scripts
This commit is contained in:
parent
595c827bd3
commit
592334f322
|
@ -266,7 +266,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
|
|||
seed = gr.Number(label='Seed', value=-1)
|
||||
|
||||
with gr.Group():
|
||||
custom_inputs = modules.scripts.setup_ui(is_img2img=False)
|
||||
custom_inputs = modules.scripts.setup_ui(is_img2img=True)
|
||||
|
||||
|
||||
with gr.Column(variant='panel'):
|
||||
|
|
|
@ -36,7 +36,7 @@ titles = {
|
|||
|
||||
"None": "Do not do anything special",
|
||||
"Prompt matrix": "Separate prompts into parts using vertical pipe character (|) and the script will create a picture for every combination of them (except for the first part, which will be present in all combinations)",
|
||||
"X/Y Plot": "Create a grid where images will have different parameters. Use inputs below to specify which parameterswill be shared by columns and rows",
|
||||
"X/Y plot": "Create a grid where images will have different parameters. Use inputs below to specify which parameterswill be shared by columns and rows",
|
||||
"Custom code": "Run python code. Advanced user only. Must run program with --allow-code for this to work",
|
||||
|
||||
"Prompt S/R": "Separate a list of words with commas, and the first word will be used as a keyword: script will search for this word in the prompt, and replace it with others",
|
||||
|
|
|
@ -0,0 +1,40 @@
|
|||
import modules.scripts as scripts
|
||||
import gradio as gr
|
||||
|
||||
from modules.processing import Processed
|
||||
from modules.shared import opts, cmd_opts, state
|
||||
|
||||
|
||||
class Script(scripts.Script):
|
||||
def title(self):
|
||||
return "Custom code"
|
||||
|
||||
def enabled(self):
|
||||
return cmd_opts.allow_code
|
||||
|
||||
def ui(self, is_img2img):
|
||||
code = gr.Textbox(label="Python code", visible=False, lines=1)
|
||||
|
||||
return [code]
|
||||
|
||||
def run(self, p, code):
|
||||
if not cmd_opts.allow_code:
|
||||
return
|
||||
|
||||
display_result_data = [[], -1, ""]
|
||||
|
||||
def display(imgs, s=display_result_data[1], i=display_result_data[2]):
|
||||
display_result_data[0] = imgs
|
||||
display_result_data[1] = s
|
||||
display_result_data[2] = i
|
||||
|
||||
from types import ModuleType
|
||||
compiled = compile(code, '', 'exec')
|
||||
module = ModuleType("testmodule")
|
||||
module.__dict__.update(globals())
|
||||
module.p = p
|
||||
module.display = display
|
||||
exec(compiled, module.__dict__)
|
||||
|
||||
return Processed(p, *display_result_data)
|
||||
|
|
@ -0,0 +1,82 @@
|
|||
import math
|
||||
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 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 "Prompt matrix"
|
||||
|
||||
def ui(self, is_img2img):
|
||||
put_at_start = gr.Checkbox(label='Put variable parts at start of prompt', value=False)
|
||||
|
||||
return [put_at_start]
|
||||
|
||||
def run(self, p, put_at_start):
|
||||
seed = int(random.randrange(4294967294) if p.seed == -1 else p.seed)
|
||||
|
||||
original_prompt = p.prompt[0] if type(p.prompt) == list else p.prompt
|
||||
|
||||
all_prompts = []
|
||||
prompt_matrix_parts = original_prompt.split("|")
|
||||
combination_count = 2 ** (len(prompt_matrix_parts) - 1)
|
||||
for combination_num in range(combination_count):
|
||||
selected_prompts = [text.strip().strip(',') for n, text in enumerate(prompt_matrix_parts[1:]) if combination_num & (1 << n)]
|
||||
|
||||
if put_at_start:
|
||||
selected_prompts = selected_prompts + [prompt_matrix_parts[0]]
|
||||
else:
|
||||
selected_prompts = [prompt_matrix_parts[0]] + selected_prompts
|
||||
|
||||
all_prompts.append(", ".join(selected_prompts))
|
||||
|
||||
p.n_iter = math.ceil(len(all_prompts) / p.batch_size)
|
||||
p.do_not_save_grid = True
|
||||
|
||||
print(f"Prompt matrix will create {len(all_prompts)} images using a total of {p.n_iter} batches.")
|
||||
|
||||
p.prompt = all_prompts
|
||||
p.prompt_for_display = original_prompt
|
||||
p.seed = len(all_prompts) * [seed]
|
||||
processed = process_images(p)
|
||||
|
||||
grid = images.image_grid(processed.images, p.batch_size, rows=1 << ((len(prompt_matrix_parts) - 1) // 2))
|
||||
grid = images.draw_prompt_matrix(grid, p.width, p.height, prompt_matrix_parts)
|
||||
processed.images.insert(0, grid)
|
||||
|
||||
return processed
|
|
@ -0,0 +1,154 @@
|
|||
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
|
Loading…
Reference in New Issue