diff --git a/.gitignore b/.gitignore index f9c3357c..8fa05852 100644 --- a/.gitignore +++ b/.gitignore @@ -27,4 +27,5 @@ __pycache__ notification.mp3 /SwinIR /textual_inversion -.vscode \ No newline at end of file +.vscode +/extensions diff --git a/README.md b/README.md index 5b5dc8ba..1a0e4f6a 100644 --- a/README.md +++ b/README.md @@ -83,8 +83,17 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web - Estimated completion time in progress bar - API - Support for dedicated [inpainting model](https://github.com/runwayml/stable-diffusion#inpainting-with-stable-diffusion) by RunwayML. -- Aesthetic Gradients, a way to generate images with a specific aesthetic by using clip images embds (implementation of [https://github.com/vicgalle/stable-diffusion-aesthetic-gradients](https://github.com/vicgalle/stable-diffusion-aesthetic-gradients)) +- via extension: [Aesthetic Gradients](https://github.com/AUTOMATIC1111/stable-diffusion-webui-aesthetic-gradients), a way to generate images with a specific aesthetic by using clip images embds (implementation of [https://github.com/vicgalle/stable-diffusion-aesthetic-gradients](https://github.com/vicgalle/stable-diffusion-aesthetic-gradients)) +## Where are Aesthetic Gradients?!?! +Aesthetic Gradients are now an extension. You can install it using git: + +```commandline +git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui-aesthetic-gradients extensions/aesthetic-gradients +``` + +After running this command, make sure that you have `aesthetic-gradients` dir in webui's `extensions` directory and restart +the UI. The interface for Aesthetic Gradients should appear exactly the same as it was. ## Installation and Running Make sure the required [dependencies](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies) are met and follow the instructions available for both [NVidia](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-NVidia-GPUs) (recommended) and [AMD](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs) GPUs. diff --git a/extensions/put extension here.txt b/extensions/put extension here.txt new file mode 100644 index 00000000..e69de29b diff --git a/javascript/images_history.js b/javascript/images_history.js index f7d052c3..c9aa76f8 100644 --- a/javascript/images_history.js +++ b/javascript/images_history.js @@ -17,14 +17,6 @@ var images_history_click_image = function(){ images_history_set_image_info(this); } -var images_history_click_tab = function(){ - var tabs_box = gradioApp().getElementById("images_history_tab"); - if (!tabs_box.classList.contains(this.getAttribute("tabname"))) { - gradioApp().getElementById(this.getAttribute("tabname") + "_images_history_renew_page").click(); - tabs_box.classList.add(this.getAttribute("tabname")) - } -} - function images_history_disabled_del(){ gradioApp().querySelectorAll(".images_history_del_button").forEach(function(btn){ btn.setAttribute('disabled','disabled'); @@ -43,7 +35,6 @@ function images_history_get_parent_by_tagname(item, tagname){ var parent = item.parentElement; tagname = tagname.toUpperCase() while(parent.tagName != tagname){ - console.log(parent.tagName, tagname) parent = parent.parentElement; } return parent; @@ -88,15 +79,15 @@ function images_history_set_image_info(button){ } -function images_history_get_current_img(tabname, image_path, files){ +function images_history_get_current_img(tabname, img_index, files){ return [ - gradioApp().getElementById(tabname + '_images_history_set_index').getAttribute("img_index"), - image_path, + tabname, + gradioApp().getElementById(tabname + '_images_history_set_index').getAttribute("img_index"), files ]; } -function images_history_delete(del_num, tabname, img_path, img_file_name, page_index, filenames, image_index){ +function images_history_delete(del_num, tabname, image_index){ image_index = parseInt(image_index); var tab = gradioApp().getElementById(tabname + '_images_history'); var set_btn = tab.querySelector(".images_history_set_index"); @@ -107,6 +98,7 @@ function images_history_delete(del_num, tabname, img_path, img_file_name, page_i } }); var img_num = buttons.length / 2; + del_num = Math.min(img_num - image_index, del_num) if (img_num <= del_num){ setTimeout(function(tabname){ gradioApp().getElementById(tabname + '_images_history_renew_page').click(); @@ -114,30 +106,28 @@ function images_history_delete(del_num, tabname, img_path, img_file_name, page_i } else { var next_img for (var i = 0; i < del_num; i++){ - if (image_index + i < image_index + img_num){ - buttons[image_index + i].style.display = 'none'; - buttons[image_index + img_num + 1].style.display = 'none'; - next_img = image_index + i + 1 - } + buttons[image_index + i].style.display = 'none'; + buttons[image_index + i + img_num].style.display = 'none'; + next_img = image_index + i + 1 } var bnt; if (next_img >= img_num){ - btn = buttons[image_index - del_num]; + btn = buttons[image_index - 1]; } else { btn = buttons[next_img]; } setTimeout(function(btn){btn.click()}, 30, btn); } images_history_disabled_del(); - return [del_num, tabname, img_path, img_file_name, page_index, filenames, image_index]; + } -function images_history_turnpage(img_path, page_index, image_index, tabname){ +function images_history_turnpage(tabname){ + gradioApp().getElementById(tabname + '_images_history_del_button').setAttribute('disabled','disabled'); var buttons = gradioApp().getElementById(tabname + '_images_history').querySelectorAll(".gallery-item"); buttons.forEach(function(elem) { elem.style.display = 'block'; - }) - return [img_path, page_index, image_index, tabname]; + }) } function images_history_enable_del_buttons(){ @@ -147,60 +137,64 @@ function images_history_enable_del_buttons(){ } function images_history_init(){ - var load_txt2img_button = gradioApp().getElementById('txt2img_images_history_renew_page') - if (load_txt2img_button){ + var tabnames = gradioApp().getElementById("images_history_tabnames_list") + if (tabnames){ + images_history_tab_list = tabnames.querySelector("textarea").value.split(",") for (var i in images_history_tab_list ){ - tab = images_history_tab_list[i]; + var tab = images_history_tab_list[i]; gradioApp().getElementById(tab + '_images_history').classList.add("images_history_cantainor"); gradioApp().getElementById(tab + '_images_history_set_index').classList.add("images_history_set_index"); gradioApp().getElementById(tab + '_images_history_del_button').classList.add("images_history_del_button"); - gradioApp().getElementById(tab + '_images_history_gallery').classList.add("images_history_gallery"); - + gradioApp().getElementById(tab + '_images_history_gallery').classList.add("images_history_gallery"); + gradioApp().getElementById(tab + "_images_history_start").setAttribute("style","padding:20px;font-size:25px"); } - var tabs_box = gradioApp().getElementById("tab_images_history").querySelector("div").querySelector("div").querySelector("div"); - tabs_box.setAttribute("id", "images_history_tab"); - var tab_btns = tabs_box.querySelectorAll("button"); - for (var i in images_history_tab_list){ - var tabname = images_history_tab_list[i] - tab_btns[i].setAttribute("tabname", tabname); - // this refreshes history upon tab switch - // until the history is known to work well, which is not the case now, we do not do this at startup - //tab_btns[i].addEventListener('click', images_history_click_tab); - } - tabs_box.classList.add(images_history_tab_list[0]); - - // same as above, at page load - //load_txt2img_button.click(); + //preload + if (gradioApp().getElementById("images_history_preload").querySelector("input").checked ){ + var tabs_box = gradioApp().getElementById("tab_images_history").querySelector("div").querySelector("div").querySelector("div"); + tabs_box.setAttribute("id", "images_history_tab"); + var tab_btns = tabs_box.querySelectorAll("button"); + for (var i in images_history_tab_list){ + var tabname = images_history_tab_list[i] + tab_btns[i].setAttribute("tabname", tabname); + tab_btns[i].addEventListener('click', function(){ + var tabs_box = gradioApp().getElementById("images_history_tab"); + if (!tabs_box.classList.contains(this.getAttribute("tabname"))) { + gradioApp().getElementById(this.getAttribute("tabname") + "_images_history_start").click(); + tabs_box.classList.add(this.getAttribute("tabname")) + } + }); + } + tab_btns[0].click() + } } else { setTimeout(images_history_init, 500); } } -var images_history_tab_list = ["txt2img", "img2img", "extras"]; +var images_history_tab_list = ""; setTimeout(images_history_init, 500); document.addEventListener("DOMContentLoaded", function() { var mutationObserver = new MutationObserver(function(m){ - for (var i in images_history_tab_list ){ - let tabname = images_history_tab_list[i] - var buttons = gradioApp().querySelectorAll('#' + tabname + '_images_history .gallery-item'); - buttons.forEach(function(bnt){ - bnt.addEventListener('click', images_history_click_image, true); - }); + if (images_history_tab_list != ""){ + for (var i in images_history_tab_list ){ + let tabname = images_history_tab_list[i] + var buttons = gradioApp().querySelectorAll('#' + tabname + '_images_history .gallery-item'); + buttons.forEach(function(bnt){ + bnt.addEventListener('click', images_history_click_image, true); + }); - // same as load_txt2img_button.click() above - /* - var cls_btn = gradioApp().getElementById(tabname + '_images_history_gallery').querySelector("svg"); - if (cls_btn){ - cls_btn.addEventListener('click', function(){ - gradioApp().getElementById(tabname + '_images_history_renew_page').click(); - }, false); - }*/ + var cls_btn = gradioApp().getElementById(tabname + '_images_history_gallery').querySelector("svg"); + if (cls_btn){ + cls_btn.addEventListener('click', function(){ + gradioApp().getElementById(tabname + '_images_history_renew_page').click(); + }, false); + } - } + } + } }); - mutationObserver.observe( gradioApp(), { childList:true, subtree:true }); - + mutationObserver.observe(gradioApp(), { childList:true, subtree:true }); }); diff --git a/modules/aesthetic_clip.py b/modules/aesthetic_clip.py deleted file mode 100644 index 8c828541..00000000 --- a/modules/aesthetic_clip.py +++ /dev/null @@ -1,241 +0,0 @@ -import copy -import itertools -import os -from pathlib import Path -import html -import gc - -import gradio as gr -import torch -from PIL import Image -from torch import optim - -from modules import shared -from transformers import CLIPModel, CLIPProcessor, CLIPTokenizer -from tqdm.auto import tqdm, trange -from modules.shared import opts, device - - -def get_all_images_in_folder(folder): - return [os.path.join(folder, f) for f in os.listdir(folder) if - os.path.isfile(os.path.join(folder, f)) and check_is_valid_image_file(f)] - - -def check_is_valid_image_file(filename): - return filename.lower().endswith(('.png', '.jpg', '.jpeg', ".gif", ".tiff", ".webp")) - - -def batched(dataset, total, n=1): - for ndx in range(0, total, n): - yield [dataset.__getitem__(i) for i in range(ndx, min(ndx + n, total))] - - -def iter_to_batched(iterable, n=1): - it = iter(iterable) - while True: - chunk = tuple(itertools.islice(it, n)) - if not chunk: - return - yield chunk - - -def create_ui(): - import modules.ui - - with gr.Group(): - with gr.Accordion("Open for Clip Aesthetic!", open=False): - with gr.Row(): - aesthetic_weight = gr.Slider(minimum=0, maximum=1, step=0.01, label="Aesthetic weight", - value=0.9) - aesthetic_steps = gr.Slider(minimum=0, maximum=50, step=1, label="Aesthetic steps", value=5) - - with gr.Row(): - aesthetic_lr = gr.Textbox(label='Aesthetic learning rate', - placeholder="Aesthetic learning rate", value="0.0001") - aesthetic_slerp = gr.Checkbox(label="Slerp