diff --git a/modules/api/api.py b/modules/api/api.py index 6c564ad89..5767ba904 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -286,7 +286,7 @@ class Api: # copy from check_progress_call of ui.py if shared.state.job_count == 0: - return ProgressResponse(progress=0, eta_relative=0, state=shared.state.dict()) + return ProgressResponse(progress=0, eta_relative=0, state=shared.state.dict(), textinfo=shared.state.textinfo) # avoid dividing zero progress = 0.01 @@ -308,7 +308,7 @@ class Api: if shared.state.current_image and not req.skip_current_image: current_image = encode_pil_to_base64(shared.state.current_image) - return ProgressResponse(progress=progress, eta_relative=eta_relative, state=shared.state.dict(), current_image=current_image) + return ProgressResponse(progress=progress, eta_relative=eta_relative, state=shared.state.dict(), current_image=current_image, textinfo=shared.state.textinfo) def interrogateapi(self, interrogatereq: InterrogateRequest): image_b64 = interrogatereq.image diff --git a/modules/api/models.py b/modules/api/models.py index 034b4aa0b..c78095caa 100644 --- a/modules/api/models.py +++ b/modules/api/models.py @@ -168,6 +168,7 @@ class ProgressResponse(BaseModel): eta_relative: float = Field(title="ETA in secs") state: dict = Field(title="State", description="The current state snapshot") current_image: str = Field(default=None, title="Current image", description="The current image in base64 format. opts.show_progress_every_n_steps is required for this to work.") + textinfo: str = Field(default=None, title="Info text", description="Info text used by WebUI.") class InterrogateRequest(BaseModel): image: str = Field(default="", title="Image", description="Image to work on, must be a Base64 string containing the image's data.") diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 300d3975f..194679e89 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -619,7 +619,9 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step, epoch_num = hypernetwork.step // steps_per_epoch epoch_step = hypernetwork.step % steps_per_epoch - pbar.set_description(f"[Epoch {epoch_num}: {epoch_step+1}/{steps_per_epoch}]loss: {loss_step:.7f}") + description = f"Training hypernetwork [Epoch {epoch_num}: {epoch_step+1}/{steps_per_epoch}]loss: {loss_step:.7f}" + pbar.set_description(description) + shared.state.textinfo = description if hypernetwork_dir is not None and steps_done % save_hypernetwork_every == 0: # Before saving, change name to match current checkpoint. hypernetwork_name_every = f'{hypernetwork_name}-{steps_done}' diff --git a/modules/img2img.py b/modules/img2img.py index ca58b5d87..f62783c61 100644 --- a/modules/img2img.py +++ b/modules/img2img.py @@ -59,38 +59,34 @@ def process_batch(p, input_dir, output_dir, args): processed_image.save(os.path.join(output_dir, filename)) -def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, init_img, init_img_with_mask, init_img_with_mask_orig, init_img_inpaint, init_mask_inpaint, mask_mode, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, *args): - is_inpaint = mode == 1 - is_batch = mode == 2 +def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, *args): + is_batch = mode == 5 - if is_inpaint: - # Drawn mask - if mask_mode == 0: - is_mask_sketch = isinstance(init_img_with_mask, dict) - is_mask_paint = not is_mask_sketch - if is_mask_sketch: - # Sketch: mask iff. not transparent - image, mask = init_img_with_mask["image"], init_img_with_mask["mask"] - alpha_mask = ImageOps.invert(image.split()[-1]).convert('L').point(lambda x: 255 if x > 0 else 0, mode='1') - mask = ImageChops.lighter(alpha_mask, mask.convert('L')).convert('L') - else: - # Color-sketch: mask iff. painted over - image = init_img_with_mask - orig = init_img_with_mask_orig or init_img_with_mask - pred = np.any(np.array(image) != np.array(orig), axis=-1) - mask = Image.fromarray(pred.astype(np.uint8) * 255, "L") - mask = ImageEnhance.Brightness(mask).enhance(1 - mask_alpha / 100) - blur = ImageFilter.GaussianBlur(mask_blur) - image = Image.composite(image.filter(blur), orig, mask.filter(blur)) - - image = image.convert("RGB") - # Uploaded mask - else: - image = init_img_inpaint - mask = init_mask_inpaint - # No mask + if mode == 0: # img2img + image = init_img.convert("RGB") + mask = None + elif mode == 1: # img2img sketch + image = sketch.convert("RGB") + mask = None + elif mode == 2: # inpaint + image, mask = init_img_with_mask["image"], init_img_with_mask["mask"] + alpha_mask = ImageOps.invert(image.split()[-1]).convert('L').point(lambda x: 255 if x > 0 else 0, mode='1') + mask = ImageChops.lighter(alpha_mask, mask.convert('L')).convert('L') + image = image.convert("RGB") + elif mode == 3: # inpaint sketch + image = inpaint_color_sketch + orig = inpaint_color_sketch_orig or inpaint_color_sketch + pred = np.any(np.array(image) != np.array(orig), axis=-1) + mask = Image.fromarray(pred.astype(np.uint8) * 255, "L") + mask = ImageEnhance.Brightness(mask).enhance(1 - mask_alpha / 100) + blur = ImageFilter.GaussianBlur(mask_blur) + image = Image.composite(image.filter(blur), orig, mask.filter(blur)) + image = image.convert("RGB") + elif mode == 4: # inpaint upload mask + image = init_img_inpaint + mask = init_mask_inpaint else: - image = init_img + image = None mask = None # Use the EXIF orientation of photos taken by smartphones. diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py index f70872c46..870218db8 100644 --- a/modules/prompt_parser.py +++ b/modules/prompt_parser.py @@ -49,6 +49,8 @@ def get_learned_conditioning_prompt_schedules(prompts, steps): [[5, 'a c'], [10, 'a {b|d{ c']] >>> g("((a][:b:c [d:3]") [[3, '((a][:b:c '], [10, '((a][:b:c d']] + >>> g("[a|(b:1.1)]") + [[1, 'a'], [2, '(b:1.1)'], [3, 'a'], [4, '(b:1.1)'], [5, 'a'], [6, '(b:1.1)'], [7, 'a'], [8, '(b:1.1)'], [9, 'a'], [10, '(b:1.1)']] """ def collect_steps(steps, tree): @@ -84,7 +86,7 @@ def get_learned_conditioning_prompt_schedules(prompts, steps): yield args[0].value def __default__(self, data, children, meta): for child in children: - yield from child + yield child return AtStep().transform(tree) def get_schedule(prompt): diff --git a/modules/sd_disable_initialization.py b/modules/sd_disable_initialization.py index 088ac24be..c72d8efca 100644 --- a/modules/sd_disable_initialization.py +++ b/modules/sd_disable_initialization.py @@ -20,6 +20,19 @@ class DisableInitialization: ``` """ + def __init__(self): + self.replaced = [] + + def replace(self, obj, field, func): + original = getattr(obj, field, None) + if original is None: + return None + + self.replaced.append((obj, field, original)) + setattr(obj, field, func) + + return original + def __enter__(self): def do_nothing(*args, **kwargs): pass @@ -37,11 +50,14 @@ class DisableInitialization: def transformers_utils_hub_get_file_from_cache(original, url, *args, **kwargs): # this file is always 404, prevent making request - if url == 'https://huggingface.co/openai/clip-vit-large-patch14/resolve/main/added_tokens.json': - raise transformers.utils.hub.EntryNotFoundError + if url == 'https://huggingface.co/openai/clip-vit-large-patch14/resolve/main/added_tokens.json' or url == 'openai/clip-vit-large-patch14' and args[0] == 'added_tokens.json': + return None try: - return original(url, *args, local_files_only=True, **kwargs) + res = original(url, *args, local_files_only=True, **kwargs) + if res is None: + res = original(url, *args, local_files_only=False, **kwargs) + return res except Exception as e: return original(url, *args, local_files_only=False, **kwargs) @@ -54,42 +70,19 @@ class DisableInitialization: def transformers_configuration_utils_cached_file(url, *args, local_files_only=False, **kwargs): return transformers_utils_hub_get_file_from_cache(self.transformers_configuration_utils_cached_file, url, *args, **kwargs) - self.init_kaiming_uniform = torch.nn.init.kaiming_uniform_ - self.init_no_grad_normal = torch.nn.init._no_grad_normal_ - self.init_no_grad_uniform_ = torch.nn.init._no_grad_uniform_ - self.create_model_and_transforms = open_clip.create_model_and_transforms - self.CLIPTextModel_from_pretrained = ldm.modules.encoders.modules.CLIPTextModel.from_pretrained - self.transformers_modeling_utils_load_pretrained_model = getattr(transformers.modeling_utils.PreTrainedModel, '_load_pretrained_model', None) - self.transformers_tokenization_utils_base_cached_file = getattr(transformers.tokenization_utils_base, 'cached_file', None) - self.transformers_configuration_utils_cached_file = getattr(transformers.configuration_utils, 'cached_file', None) - self.transformers_utils_hub_get_from_cache = getattr(transformers.utils.hub, 'get_from_cache', None) - - torch.nn.init.kaiming_uniform_ = do_nothing - torch.nn.init._no_grad_normal_ = do_nothing - torch.nn.init._no_grad_uniform_ = do_nothing - open_clip.create_model_and_transforms = create_model_and_transforms_without_pretrained - ldm.modules.encoders.modules.CLIPTextModel.from_pretrained = CLIPTextModel_from_pretrained - if self.transformers_modeling_utils_load_pretrained_model is not None: - transformers.modeling_utils.PreTrainedModel._load_pretrained_model = transformers_modeling_utils_load_pretrained_model - if self.transformers_tokenization_utils_base_cached_file is not None: - transformers.tokenization_utils_base.cached_file = transformers_tokenization_utils_base_cached_file - if self.transformers_configuration_utils_cached_file is not None: - transformers.configuration_utils.cached_file = transformers_configuration_utils_cached_file - if self.transformers_utils_hub_get_from_cache is not None: - transformers.utils.hub.get_from_cache = transformers_utils_hub_get_from_cache + self.replace(torch.nn.init, 'kaiming_uniform_', do_nothing) + self.replace(torch.nn.init, '_no_grad_normal_', do_nothing) + self.replace(torch.nn.init, '_no_grad_uniform_', do_nothing) + self.create_model_and_transforms = self.replace(open_clip, 'create_model_and_transforms', create_model_and_transforms_without_pretrained) + self.CLIPTextModel_from_pretrained = self.replace(ldm.modules.encoders.modules.CLIPTextModel, 'from_pretrained', CLIPTextModel_from_pretrained) + self.transformers_modeling_utils_load_pretrained_model = self.replace(transformers.modeling_utils.PreTrainedModel, '_load_pretrained_model', transformers_modeling_utils_load_pretrained_model) + self.transformers_tokenization_utils_base_cached_file = self.replace(transformers.tokenization_utils_base, 'cached_file', transformers_tokenization_utils_base_cached_file) + self.transformers_configuration_utils_cached_file = self.replace(transformers.configuration_utils, 'cached_file', transformers_configuration_utils_cached_file) + self.transformers_utils_hub_get_from_cache = self.replace(transformers.utils.hub, 'get_from_cache', transformers_utils_hub_get_from_cache) def __exit__(self, exc_type, exc_val, exc_tb): - torch.nn.init.kaiming_uniform_ = self.init_kaiming_uniform - torch.nn.init._no_grad_normal_ = self.init_no_grad_normal - torch.nn.init._no_grad_uniform_ = self.init_no_grad_uniform_ - open_clip.create_model_and_transforms = self.create_model_and_transforms - ldm.modules.encoders.modules.CLIPTextModel.from_pretrained = self.CLIPTextModel_from_pretrained - if self.transformers_modeling_utils_load_pretrained_model is not None: - transformers.modeling_utils.PreTrainedModel._load_pretrained_model = self.transformers_modeling_utils_load_pretrained_model - if self.transformers_tokenization_utils_base_cached_file is not None: - transformers.utils.hub.cached_file = self.transformers_tokenization_utils_base_cached_file - if self.transformers_configuration_utils_cached_file is not None: - transformers.utils.hub.cached_file = self.transformers_configuration_utils_cached_file - if self.transformers_utils_hub_get_from_cache is not None: - transformers.utils.hub.get_from_cache = self.transformers_utils_hub_get_from_cache + for obj, field, original in self.replaced: + setattr(obj, field, original) + + self.replaced.clear() diff --git a/modules/sd_models.py b/modules/sd_models.py index fef5e15e9..764dbda6e 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -334,6 +334,7 @@ def load_model(checkpoint_info=None): timer = Timer() sd_model = None + try: with sd_disable_initialization.DisableInitialization(): sd_model = instantiate_from_config(sd_config.model) diff --git a/modules/shared.py b/modules/shared.py index 0ef254c7e..f43f6ce83 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -74,8 +74,8 @@ parser.add_argument("--freeze-settings", action='store_true', help="disable edit parser.add_argument("--ui-settings-file", type=str, help="filename to use for ui settings", default=os.path.join(script_path, 'config.json')) parser.add_argument("--gradio-debug", action='store_true', help="launch gradio with --debug option") parser.add_argument("--gradio-auth", type=str, help='set gradio authentication like "username:password"; or comma-delimit multiple like "u1:p1,u2:p2,u3:p3"', default=None) -parser.add_argument("--gradio-img2img-tool", type=str, help='gradio image uploader tool: can be either editor for ctopping, or color-sketch for drawing', choices=["color-sketch", "editor"], default="editor") -parser.add_argument("--gradio-inpaint-tool", type=str, choices=["sketch", "color-sketch"], default="sketch", help="gradio inpainting editor: can be either sketch to only blur/noise the input, or color-sketch to paint over it") +parser.add_argument("--gradio-img2img-tool", type=str, help='does not do anything') +parser.add_argument("--gradio-inpaint-tool", type=str, help="does not do anything") parser.add_argument("--opt-channelslast", action='store_true', help="change memory type for stable diffusion to channels last") parser.add_argument("--styles-file", type=str, help="filename to use for styles", default=os.path.join(script_path, 'styles.csv')) parser.add_argument("--autolaunch", action='store_true', help="open the webui URL in the system's default browser upon launch", default=False) diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py index feb876c62..3c1042ada 100644 --- a/modules/textual_inversion/preprocess.py +++ b/modules/textual_inversion/preprocess.py @@ -135,7 +135,8 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre params.process_caption_deepbooru = process_caption_deepbooru params.preprocess_txt_action = preprocess_txt_action - for index, imagefile in enumerate(tqdm.tqdm(files)): + pbar = tqdm.tqdm(files) + for index, imagefile in enumerate(pbar): params.subindex = 0 filename = os.path.join(src, imagefile) try: @@ -143,6 +144,10 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre except Exception: continue + description = f"Preprocessing [Image {index}/{len(files)}]" + pbar.set_description(description) + shared.state.textinfo = description + params.src = filename existing_caption = None diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index 4196d3a58..b575f31f0 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -476,7 +476,9 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_ epoch_num = embedding.step // steps_per_epoch epoch_step = embedding.step % steps_per_epoch - pbar.set_description(f"[Epoch {epoch_num}: {epoch_step+1}/{steps_per_epoch}]loss: {loss_step:.7f}") + description = f"Training textual inversion [Epoch {epoch_num}: {epoch_step+1}/{steps_per_epoch}]loss: {loss_step:.7f}" + pbar.set_description(description) + shared.state.textinfo = description if embedding_dir is not None and steps_done % save_embedding_every == 0: # Before saving, change name to match current checkpoint. embedding_name_every = f'{embedding_name}-{steps_done}' diff --git a/modules/ui.py b/modules/ui.py index 8c7be8d03..cc0a1cb20 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -795,53 +795,67 @@ def create_ui(): with FormRow().style(equal_height=False): with gr.Column(variant='panel', elem_id="img2img_settings"): + with gr.Tabs(elem_id="mode_img2img"): + with gr.TabItem('img2img', id='img2img', elem_id="img2img_img2img_tab") as tab_img2img: + init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool="editor", image_mode="RGBA").style(height=480) - with gr.Tabs(elem_id="mode_img2img") as tabs_img2img_mode: - with gr.TabItem('img2img', id='img2img', elem_id="img2img_img2img_tab"): - init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool=cmd_opts.gradio_img2img_tool, image_mode="RGBA").style(height=480) + with