Mirrors
/
stable-diffusion-webui
mirror of https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

Add Denoising Strength to output parameters in the output text

This commit is contained in:
AUTOMATIC 2022-08-26 09:02:21 +03:00
parent 5e83e7081a
commit 055dd10aae
1 changed files with 19 additions and 7 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

26
webui.py
View File

@ -547,7 +547,7 @@ def get_learned_conditioning_with_embeddings(model, prompts):
return model.get_learned_conditioning(prompts) return model.get_learned_conditioning(prompts)
def process_images(outpath, func_init, func_sample, prompt, seed, sampler_index, batch_size, n_iter, steps, cfg_scale, width, height, prompt_matrix, use_GFPGAN, do_not_save_grid=False): def process_images(outpath, func_init, func_sample, prompt, seed, sampler_index, batch_size, n_iter, steps, cfg_scale, width, height, prompt_matrix, use_GFPGAN, do_not_save_grid=False, extra_generation_params=None):
"""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""" """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"""
assert prompt is not None assert prompt is not None
@ -598,11 +598,21 @@ def process_images(outpath, func_init, func_sample, prompt, seed, sampler_index,
all_prompts = batch_size * n_iter * [prompt] all_prompts = batch_size * n_iter * [prompt]
all_seeds = [seed + x for x in range(len(all_prompts))] all_seeds = [seed + x for x in range(len(all_prompts))]
generation_params = {
"Steps": steps,
"Sampler": samplers[sampler_index].name,
"CFG scale": cfg_scale,
"Seed": seed,
"GFPGAN": ("GFPGAN" if use_GFPGAN and GFPGAN is not None else None)
}
if extra_generation_params is not None:
generation_params.update(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])
def infotext(): def infotext():
return f""" return f"{prompt}\n{generation_params_text}".strip() + "".join(["\n\n" + x for x in comments])
{prompt}
Steps: {steps}, Sampler: {samplers[sampler_index].name}, CFG scale: {cfg_scale}, Seed: {seed}{', GFPGAN' if use_GFPGAN and GFPGAN is not None else ''}
""".strip() + "".join(["\n\n" + x for x in comments])
if os.path.exists(cmd_opts.embeddings_dir): if os.path.exists(cmd_opts.embeddings_dir):
text_inversion_embeddings.load(cmd_opts.embeddings_dir, model) text_inversion_embeddings.load(cmd_opts.embeddings_dir, model)
@ -824,7 +834,8 @@ def img2img(prompt: str, init_img, ddim_steps: int, use_GFPGAN: bool, prompt_mat
height=height, height=height,
prompt_matrix=prompt_matrix, prompt_matrix=prompt_matrix,
use_GFPGAN=use_GFPGAN, use_GFPGAN=use_GFPGAN,
do_not_save_grid=True do_not_save_grid=True,
extra_generation_params = {"Denoising Strength": denoising_strength},
) )
if initial_seed is None: if initial_seed is None:
@ -858,7 +869,8 @@ def img2img(prompt: str, init_img, ddim_steps: int, use_GFPGAN: bool, prompt_mat
width=width, width=width,
height=height, height=height,
prompt_matrix=prompt_matrix, prompt_matrix=prompt_matrix,
use_GFPGAN=use_GFPGAN use_GFPGAN=use_GFPGAN,
extra_generation_params = {"Denoising Strength": denoising_strength},
) )
del sampler del sampler