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import gradio as gr
import numpy as np
from tqdm import tqdm
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import modules.scripts as scripts
from modules.script_callbacks import on_cfg_denoiser, remove_callbacks_for_function, on_infotext_pasted
from modules.ui_components import InputAccordion
def parse_infotext(infotext, params):
try:
d = {}
for s in params['Detail Daemon'].split(','):
k, _, v = s.partition(':')
d[k.strip()] = v.strip()
params['Detail Daemon'] = d
except Exception:
pass
on_infotext_pasted(parse_infotext)
class Script(scripts.Script):
def title(self):
return "Detail Daemon"
def show(self, is_img2img):
return scripts.AlwaysVisible
def ui(self, is_img2img):
with InputAccordion(False, label="Detail Daemon", elem_id=self.elem_id('detail-daemon')) as gr_enabled:
with gr.Row():
with gr.Column(scale=2):
gr_amount_slider = gr.Slider(minimum=-1.00, maximum=1.00, step=.01, value=0.10, label="Detail Amount")
gr_start = gr.Slider(minimum=0.0, maximum=1.0, step=.01, value=0.2, label="Start")
gr_end = gr.Slider(minimum=0.0, maximum=1.0, step=.01, value=0.8, label="End")
gr_bias = gr.Slider(minimum=0.0, maximum=1.0, step=.01, value=0.5, label="Bias")
with gr.Column(scale=1, min_width=275):
preview = self.visualize(False, 0.2, 0.8, 0.5, 0.1, 1, 0, 0, 0, True)
gr_vis = gr.Plot(value=preview, elem_classes=['detail-daemon-vis'], show_label=False)
with gr.Accordion("More Knobs:", elem_classes=['detail-daemon-more-accordion'], open=False):
with gr.Row():
with gr.Column(scale=2):
with gr.Row():
gr_start_offset_slider = gr.Slider(minimum=-1.00, maximum=1.00, step=.01, value=0.00, label="Start Offset", min_width=60)
gr_end_offset_slider = gr.Slider(minimum=-1.00, maximum=1.00, step=.01, value=0.00, label="End Offset", min_width=60)
with gr.Row():
gr_exponent = gr.Slider(minimum=0.0, maximum=10.0, step=.05, value=1.0, label="Exponent", min_width=60)
gr_fade = gr.Slider(minimum=0.0, maximum=1.0, step=.05, value=0.0, label="Fade", min_width=60)
# Because the slider max and min are sometimes too limiting:
with gr.Row():
gr_amount = gr.Number(value=0.10, precision=4, step=.01, label="Amount", min_width=60)
gr_start_offset = gr.Number(value=0.0, precision=4, step=.01, label="Start Offset", min_width=60)
gr_end_offset = gr.Number(value=0.0, precision=4, step=.01, label="End Offset", min_width=60)
with gr.Column(scale=1, min_width=275):
gr_mode = gr.Dropdown(["both", "cond", "uncond"], value="uncond", label="Mode", show_label=True, min_width=60, elem_classes=['detail-daemon-mode'])
gr_smooth = gr.Checkbox(label="Smooth", value=True, min_width=60, elem_classes=['detail-daemon-smooth'])
gr.Markdown("## [Ⓗ Help](https://github.com/muerrilla/sd-webui-detail-daemon)", elem_classes=['detail-daemon-help'])
gr_amount_slider.release(None, gr_amount_slider, gr_amount, _js="(x) => x")
gr_amount.change(None, gr_amount, gr_amount_slider, _js="(x) => x")
gr_start_offset_slider.release(None, gr_start_offset_slider, gr_start_offset, _js="(x) => x")
gr_start_offset.change(None, gr_start_offset, gr_start_offset_slider, _js="(x) => x")
gr_end_offset_slider.release(None, gr_end_offset_slider, gr_end_offset, _js="(x) => x")
gr_end_offset.change(None, gr_end_offset, gr_end_offset_slider, _js="(x) => x")
vis_args = [gr_enabled, gr_start, gr_end, gr_bias, gr_amount, gr_exponent, gr_start_offset, gr_end_offset, gr_fade, gr_smooth]
for vis_arg in vis_args:
if isinstance(vis_arg, gr.components.Slider):
vis_arg.release(fn=self.visualize, show_progress=False, inputs=vis_args, outputs=[gr_vis])
else:
vis_arg.change(fn=self.visualize, show_progress=False, inputs=vis_args, outputs=[gr_vis])
def extract_infotext(d: dict, key, old_key):
