scripts
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@ -266,7 +266,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
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seed = gr.Number(label='Seed', value=-1)
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with gr.Group():
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custom_inputs = modules.scripts.setup_ui(is_img2img=False)
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custom_inputs = modules.scripts.setup_ui(is_img2img=True)
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with gr.Column(variant='panel'):
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@ -36,7 +36,7 @@ titles = {
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"None": "Do not do anything special",
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"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)",
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"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",
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"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",
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"Custom code": "Run python code. Advanced user only. Must run program with --allow-code for this to work",
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"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",
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40
scripts/custom_code.py
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40
scripts/custom_code.py
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import modules.scripts as scripts
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import gradio as gr
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from modules.processing import Processed
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from modules.shared import opts, cmd_opts, state
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class Script(scripts.Script):
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def title(self):
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return "Custom code"
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def enabled(self):
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return cmd_opts.allow_code
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def ui(self, is_img2img):
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code = gr.Textbox(label="Python code", visible=False, lines=1)
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return [code]
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def run(self, p, code):
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if not cmd_opts.allow_code:
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return
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display_result_data = [[], -1, ""]
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def display(imgs, s=display_result_data[1], i=display_result_data[2]):
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display_result_data[0] = imgs
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display_result_data[1] = s
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display_result_data[2] = i
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from types import ModuleType
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compiled = compile(code, '', 'exec')
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module = ModuleType("testmodule")
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module.__dict__.update(globals())
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module.p = p
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module.display = display
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exec(compiled, module.__dict__)
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return Processed(p, *display_result_data)
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82
scripts/prompt_matrix.py
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scripts/prompt_matrix.py
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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_pocessed = None
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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_pocessed is None:
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first_pocessed = 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_pocessed.images = [grid]
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return first_pocessed
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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)
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return [put_at_start]
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def run(self, p, put_at_start):
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seed = int(random.randrange(4294967294) if p.seed == -1 else p.seed)
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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.prompt_for_display = original_prompt
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p.seed = len(all_prompts) * [seed]
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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, p.width, p.height, prompt_matrix_parts)
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processed.images.insert(0, grid)
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return processed
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154
scripts/xy_grid.py
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154
scripts/xy_grid.py
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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 apply_field(field):
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def fun(p, x, xs):
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setattr(p, field, x)
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return fun
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def apply_prompt(p, x, xs):
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p.prompt = p.prompt.replace(xs[0], x)
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samplers_dict = {}
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for i, sampler in enumerate(modules.sd_samplers.samplers):
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samplers_dict[sampler.name.lower()] = i
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for alias in sampler.aliases:
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samplers_dict[alias.lower()] = i
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def apply_sampler(p, x, xs):
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sampler_index = samplers_dict.get(x.lower(), None)
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print(x, sampler_index)
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if sampler_index is None:
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raise RuntimeError(f"Unknown sampler: {x}")
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p.sampler_index = sampler_index
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def format_value_add_label(p, opt, x):
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return f"{opt.label}: {x}"
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def format_value(p, opt, x):
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return x
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AxisOption = namedtuple("AxisOption", ["label", "type", "apply", "format_value"])
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AxisOptionImg2Img = namedtuple("AxisOptionImg2Img", ["label", "type", "apply", "format_value"])
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axis_options = [
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AxisOption("Seed", int, apply_field("seed"), format_value_add_label),
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AxisOption("Steps", int, apply_field("steps"), format_value_add_label),
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AxisOption("CFG Scale", float, apply_field("cfg_scale"), format_value_add_label),
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AxisOption("Prompt S/R", str, apply_prompt, format_value),
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AxisOption("Sampler", str, apply_prompt, format_value),
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AxisOptionImg2Img("Denoising", float, apply_field("denoising_strength"), format_value_add_label) # as it is now all AxisOptionImg2Img items must go after AxisOption ones
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]
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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_pocessed = None
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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_pocessed is None:
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first_pocessed = 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_pocessed.images = [grid]
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return first_pocessed
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class Script(scripts.Script):
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def title(self):
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return "X/Y plot"
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def ui(self, is_img2img):
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current_axis_options = [x for x in axis_options if type(x) == AxisOption or type(x) == AxisOptionImg2Img and is_img2img]
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with gr.Row():
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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")
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x_values = gr.Textbox(label="X values", visible=False, lines=1)
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with gr.Row():
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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")
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y_values = gr.Textbox(label="Y values", visible=False, lines=1)
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return [x_type, x_values, y_type, y_values]
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def run(self, p, x_type, x_values, y_type, y_values):
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p.seed = int(random.randrange(4294967294) if p.seed == -1 else p.seed)
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def process_axis(opt, vals):
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valslist = [x.strip() for x in vals.split(",")]
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if opt.type == int:
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valslist_ext = []
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for val in valslist:
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if "-" in val:
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s = val.split("-")
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start = int(s[0])
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end = int(s[1])+1
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step = 1 if len(s) < 3 else int(s[2])
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valslist_ext += list(range(start, end, step))
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else:
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valslist_ext.append(val)
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valslist = valslist_ext
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valslist = [opt.type(x) for x in valslist]
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return valslist
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x_opt = axis_options[x_type]
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xs = process_axis(x_opt, x_values)
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y_opt = axis_options[y_type]
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ys = process_axis(y_opt, y_values)
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def cell(x, y):
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pc = copy(p)
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x_opt.apply(pc, x, xs)
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y_opt.apply(pc, y, ys)
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return process_images(pc)
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processed = draw_xy_grid(
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xs=xs,
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ys=ys,
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x_label=lambda x: x_opt.format_value(p, x_opt, x),
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y_label=lambda y: y_opt.format_value(p, y_opt, y),
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cell=cell
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)
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images.save_image(processed.images[0], p.outpath_grids, "xy_grid", prompt=p.prompt, seed=processed.seed)
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return processed
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