+Loss: {losses.mean():.7f}
+Step: {embedding.step}
+Last prompt: {html.escape(text)}
+Last saved embedding: {html.escape(last_saved_file)}
+Last saved image: {html.escape(last_saved_image)}
+
" + "
\n".join([f"{html.escape(x)}" for x in text.split('\n')]) + "
Time taken:
Time taken:
{progressbar}
", preview_visibility, image + if shared.state.textinfo is not None: + textinfo_result = gr.HTML.update(value=shared.state.textinfo, visible=True) + else: + textinfo_result = gr_show(False) + + return f"{progressbar}
", preview_visibility, image, textinfo_result def check_progress_call_initial(id_part): shared.state.job_count = -1 shared.state.current_latent = None shared.state.current_image = None + shared.state.textinfo = None return check_progress_call(id_part) @@ -345,11 +365,24 @@ def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info: outputs=[seed, dummy_component] ) -def update_token_counter(text): - tokens, token_count, max_length = model_hijack.tokenize(text) + +def update_token_counter(text, steps): + try: + _, prompt_flat_list, _ = prompt_parser.get_multicond_prompt_list([text]) + prompt_schedules = prompt_parser.get_learned_conditioning_prompt_schedules(prompt_flat_list, steps) + + except Exception: + # a parsing error can happen here during typing, and we don't want to bother the user with + # messages related to it in console + prompt_schedules = [[[steps, text]]] + + flat_prompts = reduce(lambda list1, list2: list1+list2, prompt_schedules) + prompts = [prompt_text for step, prompt_text in flat_prompts] + tokens, token_count, max_length = max([model_hijack.tokenize(prompt) for prompt in prompts], key=lambda args: args[1]) style_class = ' class="red"' if (token_count > max_length) else "" return f"{token_count}/{max_length}" + def create_toprow(is_img2img): id_part = "img2img" if is_img2img else "txt2img" @@ -364,8 +397,7 @@ def create_toprow(is_img2img): roll = gr.Button(value=art_symbol, elem_id="roll", visible=len(shared.artist_db.artists) > 0) paste = gr.Button(value=paste_symbol, elem_id="paste") token_counter = gr.HTML(value="", elem_id=f"{id_part}_token_counter") - hidden_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button") - hidden_button.click(fn=update_token_counter, inputs=[prompt], outputs=[token_counter]) + token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button") with gr.Column(scale=10, elem_id="style_pos_col"): prompt_style = gr.Dropdown(label="Style 1", elem_id=f"{id_part}_style_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())), visible=len(shared.prompt_styles.styles) > 1) @@ -380,7 +412,7 @@ def create_toprow(is_img2img): with gr.Column(scale=1): with gr.Row(): interrupt = gr.Button('Interrupt', elem_id=f"{id_part}_interrupt") - submit = gr.Button('Generate', elem_id="generate", variant='primary') + submit = gr.Button('Generate', elem_id=f"{id_part}_generate", variant='primary') interrupt.click( fn=lambda: shared.state.interrupt(), @@ -396,16 +428,19 @@ def create_toprow(is_img2img): prompt_style_apply = gr.Button('Apply style', elem_id="style_apply") save_style = gr.Button('Create style', elem_id="style_create") - return prompt, roll, prompt_style, negative_prompt, prompt_style2, submit, interrogate, prompt_style_apply, save_style, paste + return prompt, roll, prompt_style, negative_prompt, prompt_style2, submit, interrogate, prompt_style_apply, save_style, paste, token_counter, token_button -def setup_progressbar(progressbar, preview, id_part): +def setup_progressbar(progressbar, preview, id_part, textinfo=None): + if textinfo is None: + textinfo = gr.HTML(visible=False) + check_progress = gr.Button('Check progress', elem_id=f"{id_part}_check_progress", visible=False) check_progress.click( fn=lambda: check_progress_call(id_part), show_progress=False, inputs=[], - outputs=[progressbar, preview, preview], + outputs=[progressbar, preview, preview, textinfo], ) check_progress_initial = gr.Button('Check progress (first)', elem_id=f"{id_part}_check_progress_initial", visible=False) @@ -413,13 +448,16 @@ def setup_progressbar(progressbar, preview, id_part): fn=lambda: check_progress_call_initial(id_part), show_progress=False, inputs=[], - outputs=[progressbar, preview, preview], + outputs=[progressbar, preview, preview, textinfo], ) -def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): +def create_ui(wrap_gradio_gpu_call): + import modules.img2img + import modules.txt2img + with gr.Blocks(analytics_enabled=False) as txt2img_interface: - txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, txt2img_prompt_style_apply, txt2img_save_style, paste = create_toprow(is_img2img=False) + txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, txt2img_prompt_style_apply, txt2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=False) dummy_component = gr.Label(visible=False) with gr.Row(elem_id='txt2img_progress_row'): @@ -483,7 +521,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True) txt2img_args = dict( - fn=txt2img, + fn=wrap_gradio_gpu_call(modules.txt2img.txt2img), _js="submit", inputs=[ txt2img_prompt, @@ -539,6 +577,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): roll.click( fn=roll_artist, + _js="update_txt2img_tokens", inputs=[ txt2img_prompt, ], @@ -567,9 +606,10 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): (hr_options, lambda d: gr.Row.update(visible="Denoising strength" in d)), ] modules.generation_parameters_copypaste.connect_paste(paste, txt2img_paste_fields, txt2img_prompt) + token_button.click(fn=update_token_counter, inputs=[txt2img_prompt, steps], outputs=[token_counter]) with gr.Blocks(analytics_enabled=False) as img2img_interface: - img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_prompt_style_apply, img2img_save_style, paste = create_toprow(is_img2img=True) + img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_prompt_style_apply, img2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=True) with gr.Row(elem_id='img2img_progress_row'): with gr.Column(scale=1): @@ -585,7 +625,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): with gr.Tabs(elem_id="mode_img2img") as tabs_img2img_mode: with gr.TabItem('img2img', id='img2img'): - init_img = gr.Image(label="Image for img2img", show_label=False, source="upload", interactive=True, type="pil") + 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) with gr.TabItem('Inpaint', id='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") @@ -599,7 +639,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): mask_mode = gr.Radio(label="Mask mode", show_label=False, choices=["Draw mask", "Upload mask"], type="index", value="Draw mask", elem_id="mask_mode") inpainting_mask_invert = gr.Radio(label='Masking mode', show_label=False, choices=['Inpaint masked', 'Inpaint not masked'], value='Inpaint masked', type="index") - inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='fill', type="index") + inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='original', type="index") with gr.Row(): inpaint_full_res = gr.Checkbox(label='Inpaint at full resolution', value=False) @@ -607,7 +647,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): with gr.TabItem('Batch img2img', id='batch'): hidden = 'Process images in a directory on the same machine where the server is running.{hidden}
") + 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}
A merger of the two checkpoints will be generated in your checkpoint directory.
") - + with gr.Row(): primary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary Model Name") secondary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_secondary_model_name", label="Secondary Model Name") @@ -896,10 +940,134 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): interp_method = gr.Radio(choices=["Weighted Sum", "Sigmoid", "Inverse Sigmoid"], value="Weighted Sum", label="Interpolation Method") save_as_half = gr.Checkbox(value=False, label="Safe as float16") modelmerger_merge = gr.Button(elem_id="modelmerger_merge", label="Merge", variant='primary') - + with gr.Column(variant='panel'): submit_result = gr.Textbox(elem_id="modelmerger_result", show_label=False) + sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings() + + with gr.Blocks() as textual_inversion_interface: + with gr.Row().style(equal_height=False): + with gr.Column(): + with gr.Group(): + gr.HTML(value="See wiki for detailed explanation.