interpolation", value=False) - aesthetic_imgs = gr.Dropdown(sorted(shared.aesthetic_embeddings.keys()), - label="Aesthetic imgs embedding", - value="None") - - modules.ui.create_refresh_button(aesthetic_imgs, shared.update_aesthetic_embeddings, lambda: {"choices": sorted(shared.aesthetic_embeddings.keys())}, "refresh_aesthetic_embeddings") - - with gr.Row(): - aesthetic_imgs_text = gr.Textbox(label='Aesthetic text for imgs', - placeholder="This text is used to rotate the feature space of the imgs embs", - value="") - aesthetic_slerp_angle = gr.Slider(label='Slerp angle', minimum=0, maximum=1, step=0.01, - value=0.1) - aesthetic_text_negative = gr.Checkbox(label="Is negative text", value=False) - - return aesthetic_weight, aesthetic_steps, aesthetic_lr, aesthetic_slerp, aesthetic_imgs, aesthetic_imgs_text, aesthetic_slerp_angle, aesthetic_text_negative - - -aesthetic_clip_model = None - - -def aesthetic_clip(): - global aesthetic_clip_model - - if aesthetic_clip_model is None or aesthetic_clip_model.name_or_path != shared.sd_model.cond_stage_model.wrapped.transformer.name_or_path: - aesthetic_clip_model = CLIPModel.from_pretrained(shared.sd_model.cond_stage_model.wrapped.transformer.name_or_path) - aesthetic_clip_model.cpu() - - return aesthetic_clip_model - - -def generate_imgs_embd(name, folder, batch_size): - model = aesthetic_clip().to(device) - processor = CLIPProcessor.from_pretrained(model.name_or_path) - - with torch.no_grad(): - embs = [] - for paths in tqdm(iter_to_batched(get_all_images_in_folder(folder), batch_size), - desc=f"Generating embeddings for {name}"): - if shared.state.interrupted: - break - inputs = processor(images=[Image.open(path) for path in paths], return_tensors="pt").to(device) - outputs = model.get_image_features(**inputs).cpu() - embs.append(torch.clone(outputs)) - inputs.to("cpu") - del inputs, outputs - - embs = torch.cat(embs, dim=0).mean(dim=0, keepdim=True) - - # The generated embedding will be located here - path = str(Path(shared.cmd_opts.aesthetic_embeddings_dir) / f"{name}.pt") - torch.save(embs, path) - - model.cpu() - del processor - del embs - gc.collect() - torch.cuda.empty_cache() - res = f""" - Done generating embedding for {name}! - Aesthetic embedding saved to {html.escape(path)} - """ - shared.update_aesthetic_embeddings() - return gr.Dropdown.update(choices=sorted(shared.aesthetic_embeddings.keys()), label="Imgs embedding", - value="None"), \ - gr.Dropdown.update(choices=sorted(shared.aesthetic_embeddings.keys()), - label="Imgs embedding", - value="None"), res, "" - - -def slerp(low, high, val): - low_norm = low / torch.norm(low, dim=1, keepdim=True) - high_norm = high / torch.norm(high, dim=1, keepdim=True) - omega = torch.acos((low_norm * high_norm).sum(1)) - so = torch.sin(omega) - res = (torch.sin((1.0 - val) * omega) / so).unsqueeze(1) * low + (torch.sin(val * omega) / so).unsqueeze(1) * high - return res - - -class AestheticCLIP: - def __init__(self): - self.skip = False - self.aesthetic_steps = 0 - self.aesthetic_weight = 0 - self.aesthetic_lr = 0 - self.slerp = False - self.aesthetic_text_negative = "" - self.aesthetic_slerp_angle = 0 - self.aesthetic_imgs_text = "" - - self.image_embs_name = None - self.image_embs = None - self.load_image_embs(None) - - def set_aesthetic_params(self, p, aesthetic_lr=0, aesthetic_weight=0, aesthetic_steps=0, image_embs_name=None, - aesthetic_slerp=True, aesthetic_imgs_text="", - aesthetic_slerp_angle=0.15, - aesthetic_text_negative=False): - self.aesthetic_imgs_text = aesthetic_imgs_text - self.aesthetic_slerp_angle = aesthetic_slerp_angle - self.aesthetic_text_negative = aesthetic_text_negative - self.slerp = aesthetic_slerp - self.aesthetic_lr = aesthetic_lr - self.aesthetic_weight = aesthetic_weight - self.aesthetic_steps = aesthetic_steps - self.load_image_embs(image_embs_name) - - if self.image_embs_name is not None: - p.extra_generation_params.update({ - "Aesthetic LR": aesthetic_lr, - "Aesthetic weight": aesthetic_weight, - "Aesthetic steps": aesthetic_steps, - "Aesthetic embedding": self.image_embs_name, - "Aesthetic slerp": aesthetic_slerp, - "Aesthetic text": aesthetic_imgs_text, - "Aesthetic text negative": aesthetic_text_negative, - "Aesthetic slerp angle": aesthetic_slerp_angle, - }) - - def set_skip(self, skip): - self.skip = skip - - def load_image_embs(self, image_embs_name): - if image_embs_name is None or len(image_embs_name) == 0 or image_embs_name == "None": - image_embs_name = None - self.image_embs_name = None - if image_embs_name is not None and self.image_embs_name != image_embs_name: - self.image_embs_name = image_embs_name - self.image_embs = torch.load(shared.aesthetic_embeddings[self.image_embs_name], map_location=device) - self.image_embs /= self.image_embs.norm(dim=-1, keepdim=True) - self.image_embs.requires_grad_(False) - - def __call__(self, z, remade_batch_tokens): - if not self.skip and self.aesthetic_steps != 0 and self.aesthetic_lr != 0 and self.aesthetic_weight != 0 and self.image_embs_name is not None: - tokenizer = shared.sd_model.cond_stage_model.tokenizer - if not opts.use_old_emphasis_implementation: - remade_batch_tokens = [ - [tokenizer.bos_token_id] + x[:75] + [tokenizer.eos_token_id] for x in - remade_batch_tokens] - - tokens = torch.asarray(remade_batch_tokens).to(device) - - model = copy.deepcopy(aesthetic_clip()).to(device) - model.requires_grad_(True) - if self.aesthetic_imgs_text is not None and len(self.aesthetic_imgs_text) > 0: - text_embs_2 = model.get_text_features( - **tokenizer([self.aesthetic_imgs_text], padding=True, return_tensors="pt").to(device)) - if self.aesthetic_text_negative: - text_embs_2 = self.image_embs - text_embs_2 - text_embs_2 /= text_embs_2.norm(dim=-1, keepdim=True) - img_embs = slerp(self.image_embs, text_embs_2, self.aesthetic_slerp_angle) - else: - img_embs = self.image_embs - - with torch.enable_grad(): - - # We optimize the model to maximize the similarity - optimizer = optim.Adam( - model.text_model.parameters(), lr=self.aesthetic_lr - ) - - for _ in trange(self.aesthetic_steps, desc="Aesthetic optimization"): - text_embs = model.get_text_features(input_ids=tokens) - text_embs = text_embs / text_embs.norm(dim=-1, keepdim=True) - sim = text_embs @ img_embs.T - loss = -sim - optimizer.zero_grad() - loss.mean().backward() - optimizer.step() - - zn = model.text_model(input_ids=tokens, output_hidden_states=-opts.CLIP_stop_at_last_layers) - if opts.CLIP_stop_at_last_layers > 1: - zn = zn.hidden_states[-opts.CLIP_stop_at_last_layers] - zn = model.text_model.final_layer_norm(zn) - else: - zn = zn.last_hidden_state - model.cpu() - del model - gc.collect() - torch.cuda.empty_cache() - zn = torch.concat([zn[77 * i:77 * (i + 1)] for i in range(max(z.shape[1] // 77, 1))], 1) - if self.slerp: - z = slerp(z, zn, self.aesthetic_weight) - else: - z = z * (1 - self.aesthetic_weight) + zn * self.aesthetic_weight - - return z diff --git a/modules/images_history.py b/modules/images_history.py index 46b23e56..bc5cf11f 100644 --- a/modules/images_history.py +++ b/modules/images_history.py @@ -1,183 +1,424 @@ import os import shutil -import sys +import time +import hashlib +import gradio +system_bak_path = "webui_log_and_bak" +custom_tab_name = "custom fold" +faverate_tab_name = "favorites" +tabs_list = ["txt2img", "img2img", "extras", faverate_tab_name] +def is_valid_date(date): + try: + time.strptime(date, "%Y%m%d") + return True + except: + return False -def traverse_all_files(output_dir, image_list, curr_dir=None): - curr_path = output_dir if curr_dir is None else os.path.join(output_dir, curr_dir) +def reduplicative_file_move(src, dst): + def same_name_file(basename, path): + name, ext = os.path.splitext(basename) + f_list = os.listdir(path) + max_num = 0 + for f in f_list: + if