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made 'reuse seed' button give you the seed/subseed of the currently selected picture rather than the first

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AUTOMATIC 2022-09-19 09:02:10 +03:00
parent 7ae3dc2866
commit 7539f04e28
2 changed files with 100 additions and 74 deletions
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108
modules/processing.py
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@ -83,7 +83,7 @@ class StableDiffusionProcessing:
class Processed:
def __init__(self, p: StableDiffusionProcessing, images_list, seed, info, subseed=None):
def __init__(self, p: StableDiffusionProcessing, images_list, seed=-1, info="", subseed=None, all_prompts=None, all_seeds=None, all_subseeds=None, index_of_first_image=0):
self.images = images_list
self.prompt = p.prompt
self.negative_prompt = p.negative_prompt
@ -93,26 +93,62 @@ class Processed:
self.info = info
self.width = p.width
self.height = p.height
self.sampler_index = p.sampler_index
self.sampler = samplers[p.sampler_index].name
self.cfg_scale = p.cfg_scale
self.steps = p.steps
self.batch_size = p.batch_size
self.restore_faces = p.restore_faces
self.face_restoration_model = opts.face_restoration_model if p.restore_faces else None
self.sd_model_hash = shared.sd_model.sd_model_hash
self.seed_resize_from_w = p.seed_resize_from_w
self.seed_resize_from_h = p.seed_resize_from_h
self.denoising_strength = getattr(p, 'denoising_strength', None)
self.extra_generation_params = p.extra_generation_params
self.index_of_first_image = index_of_first_image
self.prompt = self.prompt if type(self.prompt) != list else self.prompt[0]
self.negative_prompt = self.negative_prompt if type(self.negative_prompt) != list else self.negative_prompt[0]
self.seed = int(self.seed if type(self.seed) != list else self.seed[0])
self.subseed = int(self.subseed if type(self.subseed) != list else self.subseed[0]) if self.subseed is not None else -1
self.all_prompts = all_prompts or [self.prompt]
self.all_seeds = all_seeds or [self.seed]
self.all_subseeds = all_subseeds or [self.subseed]
def js(self):
obj = {
"prompt": self.prompt if type(self.prompt) != list else self.prompt[0],
"negative_prompt": self.negative_prompt if type(self.negative_prompt) != list else self.negative_prompt[0],
"seed": int(self.seed if type(self.seed) != list else self.seed[0]),
"subseed": int(self.subseed if type(self.subseed) != list else self.subseed[0]) if self.subseed is not None else -1,
"prompt": self.prompt,
"all_prompts": self.all_prompts,
"negative_prompt": self.negative_prompt,
"seed": self.seed,
"all_seeds": self.all_seeds,
"subseed": self.subseed,
"all_subseeds": self.all_subseeds,
"subseed_strength": self.subseed_strength,
"width": self.width,
"height": self.height,
"sampler_index": self.sampler_index,
"sampler": self.sampler,
"cfg_scale": self.cfg_scale,
"steps": self.steps,
"batch_size": self.batch_size,
"restore_faces": self.restore_faces,
"face_restoration_model": self.face_restoration_model,
"sd_model_hash": self.sd_model_hash,
"seed_resize_from_w": self.seed_resize_from_w,
"seed_resize_from_h": self.seed_resize_from_h,
"denoising_strength": self.denoising_strength,
"extra_generation_params": self.extra_generation_params,
"index_of_first_image": self.index_of_first_image,
}
return json.dumps(obj)
def infotext(self, p: StableDiffusionProcessing, index):
return create_infotext(p, self.all_prompts, self.all_seeds, self.all_subseeds, comments=[], position_in_batch=index % self.batch_size, iteration=index // self.batch_size)
# from https://discuss.pytorch.org/t/help-regarding-slerp-function-for-generative-model-sampling/32475/3
def slerp(val, low, high):
low_norm = low/torch.norm(low, dim=1, keepdim=True)
@ -156,11 +192,9 @@ def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=0.0, see
noise = devices.randn(seed, noise_shape)
if subnoise is not None:
#noise = subnoise * subseed_strength + noise * (1 - subseed_strength)
noise = slerp(subseed_strength, noise, subnoise)
if noise_shape != shape:
#noise = torch.nn.functional.interpolate(noise.unsqueeze(1), size=shape[1:], mode="bilinear").squeeze()
x = devices.randn(seed, shape)
dx = (shape[2] - noise_shape[2]) // 2
dy = (shape[1] - noise_shape[1]) // 2
@ -194,6 +228,35 @@ def fix_seed(p):
p.subseed = int(random.randrange(4294967294)) if p.subseed is None or p.subseed == -1 else p.subseed
def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration=0, position_in_batch=0):
index = position_in_batch + iteration * p.batch_size
generation_params = {
"Steps": p.steps,
"Sampler": samplers[p.sampler_index].name,
