i
This commit is contained in:
parent
8a49b2a17e
commit
c6f93a29cf
@ -163,7 +163,7 @@ def ksampler(model, positive, negative, latent, seed=None, steps=30, cfg=7.0, sa
|
|||||||
def ksampler_with_refiner(model, positive, negative, refiner, refiner_positive, refiner_negative, latent,
|
def ksampler_with_refiner(model, positive, negative, refiner, refiner_positive, refiner_negative, latent,
|
||||||
seed=None, steps=30, refiner_switch_step=20, cfg=7.0, sampler_name='dpmpp_2m_sde_gpu',
|
seed=None, steps=30, refiner_switch_step=20, cfg=7.0, sampler_name='dpmpp_2m_sde_gpu',
|
||||||
scheduler='karras', denoise=1.0, disable_noise=False, start_step=None, last_step=None,
|
scheduler='karras', denoise=1.0, disable_noise=False, start_step=None, last_step=None,
|
||||||
force_full_denoise=False):
|
force_full_denoise=False, callback_function=None):
|
||||||
# SCHEDULERS = ["normal", "karras", "exponential", "simple", "ddim_uniform"]
|
# SCHEDULERS = ["normal", "karras", "exponential", "simple", "ddim_uniform"]
|
||||||
# SAMPLERS = ["euler", "euler_ancestral", "heun", "dpm_2", "dpm_2_ancestral",
|
# SAMPLERS = ["euler", "euler_ancestral", "heun", "dpm_2", "dpm_2_ancestral",
|
||||||
# "lms", "dpm_fast", "dpm_adaptive", "dpmpp_2s_ancestral", "dpmpp_sde", "dpmpp_sde_gpu",
|
# "lms", "dpm_fast", "dpm_adaptive", "dpmpp_2s_ancestral", "dpmpp_sde", "dpmpp_sde_gpu",
|
||||||
@ -189,6 +189,8 @@ def ksampler_with_refiner(model, positive, negative, refiner, refiner_positive,
|
|||||||
pbar = comfy.utils.ProgressBar(steps)
|
pbar = comfy.utils.ProgressBar(steps)
|
||||||
|
|
||||||
def callback(step, x0, x, total_steps):
|
def callback(step, x0, x, total_steps):
|
||||||
|
if callback_function is not None:
|
||||||
|
callback_function(step, x0, x, total_steps)
|
||||||
if previewer and step % 3 == 0:
|
if previewer and step % 3 == 0:
|
||||||
previewer.preview(x0, step, total_steps)
|
previewer.preview(x0, step, total_steps)
|
||||||
pbar.update_absolute(step + 1, total_steps, None)
|
pbar.update_absolute(step + 1, total_steps, None)
|
||||||
|
@ -17,7 +17,7 @@ xl_refiner = core.load_model(xl_refiner_filename)
|
|||||||
|
|
||||||
|
|
||||||
@torch.no_grad()
|
@torch.no_grad()
|
||||||
def process(positive_prompt, negative_prompt, steps, switch, width, height, image_seed):
|
def process(positive_prompt, negative_prompt, steps, switch, width, height, image_seed, callback):
|
||||||
positive_conditions = core.encode_prompt_condition(clip=xl_base.clip, prompt=positive_prompt)
|
positive_conditions = core.encode_prompt_condition(clip=xl_base.clip, prompt=positive_prompt)
|
||||||
negative_conditions = core.encode_prompt_condition(clip=xl_base.clip, prompt=negative_prompt)
|
negative_conditions = core.encode_prompt_condition(clip=xl_base.clip, prompt=negative_prompt)
|
||||||
|
|
||||||
@ -36,7 +36,8 @@ def process(positive_prompt, negative_prompt, steps, switch, width, height, imag
|
|||||||
refiner_switch_step=switch,
|
refiner_switch_step=switch,
|
||||||
latent=empty_latent,
|
latent=empty_latent,
|
||||||
steps=steps, start_step=0, last_step=steps, disable_noise=False, force_full_denoise=True,
|
steps=steps, start_step=0, last_step=steps, disable_noise=False, force_full_denoise=True,
|
||||||
seed=image_seed
|
seed=image_seed,
|
||||||
|
callback_function=callback
|
||||||
)
|
)
|
||||||
|
|
||||||
decoded_latent = core.decode_vae(vae=xl_refiner.vae, latent_image=sampled_latent)
|
decoded_latent = core.decode_vae(vae=xl_refiner.vae, latent_image=sampled_latent)
|
||||||
|
10
webui.py
10
webui.py
@ -25,8 +25,14 @@ def generate_clicked(prompt, negative_prompt, style_selction, performance_selcti
|
|||||||
if not isinstance(seed, int) or seed < 0 or seed > 65535:
|
if not isinstance(seed, int) or seed < 0 or seed > 65535:
|
||||||
seed = random.randint(1, 65535)
|
seed = random.randint(1, 65535)
|
||||||
|
|
||||||
for i in progress.tqdm(range(image_number)):
|
all_steps = steps * image_number
|
||||||
imgs = process(p_txt, n_txt, steps, switch, width, height, seed)
|
|
||||||
|
def callback(step, x0, x, total_steps):
|
||||||
|
done_steps = i * image_number + step
|
||||||
|
progress(float(done_steps) / float(all_steps), f'Step {step}/{total_steps} in the {i}-th Sampling')
|
||||||
|
|
||||||
|
for i in range(image_number):
|
||||||
|
imgs = process(p_txt, n_txt, steps, switch, width, height, seed, callback=callback)
|
||||||
seed += 1
|
seed += 1
|
||||||
results += imgs
|
results += imgs
|
||||||
|
|
||||||
|
Loading…
Reference in New Issue
Block a user