diff --git a/html/logo-bg-dark.jpg b/html/logo-bg-dark.jpg index 713b5e57e..51a0b4093 100644 Binary files a/html/logo-bg-dark.jpg and b/html/logo-bg-dark.jpg differ diff --git a/html/logo-bg-light.jpg b/html/logo-bg-light.jpg index 3c7405dd4..9a694ba07 100644 Binary files a/html/logo-bg-light.jpg and b/html/logo-bg-light.jpg differ diff --git a/installer.py b/installer.py index 7471009d4..ea8914634 100644 --- a/installer.py +++ b/installer.py @@ -612,6 +612,7 @@ def set_environment(): os.environ.setdefault('NUMEXPR_MAX_THREADS', '16') os.environ.setdefault('PYTHONHTTPSVERIFY', '0') os.environ.setdefault('HF_HUB_DISABLE_TELEMETRY', '1') + os.environ.setdefault('HF_HUB_DISABLE_EXPERIMENTAL_WARNING', '1') os.environ.setdefault('UVICORN_TIMEOUT_KEEP_ALIVE', '60') if sys.platform == 'darwin': os.environ.setdefault('PYTORCH_ENABLE_MPS_FALLBACK', '1') diff --git a/javascript/black-orange.css b/javascript/black-orange.css index bb73497ff..4785afdfd 100644 --- a/javascript/black-orange.css +++ b/javascript/black-orange.css @@ -103,6 +103,9 @@ svg.feather.feather-image, .feather .feather-image { display: none } #txt2img_checkboxes, #img2img_checkboxes { background-color: transparent; } #txt2img_checkboxes, #img2img_checkboxes { margin-bottom: 0.2em; } #txt2img_gallery, #img2img_gallery, #extras_gallery { padding: 0; margin: 0; object-fit: contain; box-shadow: none; min-height: 0; } +#txt2img_actions_column, #img2img_actions_column { display: -webkit-box; -webkit-box-pack: justify; } +#txt2img_enqueue_wrapper, #img2img_enqueue_wrapper { min-width: unset; width: 48%; } +#txt2img_generate_box, #img2img_generate_box { min-width: unset; width: 48%; } #extras_upscale { margin-top: 10px } #txt2img_progress_row > div { min-width: var(--left-column); max-width: var(--left-column); } @@ -115,6 +118,7 @@ svg.feather.feather-image, .feather .feather-image { display: none } #txtimg_hr_finalres { max-width: 200px; } #pnginfo_html2_info { margin-top: -18px; background-color: var(--input-background-fill); padding: var(--input-padding) } #txt2img_tools > div > button, #img2img_tools > div > button { filter: hue-rotate(180deg) saturate(0.5); } +#txt2img_tools, #img2img_tools { margin-top: -5px; margin-bottom: -5px; } /* custom elements overrides */ #steps-animation, #controlnet { border-width: 0; } diff --git a/javascript/style.css b/javascript/style.css index d991ad755..9f663af1b 100644 --- a/javascript/style.css +++ b/javascript/style.css @@ -110,7 +110,6 @@ button.custom-button{ #txt2img_generate_line2 > button, #img2img_generate_line2 > button, #extras_generate_box > button { height: 2.2em; line-height: 0; min-width: unset; display: block !important; } #txt2img_tools > div, #img2img_tools > div { justify-content: space-around; margin-top: 0.5em; margin-bottom: 0em; } #txt2img_tools > div > button, #img2img_tools > div > button { scale: 120%; } -#refresh_txt2img_styles, #refresh_img2img_styles { height: 2.46em; margin-left: -8px; } .interrogate-col{ min-width: 0 !important; diff --git a/modules/processing.py b/modules/processing.py index c6189573f..82cf63415 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -950,13 +950,9 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): samples = self.sd_model.get_first_stage_encoding(self.sd_model.encode_first_stage(decoded_samples)) image_conditioning = self.img2img_image_conditioning(decoded_samples, samples) shared.state.nextjob() - img2img_sampler_name = self.sampler_name - force_latent_upscaler = shared.opts.data.get('force_latent_sampler') - if force_latent_upscaler != 'None' and force_latent_upscaler != 'PLMS': - img2img_sampler_name = force_latent_upscaler - if img2img_sampler_name == 'PLMS': - img2img_sampler_name = shared.opts.fallback_sampler if shared.opts.fallback_sampler != 'PLMS' else 'UniPC' - self.sampler = sd_samplers.create_sampler(img2img_sampler_name, self.sd_model) + if self.latent_sampler == "PLMS": + self.latent_sampler = 'UniPC' + self.sampler = sd_samplers.create_sampler(self.latent_sampler or self.sampler_name, self.sd_model) samples = samples[:, :, self.truncate_y//2:samples.shape[2]-(self.truncate_y+1)//2, self.truncate_x//2:samples.shape[3]-(self.truncate_x+1)//2] noise = create_random_tensors(samples.shape[1:], seeds=seeds, subseeds=subseeds, subseed_strength=subseed_strength, p=self) x = None