Merge pull request #11957 from ljleb/pp-batch-list
Add postprocess_batch_list script callback
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@ -717,7 +717,27 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
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p.all_subseeds = [int(subseed) + x for x in range(len(p.all_prompts))]
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def infotext(iteration=0, position_in_batch=0, use_main_prompt=False):
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return create_infotext(p, p.all_prompts, p.all_seeds, p.all_subseeds, comments, iteration, position_in_batch, use_main_prompt)
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all_prompts = p.all_prompts[:]
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all_negative_prompts = p.all_negative_prompts[:]
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all_seeds = p.all_seeds[:]
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all_subseeds = p.all_subseeds[:]
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# apply changes to generation data
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all_prompts[iteration * p.batch_size:(iteration + 1) * p.batch_size] = p.prompts
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all_negative_prompts[iteration * p.batch_size:(iteration + 1) * p.batch_size] = p.negative_prompts
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all_seeds[iteration * p.batch_size:(iteration + 1) * p.batch_size] = p.seeds
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all_subseeds[iteration * p.batch_size:(iteration + 1) * p.batch_size] = p.subseeds
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# update p.all_negative_prompts in case extensions changed the size of the batch
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# create_infotext below uses it
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old_negative_prompts = p.all_negative_prompts
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p.all_negative_prompts = all_negative_prompts
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try:
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return create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration, position_in_batch, use_main_prompt)
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finally:
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# restore p.all_negative_prompts in case extensions changed the size of the batch
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p.all_negative_prompts = old_negative_prompts
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if os.path.exists(cmd_opts.embeddings_dir) and not p.do_not_reload_embeddings:
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model_hijack.embedding_db.load_textual_inversion_embeddings()
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@ -806,6 +826,10 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
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if p.scripts is not None:
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p.scripts.postprocess_batch(p, x_samples_ddim, batch_number=n)
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postprocess_batch_list_args = scripts.PostprocessBatchListArgs(list(x_samples_ddim))
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p.scripts.postprocess_batch_list(p, postprocess_batch_list_args, batch_number=n)
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x_samples_ddim = postprocess_batch_list_args.images
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for i, x_sample in enumerate(x_samples_ddim):
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p.batch_index = i
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@ -16,6 +16,11 @@ class PostprocessImageArgs:
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self.image = image
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class PostprocessBatchListArgs:
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def __init__(self, images):
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self.images = images
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class Script:
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name = None
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"""script's internal name derived from title"""
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@ -156,6 +161,25 @@ class Script:
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pass
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def postprocess_batch_list(self, p, pp: PostprocessBatchListArgs, *args, **kwargs):
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"""
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Same as postprocess_batch(), but receives batch images as a list of 3D tensors instead of a 4D tensor.
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This is useful when you want to update the entire batch instead of individual images.
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You can modify the postprocessing object (pp) to update the images in the batch, remove images, add images, etc.
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If the number of images is different from the batch size when returning,
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then the script has the responsibility to also update the following attributes in the processing object (p):
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- p.prompts
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- p.negative_prompts
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- p.seeds
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- p.subseeds
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**kwargs will have same items as process_batch, and also:
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- batch_number - index of current batch, from 0 to number of batches-1
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"""
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pass
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def postprocess_image(self, p, pp: PostprocessImageArgs, *args):
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"""
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Called for every image after it has been generated.
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@ -536,6 +560,14 @@ class ScriptRunner:
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except Exception:
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errors.report(f"Error running postprocess_batch: {script.filename}", exc_info=True)
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def postprocess_batch_list(self, p, pp: PostprocessBatchListArgs, **kwargs):
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for script in self.alwayson_scripts:
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try:
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script_args = p.script_args[script.args_from:script.args_to]
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script.postprocess_batch_list(p, pp, *script_args, **kwargs)
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except Exception:
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errors.report(f"Error running postprocess_batch_list: {script.filename}", exc_info=True)
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def postprocess_image(self, p, pp: PostprocessImageArgs):
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for script in self.alwayson_scripts:
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try:
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