if 'Detail Daemon' in d:
return d['Detail Daemon'].get(key)
return d.get(old_key)
self.infotext_fields = [
(gr_enabled, lambda d: True if ('Detail Daemon' in d or 'DD_enabled' in d) else False),
(gr_mode, lambda d: extract_infotext(d, 'mode', 'DD_mode')),
(gr_amount, lambda d: extract_infotext(d, 'amount', 'DD_amount')),
(gr_start, lambda d: extract_infotext(d, 'st', 'DD_start')),
(gr_end, lambda d: extract_infotext(d, 'ed', 'DD_end')),
(gr_bias, lambda d: extract_infotext(d, 'bias', 'DD_bias')),
(gr_exponent, lambda d: extract_infotext(d, 'exp', 'DD_exponent')),
(gr_start_offset, lambda d: extract_infotext(d, 'st_offset', 'DD_start_offset')),
(gr_end_offset, lambda d: extract_infotext(d, 'ed_offset', 'DD_end_offset')),
(gr_fade, lambda d: extract_infotext(d, 'fade', 'DD_fade')),
(gr_smooth, lambda d: extract_infotext(d, 'smooth', 'DD_smooth')),
]
return [gr_enabled, gr_mode, gr_start, gr_end, gr_bias, gr_amount, gr_exponent, gr_start_offset, gr_end_offset, gr_fade, gr_smooth]
def process(self, p, enabled, mode, start, end, bias, amount, exponent, start_offset, end_offset, fade, smooth):
enabled = getattr(p, "DD_enabled", enabled)
mode = getattr(p, "DD_mode", mode)
amount = getattr(p, "DD_amount", amount)
start = getattr(p, "DD_start", start)
end = getattr(p, "DD_end", end)
bias = getattr(p, "DD_bias", bias)
exponent = getattr(p, "DD_exponent", exponent)
start_offset = getattr(p, "DD_start_offset", start_offset)
end_offset = getattr(p, "DD_end_offset", end_offset)
fade = getattr(p, "DD_fade", fade)
smooth = getattr(p, "DD_smooth", smooth)
if enabled:
if p.sampler_name == "DPM adaptive":
tqdm.write(f'\033[33mWARNING:\033[0m Detail Daemon does not work with {p.sampler_name}')
return
# Restart can be handled better, later maybe
actual_steps = (p.steps * 2 - 1) if p.sampler_name in ['DPM++ SDE', 'DPM++ 2S a', 'Heun', 'DPM2', 'DPM2 a', 'Restart'] else p.steps
self.schedule = self.make_schedule(actual_steps, start, end, bias, amount, exponent, start_offset, end_offset, fade, smooth)
self.mode = mode
self.cfg_scale = p.cfg_scale
self.batch_size = p.batch_size
on_cfg_denoiser(self.denoiser_callback)
self.callback_added = True
p.extra_generation_params['Detail Daemon'] = f'mode:{mode},amount:{amount},st:{start},ed:{end},bias:{bias},exp:{exponent},st_offset:{start_offset},ed_offset:{end_offset},fade:{fade},smooth:{1 if smooth else 0}'
tqdm.write('\033[32mINFO:\033[0m Detail Daemon is enabled')
else:
if hasattr(self, 'callback_added'):
remove_callbacks_for_function(self.denoiser_callback)
delattr(self, 'callback_added')
# tqdm.write('\033[90mINFO: Detail Daemon callback removed\033[0m')
def before_process_batch(self, p, *args, **kwargs):
self.is_hires = False
def postprocess(self, p, processed, *args):
if hasattr(self, 'callback_added'):
remove_callbacks_for_function(self.denoiser_callback)
delattr(self, 'callback_added')
# tqdm.write('\033[90mINFO: Detail Daemon callback removed\033[0m')
def before_hr(self, p, *args):
self.is_hires = True
enabled = args[0]
if enabled:
tqdm.write(f'\033[33mINFO:\033[0m Detail Daemon does not work during Hires Fix')
def denoiser_callback(self, params):
if self.is_hires:
return
idx = params.denoiser.step
multiplier = self.schedule[idx] * .1
mode = self.mode
if params.sigma.size(0) == 1:
mode = "both"
if idx == 0:
tqdm.write(f'\033[33mWARNING:\033[0m Forge does not support `cond` and `uncond` modes, using `both` instead')
if mode == "cond":
for i in range(self.batch_size):
params.sigma[i] *= 1 - multiplier
elif mode == "uncond":
for i in range(self.batch_size):
params.sigma[self.batch_size + i] *= 1 + multiplier
else:
params.sigma *= 1 - multiplier * self.cfg_scale
def make_schedule(self, steps, start, end, bias, amount, exponent, start_offset, end_offset, fade, smooth):