") + + gr.HTML(value="Create a new embedding
") + + new_embedding_name = gr.Textbox(label="Name") + initialization_text = gr.Textbox(label="Initialization text", value="*") + nvpt = gr.Slider(label="Number of vectors per token", minimum=1, maximum=75, step=1, value=1) + + with gr.Row(): + with gr.Column(scale=3): + gr.HTML(value="") + + with gr.Column(): + create_embedding = gr.Button(value="Create", variant='primary') + + with gr.Group(): + gr.HTML(value="Preprocess images
") + + process_src = gr.Textbox(label='Source directory') + process_dst = gr.Textbox(label='Destination directory') + + with gr.Row(): + process_flip = gr.Checkbox(label='Flip') + process_split = gr.Checkbox(label='Split into two') + process_caption = gr.Checkbox(label='Add caption') + + with gr.Row(): + with gr.Column(scale=3): + gr.HTML(value="") + + with gr.Column(): + run_preprocess = gr.Button(value="Preprocess", variant='primary') + + with gr.Group(): + gr.HTML(value="Train an embedding; must specify a directory with a set of 512x512 images
") + train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())) + learn_rate = gr.Number(label='Learning rate', value=5.0e-03) + dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images") + log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion") + template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt")) + steps = gr.Number(label='Max steps', value=100000, precision=0) + create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0) + save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0) + + with gr.Row(): + with gr.Column(scale=2): + gr.HTML(value="") + + with gr.Column(): + with gr.Row(): + interrupt_training = gr.Button(value="Interrupt") + train_embedding = gr.Button(value="Train", variant='primary') + + with gr.Column(): + progressbar = gr.HTML(elem_id="ti_progressbar") + ti_output = gr.Text(elem_id="ti_output", value="", show_label=False) + + ti_gallery = gr.Gallery(label='Output', show_label=False, elem_id='ti_gallery').style(grid=4) + ti_preview = gr.Image(elem_id='ti_preview', visible=False) + ti_progress = gr.HTML(elem_id="ti_progress", value="") + ti_outcome = gr.HTML(elem_id="ti_error", value="") + setup_progressbar(progressbar, ti_preview, 'ti', textinfo=ti_progress) + + create_embedding.click( + fn=modules.textual_inversion.ui.create_embedding, + inputs=[ + new_embedding_name, + initialization_text, + nvpt, + ], + outputs=[ + train_embedding_name, + ti_output, + ti_outcome, + ] + ) + + run_preprocess.click( + fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]), + _js="start_training_textual_inversion", + inputs=[ + process_src, + process_dst, + process_flip, + process_split, + process_caption, + ], + outputs=[ + ti_output, + ti_outcome, + ], + ) + + train_embedding.click( + fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.train_embedding, extra_outputs=[gr.update()]), + _js="start_training_textual_inversion", + inputs=[ + train_embedding_name, + learn_rate, + dataset_directory, + log_directory, + steps, + create_image_every, + save_embedding_every, + template_file, + ], + outputs=[ + ti_output, + ti_outcome, + ] + ) + + interrupt_training.click( + fn=lambda: shared.state.interrupt(), + inputs=[], + outputs=[], + ) + def create_setting_component(key): def fun(): return opts.data[key] if key in opts.data else opts.data_labels[key].default @@ -1002,6 +1170,32 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): _js='function(){}' ) + with gr.Row(): + reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary') + restart_gradio = gr.Button(value='Restart Gradio and Refresh components (Custom Scripts, ui.py, js and css only)', variant='primary') + + + def reload_scripts(): + modules.scripts.reload_script_body_only() + + reload_script_bodies.click( + fn=reload_scripts, + inputs=[], + outputs=[], + _js='function(){}' + ) + + def request_restart(): + shared.state.interrupt() + settings_interface.gradio_ref.do_restart = True + + restart_gradio.click( + fn=request_restart, + inputs=[], + outputs=[], + _js='function(){restart_reload()}' + ) + if column is not None: column.