"CFG scale": p.cfg_scale,
"Seed": all_seeds[index],
"Face restoration": (opts.face_restoration_model if p.restore_faces else None),
"Size": f"{p.width}x{p.height}",
"Model hash": getattr(p, 'sd_model_hash', None if not opts.add_model_hash_to_info or not shared.sd_model.sd_model_hash else shared.sd_model.sd_model_hash),
"Batch size": (None if p.batch_size < 2 else p.batch_size),
"Batch pos": (None if p.batch_size < 2 else position_in_batch),
"Variation seed": (None if p.subseed_strength == 0 else all_subseeds[index]),
"Variation seed strength": (None if p.subseed_strength == 0 else p.subseed_strength),
"Seed resize from": (None if p.seed_resize_from_w == 0 or p.seed_resize_from_h == 0 else f"{p.seed_resize_from_w}x{p.seed_resize_from_h}"),
"Denoising strength": getattr(p, 'denoising_strength', None),
}
if p.extra_generation_params is not None:
generation_params.update(p.extra_generation_params)
generation_params_text = ", ".join([k if k == v else f'{k}: {v}' for k, v in generation_params.items() if v is not None])
negative_prompt_text = "\nNegative prompt: " + p.negative_prompt if p.negative_prompt else ""
return f"{all_prompts[index]}{negative_prompt_text}\n{generation_params_text}".strip() + "".join(["\n\n" + x for x in comments])
def process_images(p: StableDiffusionProcessing) -> Processed:
"""this is the main loop that both txt2img and img2img use; it calls func_init once inside all the scopes and func_sample once per batch"""
@ -231,32 +294,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
all_subseeds = [int(p.subseed + x) for x in range(len(all_prompts))]
def infotext(iteration=0, position_in_batch=0):
index = position_in_batch + iteration * p.batch_size
generation_params = {
"Steps": p.steps,
"Sampler": samplers[p.sampler_index].name,
"CFG scale": p.cfg_scale,
"Seed": all_seeds[index],
"Face restoration": (opts.face_restoration_model if p.restore_faces else None),
"Size": f"{p.width}x{p.height}",
"Model hash": (None if not opts.add_model_hash_to_info or not shared.sd_model.sd_model_hash else shared.sd_model.sd_model_hash),
"Batch size": (None if p.batch_size < 2 else p.batch_size),
"Batch pos": (None if p.batch_size < 2 else position_in_batch),
"Variation seed": (None if p.subseed_strength == 0 else all_subseeds[index]),
"Variation seed strength": (None if p.subseed_strength == 0 else p.subseed_strength),
"Seed resize from": (None if p.seed_resize_from_w == 0 or p.seed_resize_from_h == 0 else f"{p.seed_resize_from_w}x{p.seed_resize_from_h}"),
"Denoising strength": getattr(p, 'denoising_strength', None),
}
if p.extra_generation_params is not None:
generation_params.update(p.extra_generation_params)
generation_params_text = ", ".join([k if k == v else f'{k}: {v}' for k, v in generation_params.items() if v is not None])
negative_prompt_text = "\nNegative prompt: " + p.negative_prompt if p.negative_prompt else ""
return f"{all_prompts[index]}{negative_prompt_text}\n{generation_params_text}".strip() + "".join(["\n\n" + x for x in comments])
return create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration, position_in_batch)
if os.path.exists(cmd_opts.embeddings_dir):
model_hijack.load_textual_inversion_embeddings(cmd_opts.embeddings_dir, p.sd_model)
@ -350,18 +388,20 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
p.color_corrections = None
index_of_first_image = 0
unwanted_grid_because_of_img_count = len(output_images) < 2 and opts.grid_only_if_multiple
if (opts.return_grid or opts.grid_save) and not p.do_not_save_grid and not unwanted_grid_because_of_img_count:
grid = images.image_grid(output_images, p.batch_size)
if opts.return_grid:
output_images.insert(0, grid)
index_of_first_image = 1
if opts.grid_save:
images.save_image(grid, p.outpath_grids, "grid", all_seeds[0], all_prompts[0], opts.grid_format, info=infotext(), short_filename=not opts.grid_extended_filename, p=p)
devices.torch_gc()
return Processed(p, output_images, all_seeds[0], infotext(), subseed=all_subseeds[0])
return Processed(p, output_images, all_seeds[0], infotext(), subseed=all_subseeds[0], all_prompts=all_prompts, all_seeds=all_seeds, all_subseeds=all_subseeds, index_of_first_image=index_of_first_image)
class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):

66
modules/ui.py
View file

@ -297,53 +297,39 @@ def create_seed_inputs():
return seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w
def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info: gr.Textbox):
""" Connects a 'reuse seed' button's click event so that it copies last used
seed value from generation info the to the seed."""