gr.TabItem('Sketch', id='img2img_sketch', elem_id="img2img_img2img_sketch_tab") as tab_sketch: + sketch = gr.Image(label="Image for img2img", elem_id="img2img_sketch", show_label=False, source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGBA").style(height=480) - with gr.TabItem('Inpaint', id='inpaint', elem_id="img2img_inpaint_tab"): - init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool=cmd_opts.gradio_inpaint_tool, image_mode="RGBA").style(height=480) - init_img_with_mask_orig = gr.State(None) + with gr.TabItem('Inpaint', id='inpaint', elem_id="img2img_inpaint_tab") as tab_inpaint: + init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool="sketch", image_mode="RGBA").style(height=480) - use_color_sketch = cmd_opts.gradio_inpaint_tool == "color-sketch" - if use_color_sketch: - def update_orig(image, state): - if image is not None: - same_size = state is not None and state.size == image.size - has_exact_match = np.any(np.all(np.array(image) == np.array(state), axis=-1)) - edited = same_size and has_exact_match - return image if not edited or state is None else state + with gr.TabItem('Inpaint sketch', id='inpaint_sketch', elem_id="img2img_inpaint_sketch_tab") as tab_inpaint_color: + inpaint_color_sketch = gr.Image(label="Color sketch inpainting", show_label=False, elem_id="inpaint_sketch", source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGBA").style(height=480) + inpaint_color_sketch_orig = gr.State(None) - init_img_with_mask.change(update_orig, [init_img_with_mask, init_img_with_mask_orig], init_img_with_mask_orig) + def update_orig(image, state): + if image is not None: + same_size = state is not None and state.size == image.size + has_exact_match = np.any(np.all(np.array(image) == np.array(state), axis=-1)) + edited = same_size and has_exact_match + return image if not edited or state is None else state - init_img_inpaint = gr.Image(label="Image for img2img", show_label=False, source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_base") - init_mask_inpaint = gr.Image(label="Mask", source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_mask") + inpaint_color_sketch.change(update_orig, [inpaint_color_sketch, inpaint_color_sketch_orig], inpaint_color_sketch_orig) - with FormRow(): - mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, elem_id="img2img_mask_blur") - mask_alpha = gr.Slider(label="Mask transparency", interactive=use_color_sketch, visible=use_color_sketch, elem_id="img2img_mask_alpha") + with gr.TabItem('Inpaint upload', id='inpaint_upload', elem_id="img2img_inpaint_upload_tab") as tab_inpaint_upload: + init_img_inpaint = gr.Image(label="Image for img2img", show_label=False, source="upload", interactive=True, type="pil", elem_id="img_inpaint_base") + init_mask_inpaint = gr.Image(label="Mask", source="upload", interactive=True, type="pil", elem_id="img_inpaint_mask") - with FormRow(): - mask_mode = gr.Radio(label="Mask source", choices=["Draw mask", "Upload mask"], type="index", value="Draw mask", elem_id="mask_mode") - inpainting_mask_invert = gr.Radio(label='Mask mode', choices=['Inpaint masked', 'Inpaint not masked'], value='Inpaint masked', type="index", elem_id="img2img_mask_mode") - - with FormRow(): - inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='original', type="index", elem_id="img2img_inpainting_fill") - - with FormRow(): - with gr.Column(): - inpaint_full_res = gr.Radio(label="Inpaint area", choices=["Whole picture", "Only masked"], type="index", value="Whole picture", elem_id="img2img_inpaint_full_res") - - with gr.Column(scale=4): - inpaint_full_res_padding = gr.Slider(label='Only masked padding, pixels', minimum=0, maximum=256, step=4, value=32, elem_id="img2img_inpaint_full_res_padding") - - with gr.TabItem('Batch img2img', id='batch', elem_id="img2img_batch_tab"): + with gr.TabItem('Batch', id='batch', elem_id="img2img_batch_tab") as tab_batch: hidden = '
Disabled when launched with --hide-ui-dir-config.' if shared.cmd_opts.hide_ui_dir_config else '' gr.HTML(f"

Process images in a directory on the same machine where the server is running.
