stable-diffusion-webui/scripts/xy_grid.py

155 lines
4.9 KiB
Python
Raw Normal View History

2022-09-03 16:32:45 +00:00
from collections import namedtuple
from copy import copy
import random
import modules.scripts as scripts
import gradio as gr
from modules import images
from modules.processing import process_images, Processed
from modules.shared import opts, cmd_opts, state
import modules.sd_samplers
def apply_field(field):
def fun(p, x, xs):
setattr(p, field, x)
return fun
def apply_prompt(p, x, xs):
p.prompt = p.prompt.replace(xs[0], x)
samplers_dict = {}
for i, sampler in enumerate(modules.sd_samplers.samplers):
samplers_dict[sampler.name.lower()] = i
for alias in sampler.aliases:
samplers_dict[alias.lower()] = i
def apply_sampler(p, x, xs):
sampler_index = samplers_dict.get(x.lower(), None)
print(x, sampler_index)
if sampler_index is None:
raise RuntimeError(f"Unknown sampler: {x}")
p.sampler_index = sampler_index
def format_value_add_label(p, opt, x):
return f"{opt.label}: {x}"
def format_value(p, opt, x):
return x
AxisOption = namedtuple("AxisOption", ["label", "type", "apply", "format_value"])
AxisOptionImg2Img = namedtuple("AxisOptionImg2Img", ["label", "type", "apply", "format_value"])
axis_options = [
AxisOption("Seed", int, apply_field("seed"), format_value_add_label),
AxisOption("Steps", int, apply_field("steps"), format_value_add_label),
AxisOption("CFG Scale", float, apply_field("cfg_scale"), format_value_add_label),
AxisOption("Prompt S/R", str, apply_prompt, format_value),
AxisOption("Sampler", str, apply_prompt, format_value),
AxisOptionImg2Img("Denoising", float, apply_field("denoising_strength"), format_value_add_label) # as it is now all AxisOptionImg2Img items must go after AxisOption ones
]
def draw_xy_grid(xs, ys, x_label, y_label, cell):
res = []
ver_texts = [[images.GridAnnotation(y_label(y))] for y in ys]
hor_texts = [[images.GridAnnotation(x_label(x))] for x in xs]
first_pocessed = None
for iy, y in enumerate(ys):
for ix, x in enumerate(xs):
state.job = f"{ix + iy * len(xs) + 1} out of {len(xs) * len(ys)}"
processed = cell(x, y)
if first_pocessed is None:
first_pocessed = processed
res.append(processed.images[0])
grid = images.image_grid(res, rows=len(ys))
grid = images.draw_grid_annotations(grid, res[0].width, res[0].height, hor_texts, ver_texts)
first_pocessed.images = [grid]
return first_pocessed
class Script(scripts.Script):
def title(self):
return "X/Y plot"
def ui(self, is_img2img):
current_axis_options = [x for x in axis_options if type(x) == AxisOption or type(x) == AxisOptionImg2Img and is_img2img]
with gr.Row():
x_type = gr.Dropdown(label="X type", choices=[x.label for x in current_axis_options], value=current_axis_options[0].label, visible=False, type="index", elem_id="x_type")
x_values = gr.Textbox(label="X values", visible=False, lines=1)
with gr.Row():
y_type = gr.Dropdown(label="Y type", choices=[x.label for x in current_axis_options], value=current_axis_options[1].label, visible=False, type="index", elem_id="y_type")
y_values = gr.Textbox(label="Y values", visible=False, lines=1)
return [x_type, x_values, y_type, y_values]
def run(self, p, x_type, x_values, y_type, y_values):
p.seed = int(random.randrange(4294967294) if p.seed == -1 else p.seed)
def process_axis(opt, vals):
valslist = [x.strip() for x in vals.split(",")]
if opt.type == int:
valslist_ext = []
for val in valslist:
if "-" in val:
s = val.split("-")
start = int(s[0])
end = int(s[1])+1
step = 1 if len(s) < 3 else int(s[2])
valslist_ext += list(range(start, end, step))
else:
valslist_ext.append(val)
valslist = valslist_ext
valslist = [opt.type(x) for x in valslist]
return valslist
x_opt = axis_options[x_type]
xs = process_axis(x_opt, x_values)
y_opt = axis_options[y_type]
ys = process_axis(y_opt, y_values)
def cell(x, y):
pc = copy(p)
x_opt.apply(pc, x, xs)
y_opt.apply(pc, y, ys)
return process_images(pc)
processed = draw_xy_grid(
xs=xs,
ys=ys,
x_label=lambda x: x_opt.format_value(p, x_opt, x),
y_label=lambda y: y_opt.format_value(p, y_opt, y),
cell=cell
)
images.save_image(processed.images[0], p.outpath_grids, "xy_grid", prompt=p.prompt, seed=processed.seed)
return processed