Files
adetailer/scripts/!adetailer.py
2023-04-26 23:03:59 +09:00

378 lines
12 KiB
Python

from __future__ import annotations
from pathlib import Path
import gradio as gr
import torch
import modules
from adetailer import __version__, get_models, mediapipe_predict, ultralytics_predict
from adetailer.common import dilate_erode, is_all_black, offset
from modules import devices, scripts
from modules.paths import models_path
from modules.processing import StableDiffusionProcessingImg2Img, process_images
from modules.safe import load, unsafe_torch_load
from modules.shared import opts, state
AFTER_DETAILER = "After Detailer"
adetailer_dir = Path(models_path, "adetailer")
model_mapping = get_models(adetailer_dir)
class ADetailerArgs:
"""
manualy implemented dataclass for adetailer args, due to some issue...
see: https://github.com/mkdocs/mkdocs/issues/3141
"""
def __init__(self, *args):
self.ad_model: str = args[0]
self.ad_prompt: str = args[1]
self.ad_negative_prompt: str = args[2]
self.ad_conf: float = args[3] / 100.0
self.ad_dilate_erode: int = args[4]
self.ad_x_offset: int = args[5]
self.ad_y_offset: int = args[6]
self.ad_mask_blur: int = args[7]
self.ad_denoising_strength: float = args[8]
self.ad_inpaint_full_res: bool = args[9]
self.ad_inpaint_full_res_padding: int = args[10]
self.ad_cfg_scale: float = args[11]
def asdict(self):
return {
"ad_model": self.ad_model,
"ad_prompt": self.ad_prompt,
"ad_negative_prompt": self.ad_negative_prompt,
"ad_conf": self.ad_conf,
"ad_dilate_erode": self.ad_dilate_erode,
"ad_x_offset": self.ad_x_offset,
"ad_y_offset": self.ad_y_offset,
"ad_mask_blur": self.ad_mask_blur,
"ad_denoising_strength": self.ad_denoising_strength,
"ad_inpaint_full_res": self.ad_inpaint_full_res,
"ad_inpaint_full_res_padding": self.ad_inpaint_full_res_padding,
"ad_cfg_scale": self.ad_cfg_scale,
}
def adetailer_wrapper(func):
def wrapper(*args, **kwargs):
devices.torch_gc()
torch.load = unsafe_torch_load
result = func(*args, **kwargs)
devices.torch_gc()
torch.load = load
return result
return wrapper
def gr_show(visible=True):
return {"visible": visible, "__type__": "update"}
class AfterDetailerScript(scripts.Script):
def title(self):
return AFTER_DETAILER
def show(self, is_img2img):
return scripts.AlwaysVisible
def ui(self, is_img2img):
model_list = ["None"] + list(model_mapping.keys())
with gr.Accordion(AFTER_DETAILER, open=False, elem_id="AD_main_acc"):
with gr.Group():
with gr.Row():
ad_model = gr.Dropdown(
label="ADetailer model",
choices=model_list,
value="None",
visible=True,
type="value",
)
with gr.Row():
ad_prompt = gr.Textbox(
label="ad_prompt",
show_label=False,
lines=3,
placeholder="ADetailer prompt",
)
with gr.Row():
ad_negative_prompt = gr.Textbox(
label="ad_negative_prompt",
show_label=False,
lines=2,
placeholder="ADetailer negative prompt",
)
with gr.Group():
with gr.Row():
ad_conf = gr.Slider(
label="ADetailer confidence threshold %",
minimum=0,
maximum=100,
step=1,
value=25,
visible=True,
)
ad_dilate_erode = gr.Slider(
label="ADetailer erosion (-) / dilation (+)",
minimum=-128,
maximum=128,
step=4,
value=36,
visible=True,
)
with gr.Row():
ad_x_offset = gr.Slider(
label="ADetailer x(→) offset",
minimum=-200,
maximum=200,
step=1,
value=0,
visible=True,
)
ad_y_offset = gr.Slider(
label="ADetailer y(↑) offset",
minimum=-200,
maximum=200,
step=1,
value=0,
visible=True,
)
with gr.Row():
ad_mask_blur = gr.Slider(
label="ADetailer mask blur",
minimum=0,
maximum=64,
step=1,
value=4,
visible=True,
)
ad_denoising_strength = gr.Slider(
label="ADetailer denoising strength",
minimum=0.0,
maximum=1.0,
step=0.01,
value=0.4,
visible=True,
)
with gr.Row():
ad_inpaint_full_res = gr.Checkbox(
label="Inpaint at full resolution ",
value=True,
visible=True,
)
ad_inpaint_full_res_padding = gr.Slider(
label="Inpaint at full resolution padding, pixels ",
minimum=0,
maximum=256,
step=4,
value=0,
visible=True,
)
with gr.Row():
ad_cfg_scale = gr.Slider(
label="ADetailer CFG scale",
minimum=0.0,
maximum=30.0,
step=0.5,
value=7.0,
visible=True,
)
all_widgets = [
ad_model,
ad_prompt,
ad_negative_prompt,
ad_conf,
ad_dilate_erode,
ad_x_offset,
ad_y_offset,
ad_mask_blur,
ad_denoising_strength,
ad_inpaint_full_res,
ad_inpaint_full_res_padding,
ad_cfg_scale,
]
def on_ad_model_change(model_name):
