From 4fdb53c1e9962507fc8336dad9a0fabfe6c418c0 Mon Sep 17 00:00:00 2001 From: Unnoen Date: Wed, 19 Oct 2022 21:38:10 +1100 Subject: Generate grid preview for progress image --- modules/sd_samplers.py | 26 +++++++++++++++++++++++++- 1 file changed, 25 insertions(+), 1 deletion(-) (limited to 'modules/sd_samplers.py') diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py index f58a29b9..74a480e5 100644 --- a/modules/sd_samplers.py +++ b/modules/sd_samplers.py @@ -7,7 +7,7 @@ import inspect import k_diffusion.sampling import ldm.models.diffusion.ddim import ldm.models.diffusion.plms -from modules import prompt_parser, devices, processing +from modules import prompt_parser, devices, processing, images from modules.shared import opts, cmd_opts, state import modules.shared as shared @@ -89,6 +89,30 @@ def sample_to_image(samples): x_sample = x_sample.astype(np.uint8) return Image.fromarray(x_sample) +def samples_to_image_grid(samples): + progress_images = [] + for i in range(len(samples)): + # Decode the samples individually to reduce VRAM usage at the cost of a bit of speed. + x_sample = processing.decode_first_stage(shared.sd_model, samples[i:i+1])[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) + progress_images.append(Image.fromarray(x_sample)) + + return images.image_grid(progress_images) + +def samples_to_image_grid_combined(samples): + progress_images = [] + # Decode all samples at once to increase speed at the cost of VRAM usage. + x_samples = processing.decode_first_stage(shared.sd_model, samples) + x_samples = torch.clamp((x_samples + 1.0) / 2.0, min=0.0, max=1.0) + + for x_sample in x_samples: + x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2) + x_sample = x_sample.astype(np.uint8) + progress_images.append(Image.fromarray(x_sample)) + + return images.image_grid(progress_images) def store_latent(decoded): state.current_latent = decoded -- cgit v1.2.1 From d213d6ca6f90094cb45c11e2f3cb37d25a8d1f94 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 22 Oct 2022 20:48:13 +0300 Subject: removed the option to use 2x more memory when generating previews added an option to always only show one image in previews removed duplicate code --- modules/sd_samplers.py | 35 ++++++++++------------------------- 1 file changed, 10 insertions(+), 25 deletions(-) (limited to 'modules/sd_samplers.py') diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py index 74a480e5..0b408a70 100644 --- a/modules/sd_samplers.py +++ b/modules/sd_samplers.py @@ -71,6 +71,7 @@ sampler_extra_params = { 'sample_dpm_2': ['s_churn', 's_tmin', 's_tmax', 's_noise'], } + def setup_img2img_steps(p, steps=None): if opts.img2img_fix_steps or steps is not None: steps = int((steps or p.steps) / min(p.denoising_strength, 0.999)) if p.denoising_strength > 0 else 0 @@ -82,37 +83,21 @@ def setup_img2img_steps(p, steps=None): return steps, t_enc -def sample_to_image(samples): - x_sample = processing.decode_first_stage(shared.sd_model, samples[0:1])[0] +def single_sample_to_image(sample): + 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): + return single_sample_to_image(samples[0]) + + def samples_to_image_grid(samples): - progress_images = [] - for i in range(len(samples)): - # Decode the samples individually to reduce VRAM usage at the cost of a bit of speed. - x_sample = processing.decode_first_stage(shared.sd_model, samples[i:i+1])[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) - progress_images.append(Image.fromarray(x_sample)) - - return images.image_grid(progress_images) - -def samples_to_image_grid_combined(samples): - progress_images = [] - # Decode all samples at once to increase speed at the cost of VRAM usage. - x_samples = processing.decode_first_stage(shared.sd_model, samples) - x_samples = torch.clamp((x_samples + 1.0) / 2.0, min=0.0, max=1.0) - - for x_sample in x_samples: - x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2) - x_sample = x_sample.astype(np.uint8) - progress_images.append(Image.fromarray(x_sample)) - - return images.image_grid(progress_images) + return images.image_grid([single_sample_to_image(sample) for sample in samples]) + def store_latent(decoded): state.current_latent = decoded -- cgit v1.2.1 From b38370275275bf6e11575000f39c50c6e90b1f7a Mon Sep 17 00:00:00 2001 From: ritosonn Date: Fri, 21 Oct 2022 23:46:32 +0900 Subject: fix #3145 #3093 --- modules/sd_samplers.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) (limited to 'modules/sd_samplers.py') diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py index 0b408a70..3670b57d 100644 --- a/modules/sd_samplers.py +++ b/modules/sd_samplers.py @@ -228,7 +228,7 @@ class VanillaStableDiffusionSampler: unconditional_conditioning = {"c_concat": [image_conditioning], "c_crossattn": [unconditional_conditioning]} - samples = self.launch_sampling(steps, lambda: self.sampler.decode(x1, conditioning, t_enc, unconditional_guidance_scale=p.cfg_scale, unconditional_conditioning=unconditional_conditioning)) + samples = self.launch_sampling(t_enc + 1, lambda: self.sampler.decode(x1, conditioning, t_enc, unconditional_guidance_scale=p.cfg_scale, unconditional_conditioning=unconditional_conditioning)) return samples @@ -429,7 +429,7 @@ class KDiffusionSampler: self.model_wrap_cfg.init_latent = x self.last_latent = x - samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, xi, extra_args={ + samples = self.launch_sampling(t_enc + 1, lambda: self.func(self.model_wrap_cfg, xi, extra_args={ 'cond': conditioning, 'image_cond': image_conditioning, 'uncond': unconditional_conditioning, -- cgit v1.2.1