Add an option for faster low quality previews
This commit is contained in:
parent
ca16278188
commit
11dd79e346
|
@ -106,20 +106,29 @@ def setup_img2img_steps(p, steps=None):
|
|||
return steps, t_enc
|
||||
|
||||
|
||||
def single_sample_to_image(sample):
|
||||
x_sample = processing.decode_first_stage(shared.sd_model, sample.unsqueeze(0))[0]
|
||||
def single_sample_to_image(sample, approximation=False):
|
||||
if approximation:
|
||||
# https://discuss.huggingface.co/t/decoding-latents-to-rgb-without-upscaling/23204/2
|
||||
coefs = torch.tensor(
|
||||
[[ 0.298, 0.207, 0.208],
|
||||
[ 0.187, 0.286, 0.173],
|
||||
[-0.158, 0.189, 0.264],
|
||||
[-0.184, -0.271, -0.473]]).to(sample.device)
|
||||
x_sample = torch.einsum("lxy,lr -> rxy", sample, coefs)
|
||||
else:
|
||||
x_sample = processing.decode_first_stage(shared.sd_model, sample.unsqueeze(0))[0]
|
||||
x_sample = torch.clamp((x_sample + 1.0) / 2.0, min=0.0, max=1.0)
|
||||
x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2)
|
||||
x_sample = x_sample.astype(np.uint8)
|
||||
return Image.fromarray(x_sample)
|
||||
|
||||
|
||||
def sample_to_image(samples, index=0):
|
||||
return single_sample_to_image(samples[index])
|
||||
def sample_to_image(samples, index=0, approximation=False):
|
||||
return single_sample_to_image(samples[index], approximation)
|
||||
|
||||
|
||||
def samples_to_image_grid(samples):
|
||||
return images.image_grid([single_sample_to_image(sample) for sample in samples])
|
||||
def samples_to_image_grid(samples, approximation=False):
|
||||
return images.image_grid([single_sample_to_image(sample, approximation) for sample in samples])
|
||||
|
||||
|
||||
def store_latent(decoded):
|
||||
|
@ -127,7 +136,7 @@ def store_latent(decoded):
|
|||
|
||||
if opts.show_progress_every_n_steps > 0 and shared.state.sampling_step % opts.show_progress_every_n_steps == 0:
|
||||
if not shared.parallel_processing_allowed:
|
||||
shared.state.current_image = sample_to_image(decoded)
|
||||
shared.state.current_image = sample_to_image(decoded, approximation=opts.show_progress_approximate)
|
||||
|
||||
|
||||
class InterruptedException(BaseException):
|
||||
|
|
|
@ -212,9 +212,9 @@ class State:
|
|||
|
||||
import modules.sd_samplers
|
||||
if opts.show_progress_grid:
|
||||
self.current_image = modules.sd_samplers.samples_to_image_grid(self.current_latent)
|
||||
self.current_image = modules.sd_samplers.samples_to_image_grid(self.current_latent, approximation=opts.show_progress_approximate)
|
||||
else:
|
||||
self.current_image = modules.sd_samplers.sample_to_image(self.current_latent)
|
||||
self.current_image = modules.sd_samplers.sample_to_image(self.current_latent, approximation=opts.show_progress_approximate)
|
||||
|
||||
self.current_image_sampling_step = self.sampling_step
|
||||
|
||||
|
@ -391,6 +391,7 @@ options_templates.update(options_section(('interrogate', "Interrogate Options"),
|
|||
options_templates.update(options_section(('ui', "User interface"), {
|
||||
"show_progressbar": OptionInfo(True, "Show progressbar"),
|
||||
"show_progress_every_n_steps": OptionInfo(0, "Show image creation progress every N sampling steps. Set to 0 to disable. Set to -1 to show after completion of batch.", gr.Slider, {"minimum": -1, "maximum": 32, "step": 1}),
|
||||
"show_progress_approximate": OptionInfo(False, "Calculate small previews using fast linear approximation instead of VAE"),
|
||||
"show_progress_grid": OptionInfo(True, "Show previews of all images generated in a batch as a grid"),
|
||||
"return_grid": OptionInfo(True, "Show grid in results for web"),
|
||||
"do_not_show_images": OptionInfo(False, "Do not show any images in results for web"),
|
||||
|
|
Loading…
Reference in New Issue
Block a user