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- import numpy as np
- from tqdm import trange
-
- import modules.scripts as scripts
- import gradio as gr
-
- from modules import processing, shared, sd_samplers, images
- from modules.processing import Processed
- from modules.sd_samplers import samplers
- from modules.shared import opts, cmd_opts, state
-
-
- class Script(scripts.Script):
- def title(self):
- return "Loopback"
-
- def show(self, is_img2img):
- return is_img2img
-
- def ui(self, is_img2img):
- loops = gr.Slider(minimum=1, maximum=32, step=1, label='Loops', value=4, elem_id=self.elem_id("loops"))
- denoising_strength_change_factor = gr.Slider(minimum=0.9, maximum=1.1, step=0.01, label='Denoising strength change factor', value=1, elem_id=self.elem_id("denoising_strength_change_factor"))
-
- return [loops, denoising_strength_change_factor]
-
- def run(self, p, loops, denoising_strength_change_factor):
- processing.fix_seed(p)
- batch_count = p.n_iter
- p.extra_generation_params = {
- "Denoising strength change factor": denoising_strength_change_factor,
- }
-
- p.batch_size = 1
- p.n_iter = 1
-
- output_images, info = None, None
- initial_seed = None
- initial_info = None
-
- grids = []
- all_images = []
- original_init_image = p.init_images
- state.job_count = loops * batch_count
-
- initial_color_corrections = [processing.setup_color_correction(p.init_images[0])]
-
- for n in range(batch_count):
- history = []
-
- # Reset to original init image at the start of each batch
- p.init_images = original_init_image
-
- for i in range(loops):
- p.n_iter = 1
- p.batch_size = 1
- p.do_not_save_grid = True
-
- if opts.img2img_color_correction:
- p.color_corrections = initial_color_corrections
-
- state.job = f"Iteration {i + 1}/{loops}, batch {n + 1}/{batch_count}"
-
- processed = processing.process_images(p)
-
- if initial_seed is None:
- initial_seed = processed.seed
- initial_info = processed.info
-
- init_img = processed.images[0]
-
- p.init_images = [init_img]
- p.seed = processed.seed + 1
- p.denoising_strength = min(max(p.denoising_strength * denoising_strength_change_factor, 0.1), 1)
- history.append(processed.images[0])
-
- grid = images.image_grid(history, rows=1)
- if opts.grid_save:
- images.save_image(grid, p.outpath_grids, "grid", initial_seed, p.prompt, opts.grid_format, info=info, short_filename=not opts.grid_extended_filename, grid=True, p=p)
-
- grids.append(grid)
- all_images += history
-
- if opts.return_grid:
- all_images = grids + all_images
-
- processed = Processed(p, all_images, initial_seed, initial_info)
-
- return processed
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