start = min(start, end)
mid = start + bias * (end - start)
multipliers = np.zeros(steps)
start_idx, mid_idx, end_idx = [int(round(x * (steps - 1))) for x in [start, mid, end]]
start_values = np.linspace(0, 1, mid_idx - start_idx + 1)
if smooth:
start_values = 0.5 * (1 - np.cos(start_values * np.pi))
start_values = start_values ** exponent
if start_values.any():
start_values *= (amount - start_offset)
start_values += start_offset
end_values = np.linspace(1, 0, end_idx - mid_idx + 1)
if smooth:
end_values = 0.5 * (1 - np.cos(end_values * np.pi))
end_values = end_values ** exponent
if end_values.any():
end_values *= (amount - end_offset)
end_values += end_offset
multipliers[start_idx:mid_idx+1] = start_values
multipliers[mid_idx:end_idx+1] = end_values
multipliers[:start_idx] = start_offset
multipliers[end_idx+1:] = end_offset
multipliers *= 1 - fade
return multipliers
def visualize(self, enabled, start, end, bias, amount, exponent, start_offset, end_offset, fade, smooth):
try:
steps = 50
values = self.make_schedule(steps, start, end, bias, amount, exponent, start_offset, end_offset, fade, smooth)
mean = sum(values)/steps
peak = np.clip(max(abs(values)), -1, 1)
if start > end:
start = end
mid = start + bias * (end - start)
opacity = .1 + (1 - fade) * 0.7
plot_color = (0.5, 0.5, 0.5, opacity) if not enabled else ((1 - peak)**2, 1, 0, opacity) if mean >= 0 else (1, (1 - peak)**2, 0, opacity)
plt.rcParams.update({
"text.color": plot_color,
"axes.labelcolor": plot_color,
"axes.edgecolor": plot_color,
"figure.facecolor": (0.0, 0.0, 0.0, 0.0),
"axes.facecolor": (0.0, 0.0, 0.0, 0.0),
"ytick.labelsize": 6,
"ytick.labelcolor": plot_color,
"ytick.color": plot_color,
})
fig, ax = plt.subplots(figsize=(2.15, 2.00), layout="constrained")
ax.plot(range(steps), values, color=plot_color)
ax.axhline(y=0, color=plot_color, linestyle='dotted')
ax.axvline(x=mid * (steps - 1), color=plot_color, linestyle='dotted')
ax.tick_params(right=False, color=plot_color)
ax.set_xticks([i * (steps - 1) / 10 for i in range(10)][1:])
ax.set_xticklabels([])
ax.set_ylim([-1, 1])
ax.set_xlim([0, steps-1])
plt.close()
self.last_vis = fig
return fig
except Exception:
if self.last_vis is not None:
return self.last_vis
return
def xyz_support():
for scriptDataTuple in scripts.scripts_data:
if os.path.basename(scriptDataTuple.path) == 'xyz_grid.py':
xy_grid = scriptDataTuple.module
def confirm_mode(p, xs):
for x in xs:
if x not in ['both', 'cond', 'uncond']:
raise RuntimeError(f'Invalid Detail Daemon Mode: {x}')
mode = xy_grid.AxisOption(
'[Detail Daemon] Mode',
str,
xy_grid.apply_field('DD_mode'),
confirm=confirm_mode
)
amount = xy_grid.AxisOption(
'[Detail Daemon] Amount',
float,
xy_grid.apply_field('DD_amount')
)
start = xy_grid.AxisOption(
'[Detail Daemon] Start',
float,
xy_grid.apply_field('DD_start')
)
end = xy_grid.AxisOption(
'[Detail Daemon] End',
float,
xy_grid.apply_field('DD_end')
)
bias = xy_grid.AxisOption(
'[Detail Daemon] Bias',
float,
xy_grid.apply_field('DD_bias')
)
exponent = xy_grid.AxisOption(
'[Detail Daemon] Exponent',
float,
xy_grid.apply_field('DD_exponent')
)
start_offset = xy_grid.AxisOption(
'[Detail Daemon] Start Offset',
float,
xy_grid.apply_field('DD_start_offset')
)
end_offset = xy_grid.AxisOption(
'[Detail Daemon] End Offset',
float,
xy_grid.apply_field('DD_end_offset')
)
fade = xy_grid.AxisOption(
'[Detail Daemon] Fade',
float,
xy_grid.apply_field('DD_fade')
)
xy_grid.axis_options.extend([
mode,
amount,
start,
end,
bias,
exponent,
start_offset,
end_offset,
fade,
])
try:
xyz_support()
except Exception as e:
print(f'Error trying to add XYZ plot options for Detail Daemon', e)
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