Use an empty output directory to save pictures normally instead of writing to the output directory.{hidden}

") img2img_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, elem_id="img2img_batch_input_dir") img2img_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, elem_id="img2img_batch_output_dir") + with FormGroup(elem_id="inpaint_controls", visible=False) as inpaint_controls: + with FormRow(): + mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, elem_id="img2img_mask_blur") + mask_alpha = gr.Slider(label="Mask transparency", visible=False, elem_id="img2img_mask_alpha") + + with FormRow(): + inpainting_mask_invert = gr.Radio(label='Mask mode', choices=['Inpaint masked', 'Inpaint not masked'], value='Inpaint masked', type="index", elem_id="img2img_mask_mode") + + with FormRow(): + inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='original', type="index", elem_id="img2img_inpainting_fill") + + with FormRow(): + with gr.Column(): + inpaint_full_res = gr.Radio(label="Inpaint area", choices=["Whole picture", "Only masked"], type="index", value="Whole picture", elem_id="img2img_inpaint_full_res") + + with gr.Column(scale=4): + inpaint_full_res_padding = gr.Slider(label='Only masked padding, pixels', minimum=0, maximum=256, step=4, value=32, elem_id="img2img_inpaint_full_res_padding") + + def select_img2img_tab(tab): + return gr.update(visible=tab in [2, 3, 4]), gr.update(visible=tab == 3), + + for i, elem in enumerate([tab_img2img, tab_sketch, tab_inpaint, tab_inpaint_color, tab_inpaint_upload, tab_batch]): + elem.select( + fn=lambda tab=i: select_img2img_tab(tab), + inputs=[], + outputs=[inpaint_controls, mask_alpha], + ) + with FormRow(): resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", choices=["Just resize", "Crop and resize", "Resize and fill", "Just resize (latent upscale)"], type="index", value="Just resize") @@ -900,20 +914,6 @@ def create_ui(): ] ) - mask_mode.change( - lambda mode, img: { - init_img_with_mask: gr_show(mode == 0), - init_img_inpaint: gr_show(mode == 1), - init_mask_inpaint: gr_show(mode == 1), - }, - inputs=[mask_mode, init_img_with_mask], - outputs=[ - init_img_with_mask, - init_img_inpaint, - init_mask_inpaint, - ], - ) - img2img_args = dict( fn=wrap_gradio_gpu_call(modules.img2img.img2img, extra_outputs=[None, '', '']), _js="submit_img2img", @@ -924,11 +924,12 @@ def create_ui(): img2img_prompt_style, img2img_prompt_style2, init_img, + sketch, init_img_with_mask, - init_img_with_mask_orig, + inpaint_color_sketch, + inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, - mask_mode, steps, sampler_index, mask_blur, diff --git a/style.css b/style.css index ec5e41827..ffd6307f2 100644 --- a/style.css +++ b/style.css @@ -557,7 +557,9 @@ canvas[key="mask"] { } #img2img_image, #img2img_image > .h-60, #img2img_image > .h-60 > div, #img2img_image > .h-60 > div > img, -img2maskimg, #img2maskimg > .h-60, #img2maskimg > .h-60 > div, #img2maskimg > .h-60 > div > img +#img2img_sketch, #img2img_sketch > .h-60, #img2img_sketch > .h-60 > div, #img2img_sketch > .h-60 > div > img, +#img2maskimg, #img2maskimg > .h-60, #img2maskimg > .h-60 > div, #img2maskimg > .h-60 > div > img, +#inpaint_sketch, #inpaint_sketch > .h-60, #inpaint_sketch > .h-60 > div, #inpaint_sketch > .h-60 > div > img { height: 480px !important; max-height: 480px !important;