__exit__() @@ -1011,6 +1205,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): (extras_interface, "Extras", "extras"), (pnginfo_interface, "PNG Info", "pnginfo"), (modelmerger_interface, "Checkpoint Merger", "modelmerger"), + (textual_inversion_interface, "Textual inversion", "ti"), (settings_interface, "Settings", "settings"), ] @@ -1026,7 +1221,9 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): css += css_hide_progressbar with gr.Blocks(css=css, analytics_enabled=False, title="Stable Diffusion") as demo: - + + settings_interface.gradio_ref = demo + with gr.Tabs() as tabs: for interface, label, ifid in interfaces: with gr.TabItem(label, id=ifid): @@ -1044,11 +1241,11 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger): def modelmerger(*args): try: - results = run_modelmerger(*args) + results = modules.extras.run_modelmerger(*args) except Exception as e: print("Error loading/saving model file:", file=sys.stderr) print(traceback.format_exc(), file=sys.stderr) - modules.sd_models.list_models() #To remove the potentially missing models from the list + modules.sd_models.list_models() # to remove the potentially missing models from the list return ["Error loading/saving model file. It doesn't exist or the name contains illegal characters"] + [gr.Dropdown.update(choices=modules.sd_models.checkpoint_tiles()) for _ in range(3)] return results @@ -1206,12 +1403,12 @@ for filename in sorted(os.listdir(jsdir)): javascript += f"\n" -def template_response(*args, **kwargs): - res = gradio_routes_templates_response(*args, **kwargs) - res.body = res.body.replace(b'', f'{javascript}'.encode("utf8")) - res.init_headers() - return res +if 'gradio_routes_templates_response' not in globals(): + def template_response(*args, **kwargs): + res = gradio_routes_templates_response(*args, **kwargs) + res.body = res.body.replace(b'', f'{javascript}'.encode("utf8")) + res.init_headers() + return res - -gradio_routes_templates_response = gradio.routes.templates.TemplateResponse -gradio.routes.templates.TemplateResponse = template_response + gradio_routes_templates_response = gradio.routes.templates.TemplateResponse + gradio.routes.templates.TemplateResponse = template_response diff --git a/requirements.txt b/requirements.txt index 7cb9d329..631fe616 100644 --- a/requirements.txt +++ b/requirements.txt @@ -13,14 +13,13 @@ Pillow pytorch_lightning realesrgan scikit-image>=0.19 -git+https://github.com/TencentARC/GFPGAN.git@8d2447a2d918f8eba5a4a01463fd48e45126a379 timm==0.4.12 transformers==4.19.2 torch einops jsonmerge clean-fid -git+https://github.com/openai/CLIP@d50d76daa670286dd6cacf3bcd80b5e4823fc8e1 resize-right torchdiffeq kornia +lark diff --git a/requirements_versions.txt b/requirements_versions.txt index 1e8006e0..fdff2687 100644 --- a/requirements_versions.txt +++ b/requirements_versions.txt @@ -18,7 +18,7 @@ piexif==1.1.3 einops==0.4.1 jsonmerge==1.8.0 clean-fid==0.1.29 -git+https://github.com/openai/CLIP@d50d76daa670286dd6cacf3bcd80b5e4823fc8e1 resize-right==0.0.2 torchdiffeq==0.2.3 kornia==0.6.7 +lark==1.1.2 diff --git a/scripts/img2imgalt.py b/scripts/img2imgalt.py index 0ef137f7..f9894cb0 100644 --- a/scripts/img2imgalt.py +++ b/scripts/img2imgalt.py @@ -8,7 +8,6 @@ import gradio as gr from modules import processing, shared, sd_samplers, prompt_parser from modules.processing import Processed -from modules.sd_samplers import samplers from modules.shared import opts, cmd_opts, state import torch @@ -159,7 +158,7 @@ class Script(scripts.Script): combined_noise = ((1 - randomness) * rec_noise + randomness * rand_noise) / ((randomness**2 + (1-randomness)**2) ** 0.5) - sampler = samplers[p.sampler_index].constructor(p.sd_model) + sampler = sd_samplers.create_sampler_with_index(sd_samplers.samplers, p.sampler_index, p.sd_model) sigmas = sampler.model_wrap.get_sigmas(p.steps) diff --git a/scripts/outpainting_mk_2.py b/scripts/outpainting_mk_2.py index 9719bb8f..a6468e09 100644 --- a/scripts/outpainting_mk_2.py +++ b/scripts/outpainting_mk_2.py @@ -11,46 +11,8 @@ from modules import images, processing, devices from modules.processing import Processed, process_images from modules.shared import opts, cmd_opts, state -# https://github.com/parlance-zz/g-diffuser-bot -def expand(x, dir, amount, power=0.75): - is_left = dir == 3 - is_right = dir == 1 - is_up = dir == 0 - is_down = dir == 2 - - if is_left or is_right: - noise = np.zeros((x.shape[0], amount, 3), dtype=float) - indexes = np.random.random((x.shape[0], amount)) ** power * (1 - np.arange(amount) / amount) - if is_right: - indexes = 1 - indexes - indexes = (indexes * (x.shape[1] - 1)).astype(int) - - for row in range(x.shape[0]): - if is_left: - noise[row] = x[row][indexes[row]] - else: - noise[row] = np.flip(x[row][indexes[row]], axis=0) - - x = np.concatenate([noise, x] if is_left else [x, noise], axis=1) - return x - - if is_up or is_down: - noise = np.zeros((amount, x.shape[1], 3), dtype=float) - indexes = np.random.random((x.shape[1], amount)) ** power * (1 - np.arange(amount) / amount) - if is_down: - indexes = 1 - indexes - indexes = (indexes * x.shape[0] - 1).astype(int) - - for row in range(x.shape[1]): - if is_up: - noise[:, row] = x[:, row][indexes[row]] - else: - noise[:, row] = np.flip(x[:, row][indexes[row]], axis=0) - - x = np.concatenate([noise, x] if is_up else [x, noise], axis=0) - return x - +# this function is taken from https://github.com/parlance-zz/g-diffuser-bot def get_matched_noise(_np_src_image, np_mask_rgb, noise_q=1, color_variation=0.05): # helper fft routines that keep ortho normalization and auto-shift before and after fft def _fft2(data): @@ -123,8 +85,11 @@ def get_matched_noise(_np_src_image, np_mask_rgb, noise_q=1, color_variation=0.0 src_dist = np.absolute(src_fft) src_phase = src_fft / src_dist + # create a generator with a static seed to make outpainting deterministic / only follow global seed + rng = np.random.default_rng(0) + noise_window = _get_gaussian_window(width, height, mode=1) # start with simple gaussian noise - noise_rgb = np.random.random_sample((width, height, num_channels)) + noise_rgb = rng.random((width, height, num_channels)) noise_grey = (np.sum(noise_rgb, axis=2) / 3.) noise_rgb *= color_variation # the colorfulness of the starting noise is blended to greyscale with a parameter for c in range(num_channels): diff --git a/scripts/sd_upscale.py b/scripts/sd_upscale.py index 2653e2d4..cb37ff7e 100644 --- a/scripts/sd_upscale.py +++ b/scripts/sd_upscale.py @@ -34,7 +34,11 @@ class Script(scripts.Script): seed = p.seed init_img = p.init_images[0] - img = upscaler.scaler.upscale(init_img, 2, upscaler.data_path) + + if(upscaler.name != "None"): + img = upscaler.scaler.upscale(init_img, 2, upscaler.data_path) + else: + img = init_img devices.torch_gc() diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py index 146663b0..6344e612 100644 --- a/scripts/xy_grid.py +++ b/scripts/xy_grid.py @@ -1,7 +1,9 @@ from collections import namedtuple from copy import copy +from itertools import permutations, chain import random - +import csv +from io import StringIO from PIL import Image import numpy as np @@ -29,6 +31,31 @@ def apply_prompt(p, x, xs): p.negative_prompt = p.negative_prompt.replace(xs[0], x) +def apply_order(p, x, xs): + token_order = [] + + # Initally grab the tokens from the