adetailer support via injecting results earlier which should also help other post-processing based extensions. However, more accurate infotext and autosave temporarily broken from this
papuSpartan
parent
8972592319
commit
4023845658
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@ -13,6 +13,7 @@ import time
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from threading import Thread
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from typing import List
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import gradio
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from torchvision.transforms import ToTensor
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import urllib3
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from PIL import Image
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from modules import processing
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@ -71,7 +72,7 @@ class DistributedScript(scripts.Script):
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# return some components that should be exposed to the api
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return components
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def add_to_gallery(self, processed, p):
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def add_to_gallery(self, pp, p):
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"""adds generated images to the image gallery after waiting for all workers to finish"""
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def processed_inject_image(image, info_index, save_path_override=None, grid=False, response=None):
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@ -101,17 +102,20 @@ class DistributedScript(scripts.Script):
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processed_inject_image(image=image, info_index=0, response=response)
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return
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processed.all_seeds.append(seed)
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processed.all_subseeds.append(subseed)
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processed.all_negative_prompts.append(negative_prompt)
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processed.all_prompts.append(pos_prompt)
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processed.images.append(image) # actual received image
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p.seeds.append(seed)
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p.subseeds.append(subseed)
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p.negative_prompts.append(negative_prompt)
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p.prompts.append(pos_prompt)
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transform = ToTensor()
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pp.images.append(transform(image)) # actual received image
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# generate info-text string
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# modules.ui_common -> update_generation_info renders to html below gallery
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images_per_batch = p.n_iter * p.batch_size
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# zero-indexed position of image in total batch (so including master results)
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true_image_pos = len(processed.images) - 1
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true_image_pos = len(pp.images) - 1
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num_remote_images = images_per_batch * p.batch_size
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if p.n_iter > 1: # if splitting by batch count
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num_remote_images *= p.n_iter - 1
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@ -120,28 +124,28 @@ class DistributedScript(scripts.Script):
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f"info-index: {info_index}")
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if self.world.thin_client_mode:
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p.all_negative_prompts = processed.all_negative_prompts
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p.all_negative_prompts = pp.all_negative_prompts
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try:
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info_text = image_info_post['infotexts'][i]
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except IndexError:
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if not grid:
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logger.warning(f"image {true_image_pos + 1} was missing info-text")
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info_text = processed.infotexts[0]
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info_text += f", Worker Label: {job.worker.label}"
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processed.infotexts.append(info_text)
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# try:
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# info_text = image_info_post['infotexts'][i]
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# except IndexError:
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# if not grid:
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# logger.warning(f"image {true_image_pos + 1} was missing info-text")
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# info_text = processed.infotexts[0]
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# info_text += f", Worker Label: {job.worker.label}"
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# processed.infotexts.append(info_text)
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# automatically save received image to local disk if desired
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if cmd_opts.distributed_remotes_autosave:
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save_image(
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image=image,
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path=p.outpath_samples if save_path_override is None else save_path_override,
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basename="",
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seed=seed,
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prompt=pos_prompt,
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info=info_text,
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extension=opts.samples_format
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)
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#if cmd_opts.distributed_remotes_autosave:
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# save_image(
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# image=image,
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# path=p.outpath_samples if save_path_override is None else save_path_override,
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# basename="",
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# seed=seed,
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# prompt=pos_prompt,
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# info=info_text,
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# extension=opts.samples_format
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# )
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# get master ipm by estimating based on worker speed
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master_elapsed = time.time() - self.master_start
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@ -197,22 +201,11 @@ class DistributedScript(scripts.Script):
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logger.critical("couldn't collect any responses, the extension will have no effect")
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return
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# generate and inject grid
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if opts.return_grid and len(processed.images) > 1:
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grid = image_grid(processed.images, len(processed.images))
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processed_inject_image(
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image=grid,
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info_index=0,
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save_path_override=p.outpath_grids,
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grid=True,
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response=donor_worker.response
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)
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# cleanup after we're doing using all the responses
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for worker in self.world.get_workers():
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worker.response = None
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p.batch_size = len(processed.images)
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p.batch_size = len(pp.images)
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return
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# p's type is
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@ -351,11 +344,26 @@ class DistributedScript(scripts.Script):
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self.master_start = time.time()
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# generate images assigned to local machine
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p.do_not_save_grid = True # don't generate grid from master as we are doing this later.
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# p.do_not_save_grid = True # don't generate grid from master as we are doing this later.
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self.runs_since_init += 1
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return
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def postprocess(self, p, processed, *args):
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# def postprocess(self, p, processed, *args):
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# is_img2img = getattr(p, 'init_images', False)
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# if is_img2img and self.world.enabled_i2i is False:
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# return
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# elif not is_img2img and self.world.enabled is False:
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# return
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# if self.master_start is not None:
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# self.add_to_gallery(p=p, processed=processed)
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# # restore process_images_inner if it was monkey-patched
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# processing.process_images_inner = self.original_process_images_inner
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# # save any dangling state to prevent load_config in next iteration overwriting it
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# self.world.save_config()
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def postprocess_batch_list(self, p, pp, *args, **kwargs):
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is_img2img = getattr(p, 'init_images', False)
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if is_img2img and self.world.enabled_i2i is False:
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return
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@ -363,7 +371,7 @@ class DistributedScript(scripts.Script):
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return
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if self.master_start is not None:
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self.add_to_gallery(p=p, processed=processed)
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self.add_to_gallery(p=p, pp=pp)
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# restore process_images_inner if it was monkey-patched
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processing.process_images_inner = self.original_process_images_inner
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