0)
with InputAccordion(False, label="Override for Hires. fix") as hr_override:
hr_cfg = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label="CFG Scale", value=7.0)
hr_scale = gr.Slider(label="SEG Scale", minimum=0.0, maximum=30.0, step=0.01, value=3.0)
with gr.Row():
hr_rescale_seg = gr.Slider(label="Rescale SEG", minimum=0.0, maximum=1.0, step=0.01, value=0.0)
hr_rescale_mode = gr.Dropdown(choices=["full", "partial", "snf"], value="full", label="Rescale Mode")
hr_blur_sigma = gr.Slider(label="Blur Sigma", minimum=-1.0, maximum=9999.0, step=0.01, value=-1.0)
with gr.Row():
block = gr.Dropdown(choices=["input", "middle", "output"], value="middle", label="U-Net Block")
block_id = gr.Number(label="U-Net Block Id", value=0, precision=0, minimum=0)
block_list = gr.Text(label="U-Net Block List")
with gr.Row():
sigma_start = gr.Number(minimum=-1.0, label="Sigma Start", value=-1.0)
sigma_end = gr.Number(minimum=-1.0, label="Sigma End", value=-1.0)
self.infotext_fields = (
(enabled, lambda p: gr.Checkbox.update(value="seg_enabled" in p)),
(scale, "seg_scale"),
(rescale_seg, "seg_rescale"),
(rescale_mode, lambda p: gr.Dropdown.update(value=p.get("seg_rescale_mode", "full"))),
(blur_sigma, "seg_blur_sigma"),
(hr_override, lambda p: gr.Checkbox.update(value="hr_override" in p)),
(hr_cfg, "seg_hr_cfg"),
(hr_scale, "seg_hr_scale"),
(hr_rescale_seg, "seg_hr_rescale"),
(hr_rescale_mode, lambda p: gr.Dropdown.update(value=p.get("seg_hr_rescale_mode", "full"))),
(hr_blur_sigma, "seg_hr_blur_sigma"),
(block, lambda p: gr.Dropdown.update(value=p.get("seg_block", "middle"))),
(block_id, "seg_block_id"),
(block_list, lambda p: gr.Text.update(value=p.get("seg_block_list", ""))),
(sigma_start, "seg_sigma_start"),
(sigma_end, "seg_sigma_end"),
)
return enabled, scale, rescale_seg, rescale_mode, blur_sigma, block, block_id, block_list, hr_override, hr_cfg, hr_scale, hr_rescale_seg, hr_rescale_mode, hr_blur_sigma, sigma_start, sigma_end
def process_before_every_sampling(self, p, *script_args, **kwargs):
(
enabled,
scale,
rescale_seg,
rescale_mode,
blur_sigma,
block,
block_id,
block_list,
hr_override,
hr_cfg,
hr_scale,
hr_rescale_seg,
hr_rescale_mode,
hr_blur_sigma,
sigma_start,
sigma_end,
) = script_args
if not enabled:
return
unet = p.sd_model.forge_objects.unet
hr_enabled = getattr(p, "enable_hr", False)
if hr_enabled and p.is_hr_pass and hr_override:
p.cfg_scale_before_hr = p.cfg_scale
p.cfg_scale = hr_cfg
unet = opSEG.patch(unet, hr_scale, hr_blur_sigma, block, block_id, sigma_start, sigma_end, hr_rescale_seg, hr_rescale_mode, block_list)[0]
else:
unet = opSEG.patch(unet, scale, blur_sigma, block, block_id, sigma_start, sigma_end, rescale_seg, rescale_mode, block_list)[0]
p.sd_model.forge_objects.unet = unet
p.extra_generation_params.update(
dict(
seg_enabled=enabled,
seg_scale=scale,
seg_rescale=rescale_seg,
seg_rescale_mode=rescale_mode,
seg_blur_sigma=blur_sigma,
seg_block=block,
seg_block_id=block_id,
seg_block_list=block_list,
)
)
if hr_enabled:
p.extra_generation_params["seg_hr_override"] = hr_override
if hr_override:
p.extra_generation_params.update(
dict(
seg_hr_cfg=hr_cfg,
seg_hr_scale=hr_scale,
seg_hr_rescale=hr_rescale_seg,
seg_hr_rescale_mode=hr_rescale_mode,
seg_hr_blur_sigma=hr_blur_sigma,
)
)
if sigma_start >= 0 or sigma_end >= 0:
p.extra_generation_params.update(
dict(
seg_sigma_start=sigma_start,
seg_sigma_end=sigma_end,
)
)
return
def post_sample(self, p, ps, *script_args):
(
enabled,
scale,
rescale_seg,
rescale_mode,
blur_sigma,
block,
block_id,
block_list,
hr_override,
hr_cfg,
hr_scale,
hr_rescale_seg,
hr_rescale_mode,
hr_blur_sigma,
sigma_start,
sigma_end,
) = script_args
if not enabled:
return
hr_enabled = getattr(p, "enable_hr", False)
if hr_enabled and hr_override:
p.cfg_scale = p.cfg_scale_before_hr
return
except ImportError:
pass
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