mirror of
https://github.com/lllyasviel/stable-diffusion-webui-forge.git
synced 2026-07-21 21:01:24 +08:00
105 lines
4.3 KiB
Python
105 lines
4.3 KiB
Python
import math
|
|
|
|
import gradio as gr
|
|
import modules.scripts as scripts
|
|
from modules import images
|
|
from modules.processing import fix_seed, process_images
|
|
from modules.shared import opts, state
|
|
|
|
|
|
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_processed = None
|
|
|
|
state.job_count = len(xs) * len(ys)
|
|
|
|
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_processed is None:
|
|
first_processed = 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_processed.images = [grid]
|
|
return first_processed
|
|
|
|
|
|
class PromptMatrix(scripts.Script):
|
|
def title(self):
|
|
return "Prompt Matrix"
|
|
|
|
def ui(self, is_img2img):
|
|
gr.HTML("<br>")
|
|
with gr.Row():
|
|
with gr.Column():
|
|
put_at_start = gr.Checkbox(value=False, label="Put the variable parts at the start of prompt", elem_id=self.elem_id("put_at_start"))
|
|
different_seeds = gr.Checkbox(value=False, label="Use different seeds for each image", elem_id=self.elem_id("different_seeds"))
|
|
margin_size = gr.Slider(value=0, label="Grid Margins (px)", minimum=0, maximum=256, step=2, elem_id=self.elem_id("margin_size"))
|
|
with gr.Column():
|
|
prompt_type = gr.Radio(value="positive", label="Prompt", choices=("positive", "negative"), elem_id=self.elem_id("prompt_type"))
|
|
variations_delimiter = gr.Radio(value="comma", label="Joining Char.", choices=("comma", "space"), elem_id=self.elem_id("variations_delimiter"))
|
|
|
|
return [put_at_start, different_seeds, prompt_type, variations_delimiter, margin_size]
|
|
|
|
def run(self, p, put_at_start: bool, different_seeds: bool, prompt_type: str, variations_delimiter: str, margin_size: int):
|
|
fix_seed(p)
|
|
|
|
assert prompt_type in ("positive", "negative")
|
|
assert variations_delimiter in ("comma", "space")
|
|
|
|
prompt = p.prompt if prompt_type == "positive" else p.negative_prompt
|
|
original_prompt = prompt[0] if isinstance(prompt, list) else prompt
|
|
positive_prompt = p.prompt[0] if isinstance(p.prompt, list) else p.prompt
|
|
|
|
delimiter = ", " if variations_delimiter == "comma" else " "
|
|
|
|
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(delimiter.join(selected_prompts))
|
|
|
|
p.n_iter = math.ceil(len(all_prompts) / p.batch_size)
|
|
p.do_not_save_grid = True
|
|
|
|
print(f"PromptMatrix: creating {len(all_prompts)} images in {p.n_iter} batches")
|
|
|
|
if prompt_type == "positive":
|
|
p.prompt = all_prompts
|
|
else:
|
|
p.negative_prompt = all_prompts
|
|
|
|
p.prompt_for_display = positive_prompt
|
|
p.seed = [p.seed + (i if different_seeds else 0) for i in range(len(all_prompts))]
|
|
|
|
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, processed.images[0].width, processed.images[0].height, prompt_matrix_parts, margin_size)
|
|
|
|
processed.images.insert(0, grid)
|
|
processed.index_of_first_image = 1
|
|
processed.infotexts.insert(0, processed.infotexts[0])
|
|
|
|
if opts.grid_save:
|
|
images.save_image(processed.images[0], p.outpath_grids, "prompt_matrix", extension=opts.grid_format, prompt=original_prompt, seed=processed.seed, grid=True, p=p)
|
|
|
|
return processed
|