prompt, so they can be replaced in order of earliest seen + for token in x: + token_order.append((p.prompt.find(token), token)) + + token_order.sort(key=lambda t: t[0]) + + prompt_parts = [] + + # Split the prompt up, taking out the tokens + for _, token in token_order: + n = p.prompt.find(token) + prompt_parts.append(p.prompt[0:n]) + p.prompt = p.prompt[n + len(token):] + + # Rebuild the prompt with the tokens in the order we want + prompt_tmp = "" + for idx, part in enumerate(prompt_parts): + prompt_tmp += part + prompt_tmp += x[idx] + p.prompt = prompt_tmp + p.prompt + + samplers_dict = {} for i, sampler in enumerate(modules.sd_samplers.samplers): samplers_dict[sampler.name.lower()] = i @@ -60,16 +87,26 @@ def format_value_add_label(p, opt, x): def format_value(p, opt, x): if type(x) == float: x = round(x, 8) - return x + +def format_value_join_list(p, opt, x): + return ", ".join(x) + + def do_nothing(p, x, xs): pass + def format_nothing(p, opt, x): return "" +def str_permutations(x): + """dummy function for specifying it in AxisOption's type when you want to get a list of permutations""" + return x + + AxisOption = namedtuple("AxisOption", ["label", "type", "apply", "format_value"]) AxisOptionImg2Img = namedtuple("AxisOptionImg2Img", ["label", "type", "apply", "format_value"]) @@ -82,6 +119,7 @@ axis_options = [ AxisOption("Steps", int, apply_field("steps"), format_value_add_label), AxisOption("CFG Scale", float, apply_field("cfg_scale"), format_value_add_label), AxisOption("Prompt S/R", str, apply_prompt, format_value), + AxisOption("Prompt order", str_permutations, apply_order, format_value_join_list), AxisOption("Sampler", str, apply_sampler, format_value), AxisOption("Checkpoint name", str, apply_checkpoint, format_value), AxisOption("Sigma Churn", float, apply_field("s_churn"), format_value_add_label), @@ -159,7 +197,7 @@ class Script(scripts.Script): if opt.label == 'Nothing': return [0] - valslist = [x.strip() for x in vals.split(",")] + valslist = [x.strip() for x in chain.from_iterable(csv.reader(StringIO(vals)))] if opt.type == int: valslist_ext = [] @@ -206,6 +244,8 @@ class Script(scripts.Script): valslist_ext.append(val) valslist = valslist_ext + elif opt.type == str_permutations: + valslist = list(permutations(valslist)) valslist = [opt.type(x) for x in valslist] diff --git a/style.css b/style.css index e11316b9..da0729a2 100644 --- a/style.css +++ b/style.css @@ -23,7 +23,7 @@ text-align: right; } -#generate{ +#txt2img_generate, #img2img_generate { min-height: 4.5em; } @@ -157,7 +157,7 @@ button{ max-width: 10em; } -#txt2img_preview, #img2img_preview{ +#txt2img_preview, #img2img_preview, #ti_preview{ position: absolute; width: 320px; left: 0; @@ -172,18 +172,18 @@ button{ } @media screen and (min-width: 768px) { - #txt2img_preview, #img2img_preview { + #txt2img_preview, #img2img_preview, #ti_preview { position: absolute; } } @media screen and (max-width: 767px) { - #txt2img_preview, #img2img_preview { + #txt2img_preview, #img2img_preview, #ti_preview { position: relative; } } -#txt2img_preview div.left-0.top-0, #img2img_preview div.left-0.top-0{ +#txt2img_preview div.left-0.top-0, #img2img_preview div.left-0.top-0, #ti_preview div.left-0.top-0{ display: none; } @@ -247,7 +247,7 @@ input[type="range"]{ #txt2img_negative_prompt, #img2img_negative_prompt{ } -#txt2img_progressbar, #img2img_progressbar{ +#txt2img_progressbar, #img2img_progressbar, #ti_progressbar{ position: absolute; z-index: 1000; right: 0; @@ -407,3 +407,7 @@ input[type="range"]{ .gallery-item { --tw-bg-opacity: 0 !important; } + +#img2img_image div.h-60{ + height: 480px; +} \ No newline at end of file diff --git a/textual_inversion_templates/style.txt b/textual_inversion_templates/style.txt new file mode 100644 index 00000000..15af2d6b --- /dev/null +++ b/textual_inversion_templates/style.txt @@ -0,0 +1,19 @@ +a painting, art by [name] +a rendering, art by [name] +a cropped painting, art by [name] +the painting, art by [name] +a clean painting, art by [name] +a dirty painting, art by [name] +a dark painting, art by [name] +a picture, art by [name] +a cool painting, art by [name] +a close-up painting, art by [name] +a bright painting, art by [name] +a cropped painting, art by [name] +a good painting, art by [name] +a close-up painting, art by [name] +a rendition, art by [name] +a nice painting, art by [name] +a small painting, art by [name] +a weird painting, art by [name] +a large painting, art by [name] diff --git a/textual_inversion_templates/style_filewords.txt b/textual_inversion_templates/style_filewords.txt new file mode 100644 index 00000000..b3a8159a --- /dev/null +++ b/textual_inversion_templates/style_filewords.txt @@ -0,0 +1,19 @@ +a painting of [filewords], art by [name] +a rendering of [filewords], art by [name] +a cropped painting of [filewords], art by [name] +the painting of [filewords], art by [name] +a clean painting of [filewords], art by [name] +a dirty painting of [filewords], art by [name] +a dark painting of [filewords], art by [name] +a picture of [filewords], art by [name] +a cool painting of [filewords], art by [name] +a close-up painting of [filewords], art by [name] +a bright painting of [filewords], art by [name] +a cropped painting of [filewords], art by [name] +a good painting of [filewords], art by [name] +a close-up painting of [filewords], art by [name] +a rendition of [filewords], art by [name] +a nice painting of [filewords], art by [name] +a small painting of [filewords], art by [name] +a weird painting of [filewords], art by [name] +a large painting of [filewords], art by [name] diff --git a/textual_inversion_templates/subject.txt b/textual_inversion_templates/subject.txt new file mode 100644 index 00000000..79f36aa0 --- /dev/null +++ b/textual_inversion_templates/subject.txt @@ -0,0 +1,27 @@ +a photo of a [name] +a rendering of a [name] +a cropped photo of the [name] +the photo of a [name] +a photo of a clean [name] +a photo of a dirty [name] +a dark photo of the [name] +a photo of my [name] +a photo of the cool [name] +a close-up photo of a [name] +a bright photo of the [name] +a cropped photo of a [name] +a photo of the [name] +a good photo of the [name] +a photo of one [name] +a close-up photo of the [name] +a rendition of the [name] +a photo of the clean [name] +a rendition of a [name] +a photo of a nice [name] +a good photo of a [name] +a photo of the nice [name] +a photo of the small [name] +a photo of the weird [name] +a photo of the large [name] +a photo of a cool [name] +a photo of a small [name] diff --git a/textual_inversion_templates/subject_filewords.txt b/textual_inversion_templates/subject_filewords.txt new file mode 100644 index 00000000..008652a6 --- /dev/null +++ b/textual_inversion_templates/subject_filewords.txt @@ -0,0 +1,27 @@ +a photo of a [name], [filewords] +a rendering of a [name], [filewords] +a cropped photo of the [name], [filewords] +the photo of a [name], [filewords] +a photo of a clean [name], [filewords] +a photo of a dirty [name], [filewords] +a dark photo of the [name], [filewords] +a photo of my [name], [filewords] +a photo of the cool [name], [filewords] +a close-up photo of a [name], [filewords] +a bright photo of the [name], [filewords] +a cropped photo of a [name], [filewords] +a photo of the [name], [filewords] +a good photo of the [name], [filewords] +a photo of one [name], [filewords] +a close-up photo of the [name], [filewords] +a rendition of the [name], [filewords] +a photo of the clean [name], [filewords] +a rendition of a [name], [filewords] +a photo of a nice [name], [filewords] +a good photo