def copy_seed(gen_info_string: str):
try:
gen_info = json.loads(gen_info_string)
return gen_info.get('seed', -1)
except json.decoder.JSONDecodeError as e:
if gen_info_string != '':
print("Error parsing JSON generation info:", file=sys.stderr)
print(gen_info_string, file=sys.stderr)
return -1
reuse_seed.click(
fn=copy_seed,
show_progress=False,
inputs=[generation_info],
outputs=[seed]
)
def connect_reuse_subseed(seed: gr.Number, reuse_seed: gr.Button, generation_info: gr.Textbox):
""" Connects a 'reuse subseed' button's click event so that it copies last used
subseed value from generation info the to the subseed. If subseed strength
def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info: gr.Textbox, dummy_component, is_subseed):
""" Connects a 'reuse (sub)seed' button's click event so that it copies last used
(sub)seed value from generation info the to the seed field. If copying subseed and subseed strength
was 0, i.e. no variation seed was used, it copies the normal seed value instead."""
def copy_seed(gen_info_string: str):
def copy_seed(gen_info_string: str, index):
res = -1
try:
gen_info = json.loads(gen_info_string)
subseed_strength = gen_info.get('subseed_strength', 0)
if subseed_strength > 0:
return gen_info.get('subseed', -1)
index -= gen_info.get('index_of_first_image', 0)
if is_subseed and gen_info.get('subseed_strength', 0) > 0:
all_subseeds = gen_info.get('all_subseeds', [-1])
res = all_subseeds[index if 0 <= index < len(all_subseeds) else 0]
else:
return gen_info.get('seed', -1)
all_seeds = gen_info.get('all_seeds', [-1])
res = all_seeds[index if 0 <= index < len(all_seeds) else 0]
except json.decoder.JSONDecodeError as e:
if gen_info_string != '':
print("Error parsing JSON generation info:", file=sys.stderr)
print(gen_info_string, file=sys.stderr)
return -1
return [res, gr_show(False)]
reuse_seed.click(
fn=copy_seed,
_js="(x, y) => [x, selected_gallery_index()]",
show_progress=False,
inputs=[generation_info],
outputs=[seed]
inputs=[generation_info, dummy_component],
outputs=[seed, dummy_component]
)
def create_toprow(is_img2img):
with gr.Row(elem_id="toprow"):
with gr.Column(scale=4):
@ -399,6 +385,7 @@ def setup_progressbar(progressbar, preview):
def create_ui(txt2img, img2img, run_extras, run_pnginfo):
with gr.Blocks(analytics_enabled=False) as txt2img_interface:
txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, txt2img_prompt_style_apply, txt2img_save_style = create_toprow(is_img2img=False)
dummy_component = gr.Label(visible=False)
with gr.Row().style(equal_height=False):
with gr.Column(variant='panel'):
@ -445,8 +432,8 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
html_info = gr.HTML()
generation_info = gr.Textbox(visible=False)
connect_reuse_seed(seed, reuse_seed, generation_info)
connect_reuse_subseed(subseed, reuse_subseed, generation_info)
connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
txt2img_args = dict(
fn=txt2img,
@ -487,11 +474,11 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
save.click(
fn=wrap_gradio_call(save_files),
_js = "(x, y, z) => [x, y, selected_gallery_index()]",
_js="(x, y, z) => [x, y, selected_gallery_index()]",
inputs=[
generation_info,
txt2img_gallery,
html_info
html_info,
],
outputs=[
html_info,
@ -583,8 +570,8 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
html_info = gr.HTML()
generation_info = gr.Textbox(visible=False)
connect_reuse_seed(seed, reuse_seed, generation_info)
connect_reuse_subseed(subseed, reuse_subseed, generation_info)
connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
def apply_mode(mode, uploadmask):
is_classic = mode == 0
@ -723,7 +710,6 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
prompts = [(txt2img_prompt, txt2img_negative_prompt), (img2img_prompt, img2img_negative_prompt)]
style_dropdowns = [(txt2img_prompt_style, txt2img_prompt_style2), (img2img_prompt_style, img2img_prompt_style2)]
dummy_component = gr.Label(visible=False)
for button, (prompt, negative_prompt) in zip([txt2img_save_style, img2img_save_style], prompts):
button.click(
fn=add_style,