openvinotoolkit/stable-diffusion-webui
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Merge pull request #9445 from gakada/master

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Add [batch_number] and [generation_number] filename patterns
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AUTOMATIC1111 2023-04-29 16:41:19 +03:00 committed by GitHub
commit 8651943cf9
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2 changed files with 9 additions and 1 deletions
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6
modules/images.py
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@ -352,6 +352,8 @@ class FilenameGenerator:
'prompt_no_styles': lambda self: self.prompt_no_style(), 'prompt_no_styles': lambda self: self.prompt_no_style(),
'prompt_spaces': lambda self: sanitize_filename_part(self.prompt, replace_spaces=False), 'prompt_spaces': lambda self: sanitize_filename_part(self.prompt, replace_spaces=False),
'prompt_words': lambda self: self.prompt_words(), 'prompt_words': lambda self: self.prompt_words(),
'batch_number': lambda self: self.p.batch_index + 1,
'generation_number': lambda self: self.p.iteration * self.p.batch_size + self.p.batch_index + 1,
'hasprompt': lambda self, *args: self.hasprompt(*args), #accept formats:[hasprompt<prompt1|default><prompt2>..] 'hasprompt': lambda self, *args: self.hasprompt(*args), #accept formats:[hasprompt<prompt1|default><prompt2>..]
'clip_skip': lambda self: opts.data["CLIP_stop_at_last_layers"], 'clip_skip': lambda self: opts.data["CLIP_stop_at_last_layers"],
} }
@ -421,6 +423,10 @@ class FilenameGenerator:
for m in re_pattern.finditer(x): for m in re_pattern.finditer(x):
text, pattern = m.groups() text, pattern = m.groups()
if pattern is not None and (pattern.lower() == 'batch_number' and self.p.batch_size == 1 or pattern.lower() == 'generation_number' and self.p.n_iter == 1 and self.p.batch_size == 1):
continue
res += text res += text
if pattern is None: if pattern is None:

2
modules/processing.py
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@ -683,6 +683,8 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
p.scripts.postprocess_batch(p, x_samples_ddim, batch_number=n) p.scripts.postprocess_batch(p, x_samples_ddim, batch_number=n)
for i, x_sample in enumerate(x_samples_ddim): for i, x_sample in enumerate(x_samples_ddim):
p.batch_index = i
x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2) x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2)
x_sample = x_sample.astype(np.uint8) x_sample = x_sample.astype(np.uint8)