of a [name], [filewords] +a photo of the nice [name], [filewords] +a photo of the small [name], [filewords] +a photo of the weird [name], [filewords] +a photo of the large [name], [filewords] +a photo of a cool [name], [filewords] +a photo of a small [name], [filewords] diff --git a/webui.py b/webui.py index b8cccd54..480360fe 100644 --- a/webui.py +++ b/webui.py @@ -1,34 +1,35 @@ import os import threading - -from modules import devices -from modules.paths import script_path +import time +import importlib import signal import threading -import modules.paths + +from modules.paths import script_path + +from modules import devices, sd_samplers import modules.codeformer_model as codeformer -import modules.esrgan_model as esrgan -import modules.bsrgan_model as bsrgan import modules.extras import modules.face_restoration import modules.gfpgan_model as gfpgan import modules.img2img -import modules.ldsr_model as ldsr + import modules.lowvram -import modules.realesrgan_model as realesrgan +import modules.paths import modules.scripts import modules.sd_hijack import modules.sd_models import modules.shared as shared -import modules.swinir_model as swinir import modules.txt2img + import modules.ui +from modules import devices from modules import modelloader from modules.paths import script_path from modules.shared import cmd_opts modelloader.cleanup_models() -modules.sd_models.setup_model(cmd_opts.ckpt_dir) +modules.sd_models.setup_model() codeformer.setup_model(cmd_opts.codeformer_models_path) gfpgan.setup_model(cmd_opts.gfpgan_models_path) shared.face_restorers.append(modules.face_restoration.FaceRestoration()) @@ -46,7 +47,7 @@ def wrap_queued_call(func): return f -def wrap_gradio_gpu_call(func): +def wrap_gradio_gpu_call(func, extra_outputs=None): def f(*args, **kwargs): devices.torch_gc() @@ -58,6 +59,7 @@ def wrap_gradio_gpu_call(func): shared.state.current_image = None shared.state.current_image_sampling_step = 0 shared.state.interrupted = False + shared.state.textinfo = None with queue_lock: res = func(*args, **kwargs) @@ -69,7 +71,7 @@ def wrap_gradio_gpu_call(func): return res - return modules.ui.wrap_gradio_call(f) + return modules.ui.wrap_gradio_call(f, extra_outputs=extra_outputs) modules.scripts.load_scripts(os.path.join(script_path, "scripts")) @@ -86,22 +88,36 @@ def webui(): signal.signal(signal.SIGINT, sigint_handler) - demo = modules.ui.create_ui( - txt2img=wrap_gradio_gpu_call(modules.txt2img.txt2img), - img2img=wrap_gradio_gpu_call(modules.img2img.img2img), - run_extras=wrap_gradio_gpu_call(modules.extras.run_extras), - run_pnginfo=modules.extras.run_pnginfo, - run_modelmerger=modules.extras.run_modelmerger - ) + while 1: + + demo = modules.ui.create_ui(wrap_gradio_gpu_call=wrap_gradio_gpu_call) + + demo.launch( + share=cmd_opts.share, + server_name="0.0.0.0" if cmd_opts.listen else None, + server_port=cmd_opts.port, + debug=cmd_opts.gradio_debug, + auth=[tuple(cred.split(':')) for cred in cmd_opts.gradio_auth.strip('"').split(',')] if cmd_opts.gradio_auth else None, + inbrowser=cmd_opts.autolaunch, + prevent_thread_lock=True + ) + + while 1: + time.sleep(0.5) + if getattr(demo, 'do_restart', False): + time.sleep(0.5) + demo.close() + time.sleep(0.5) + break + + sd_samplers.set_samplers() + + print('Reloading Custom Scripts') + modules.scripts.reload_scripts(os.path.join(script_path, "scripts")) + print('Reloading modules: modules.ui') + importlib.reload(modules.ui) + print('Restarting Gradio') - demo.launch( - share=cmd_opts.share, - server_name="0.0.0.0" if cmd_opts.listen else None, - server_port=cmd_opts.port, - debug=cmd_opts.gradio_debug, - auth=[tuple(cred.split(':')) for cred in cmd_opts.gradio_auth.strip('"').split(',')] if cmd_opts.gradio_auth else None, - inbrowser=cmd_opts.autolaunch, - ) if __name__ == "__main__":