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https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
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17b24e45e8
- images.draw_prompt_matrix() should be called with the final width/height of the generated images, after upscaling. Otherwise, the number of rows/cols computed in images.draw_grid_annotations will increase by the upscaling factor. - Round the number of cols/rows in images.draw_grid_annotations, since the final images width may be a bit less than the required hr_upscale_to_x/y
91 lines
3.4 KiB
Python
91 lines
3.4 KiB
Python
import math
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from collections import namedtuple
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from copy import copy
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import random
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import modules.scripts as scripts
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import gradio as gr
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from modules import images
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from modules.processing import process_images, Processed
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from modules.shared import opts, cmd_opts, state
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import modules.sd_samplers
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def draw_xy_grid(xs, ys, x_label, y_label, cell):
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res = []
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ver_texts = [[images.GridAnnotation(y_label(y))] for y in ys]
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hor_texts = [[images.GridAnnotation(x_label(x))] for x in xs]
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first_processed = None
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state.job_count = len(xs) * len(ys)
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for iy, y in enumerate(ys):
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for ix, x in enumerate(xs):
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state.job = f"{ix + iy * len(xs) + 1} out of {len(xs) * len(ys)}"
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processed = cell(x, y)
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if first_processed is None:
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first_processed = processed
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res.append(processed.images[0])
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grid = images.image_grid(res, rows=len(ys))
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grid = images.draw_grid_annotations(grid, res[0].width, res[0].height, hor_texts, ver_texts)
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first_processed.images = [grid]
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return first_processed
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class Script(scripts.Script):
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def title(self):
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return "Prompt matrix"
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def ui(self, is_img2img):
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put_at_start = gr.Checkbox(label='Put variable parts at start of prompt', value=False, elem_id=self.elem_id("put_at_start"))
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different_seeds = gr.Checkbox(label='Use different seed for each picture', value=False, elem_id=self.elem_id("different_seeds"))
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return [put_at_start, different_seeds]
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def run(self, p, put_at_start, different_seeds):
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modules.processing.fix_seed(p)
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original_prompt = p.prompt[0] if type(p.prompt) == list else p.prompt
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all_prompts = []
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prompt_matrix_parts = original_prompt.split("|")
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combination_count = 2 ** (len(prompt_matrix_parts) - 1)
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for combination_num in range(combination_count):
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selected_prompts = [text.strip().strip(',') for n, text in enumerate(prompt_matrix_parts[1:]) if combination_num & (1 << n)]
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if put_at_start:
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selected_prompts = selected_prompts + [prompt_matrix_parts[0]]
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else:
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selected_prompts = [prompt_matrix_parts[0]] + selected_prompts
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all_prompts.append(", ".join(selected_prompts))
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p.n_iter = math.ceil(len(all_prompts) / p.batch_size)
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p.do_not_save_grid = True
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print(f"Prompt matrix will create {len(all_prompts)} images using a total of {p.n_iter} batches.")
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p.prompt = all_prompts
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p.seed = [p.seed + (i if different_seeds else 0) for i in range(len(all_prompts))]
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p.prompt_for_display = original_prompt
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processed = process_images(p)
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grid = images.image_grid(processed.images, p.batch_size, rows=1 << ((len(prompt_matrix_parts) - 1) // 2))
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grid = images.draw_prompt_matrix(grid, max(p.width, p.hr_upscale_to_x), max(p.height, p.hr_upscale_to_y), prompt_matrix_parts)
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processed.images.insert(0, grid)
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processed.index_of_first_image = 1
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processed.infotexts.insert(0, processed.infotexts[0])
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if opts.grid_save:
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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)
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return processed
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