visible = model_name != "None"
return {widget: gr_show(visible) for widget in all_widgets[1:]}
ad_model.change(on_ad_model_change, inputs=[ad_model], outputs=all_widgets[1:])
self.infotext_fields = [
(ad_model, "ADetailer model"),
(ad_prompt, "ADetailer prompt"),
(ad_negative_prompt, "ADetailer negative prompt"),
(ad_conf, "ADetailer conf"),
(ad_dilate_erode, "ADetailer dilate/erode"),
(ad_x_offset, "ADetailer x offset"),
(ad_y_offset, "ADetailer y offset"),
(ad_mask_blur, "ADetailer mask blur"),
(ad_denoising_strength, "ADetailer denoising strength"),
(ad_inpaint_full_res, "ADetailer inpaint full"),
(ad_inpaint_full_res_padding, "ADetailer inpaint padding"),
(ad_cfg_scale, "ADetailer CFG scale"),
]
return all_widgets
@staticmethod
def extra_params(
ad_model,
ad_prompt,
ad_negative_prompt,
ad_conf,
ad_dilate_erode,
ad_x_offset,
ad_y_offset,
ad_mask_blur,
ad_denoising_strength,
ad_inpaint_full_res,
ad_inpaint_full_res_padding,
ad_cfg_scale,
):
params = {
"ADetailer model": ad_model,
"ADetailer prompt": ad_prompt,
"ADetailer negative prompt": ad_negative_prompt,
"ADetailer conf": int(ad_conf * 100),
"ADetailer dilate/erode": ad_dilate_erode,
"ADetailer x offset": ad_x_offset,
"ADetailer y offset": ad_y_offset,
"ADetailer mask blur": ad_mask_blur,
"ADetailer denoising strength": ad_denoising_strength,
"ADetailer inpaint full": ad_inpaint_full_res,
"ADetailer inpaint padding": ad_inpaint_full_res_padding,
"ADetailer CFG scale": ad_cfg_scale,
"ADetailer version": __version__,
}
if not ad_prompt:
params.pop("ADetailer prompt")
if not ad_negative_prompt:
params.pop("ADetailer negative prompt")
return params
@staticmethod
def get_args(*args):
return ADetailerArgs(*args)
@adetailer_wrapper
def postprocess_image(self, p, pp, *args_):
if getattr(p, "_disable_adetailer", False):
return
args = self.get_args(*args_)
if args.ad_model.lower() == "none":
return
extra_params = self.extra_params(**args.asdict())
p.extra_generation_params.update(extra_params)
p._idx = getattr(p, "_idx", -1) + 1
i = p._idx
assert hasattr(p, "all_prompts")
assert hasattr(p, "all_negative_prompts")
assert len(p.all_prompts) == len(p.all_negative_prompts)
assert 0 <= i < len(p.all_prompts)
assert 0 <= i < len(p.all_negative_prompts)
prompt = args.ad_prompt if args.ad_prompt else p.all_prompts[i]
if args.ad_negative_prompt:
negative_prompt = args.ad_negative_prompt
else:
negative_prompt = p.all_negative_prompts[i]
seed = p.all_seeds[i]
subseed = p.all_subseeds[i]
sampler_name = p.sampler_name
if sampler_name in ["PLMS", "UniPC"]:
sampler_name = "Euler"
i2i = StableDiffusionProcessingImg2Img(
init_images=[pp.image],
resize_mode=0,
denoising_strength=args.ad_denoising_strength,
mask=None,
mask_blur=args.ad_mask_blur,
inpainting_fill=1,
inpaint_full_res=args.ad_inpaint_full_res,
inpaint_full_res_padding=args.ad_inpaint_full_res_padding,
inpainting_mask_invert=0,
sd_model=p.sd_model,
outpath_samples=p.outpath_samples,
outpath_grids=p.outpath_grids,
prompt=prompt,
negative_prompt=negative_prompt,
styles=p.styles,
seed=seed,
subseed=subseed,
subseed_strength=p.subseed_strength,
seed_resize_from_h=p.seed_resize_from_h,
seed_resize_from_w=p.seed_resize_from_w,
sampler_name=sampler_name,
batch_size=1,
n_iter=1,
steps=p.steps,
cfg_scale=args.ad_cfg_scale,
width=p.width,
height=p.height,
tiling=p.tiling,
extra_generation_params=p.extra_generation_params,
do_not_save_samples=True,
do_not_save_grid=True,
)
i2i.scripts = p.scripts
i2i.script_args = p.script_args
i2i._disable_adetailer = True
if args.ad_model.lower().startswith("mediapipe"):
predictor = mediapipe_predict
ad_model = args.ad_model
else:
predictor = ultralytics_predict
ad_model = model_mapping[args.ad_model]
pred = predictor(ad_model, pp.image, args.ad_conf)
if pred.masks is None:
print("ADetailer: nothing detected with current settings")
return
masks = pred.masks
steps = len(masks)
processed = None
for j in range(steps):
mask = masks[j]
mask = dilate_erode(mask, args.ad_dilate_erode)
if is_all_black(mask):
continue
mask = offset(mask, args.ad_x_offset, args.ad_y_offset)
i2i.image_mask = mask
processed = process_images(i2i)
i2i.seed = seed + j + 1
i2i.subseed = subseed + j + 1
i2i.init_images = processed.images
if processed is not None:
pp.image = processed.images[0]