len(f) <= len(basename): + continue + f_ext = f[-len(ext):] if len(ext) > 0 else "" + if f[:len(name)] == name and f_ext == ext: + if f[len(name)] == "(" and f[-len(ext)-1] == ")": + number = f[len(name)+1:-len(ext)-1] + if number.isdigit(): + if int(number) > max_num: + max_num = int(number) + return f"{name}({max_num + 1}){ext}" + name = os.path.basename(src) + save_name = os.path.join(dst, name) + if not os.path.exists(save_name): + shutil.move(src, dst) + else: + name = same_name_file(name, dst) + shutil.move(src, os.path.join(dst, name)) + +def traverse_all_files(curr_path, image_list, all_type=False): try: f_list = os.listdir(curr_path) except: - if curr_dir[-10:].rfind(".") > 0 and curr_dir[-4:] != ".txt": - image_list.append(curr_dir) + if all_type or (curr_path[-10:].rfind(".") > 0 and curr_path[-4:] != ".txt" and curr_path[-4:] != ".csv"): + image_list.append(curr_path) return image_list for file in f_list: - file = file if curr_dir is None else os.path.join(curr_dir, file) - file_path = os.path.join(curr_path, file) - if file[-4:] == ".txt": + file = os.path.join(curr_path, file) + if (not all_type) and (file[-4:] == ".txt" or file[-4:] == ".csv"): pass - elif os.path.isfile(file_path) and file[-10:].rfind(".") > 0: + elif os.path.isfile(file) and file[-10:].rfind(".") > 0: image_list.append(file) else: - image_list = traverse_all_files(output_dir, image_list, file) + image_list = traverse_all_files(file, image_list) return image_list +def auto_sorting(dir_name): + bak_path = os.path.join(dir_name, system_bak_path) + if not os.path.exists(bak_path): + os.mkdir(bak_path) + log_file = None + files_list = [] + f_list = os.listdir(dir_name) + for file in f_list: + if file == system_bak_path: + continue + file_path = os.path.join(dir_name, file) + if not is_valid_date(file): + if file[-10:].rfind(".") > 0: + files_list.append(file_path) + else: + files_list = traverse_all_files(file_path, files_list, all_type=True) -def get_recent_images(dir_name, page_index, step, image_index, tabname): - page_index = int(page_index) - image_list = [] - if not os.path.exists(dir_name): - pass - elif os.path.isdir(dir_name): - image_list = traverse_all_files(dir_name, image_list) - image_list = sorted(image_list, key=lambda file: -os.path.getctime(os.path.join(dir_name, file))) + for file in files_list: + date_str = time.strftime("%Y%m%d",time.localtime(os.path.getmtime(file))) + file_path = os.path.dirname(file) + hash_path = hashlib.md5(file_path.encode()).hexdigest() + path = os.path.join(dir_name, date_str, hash_path) + if not os.path.exists(path): + os.makedirs(path) + if log_file is None: + log_file = open(os.path.join(bak_path,"path_mapping.csv"),"a") + log_file.write(f"{hash_path},{file_path}\n") + reduplicative_file_move(file, path) + + date_list = [] + f_list = os.listdir(dir_name) + for f in f_list: + if is_valid_date(f): + date_list.append(f) + elif f == system_bak_path: + continue + else: + try: + reduplicative_file_move(os.path.join(dir_name, f), bak_path) + except: + pass + + today = time.strftime("%Y%m%d",time.localtime(time.time())) + if today not in date_list: + date_list.append(today) + return sorted(date_list, reverse=True) + +def archive_images(dir_name, date_to): + filenames = [] + batch_size =int(opts.images_history_num_per_page * opts.images_history_pages_num) + if batch_size <= 0: + batch_size = opts.images_history_num_per_page * 6 + today = time.strftime("%Y%m%d",time.localtime(time.time())) + date_to = today if date_to is None or date_to == "" else date_to + date_to_bak = date_to + if False: #opts.images_history_reconstruct_directory: + date_list = auto_sorting(dir_name) + for date in date_list: + if date <= date_to: + path = os.path.join(dir_name, date) + if date == today and not os.path.exists(path): + continue + filenames = traverse_all_files(path, filenames) + if len(filenames) > batch_size: + break + filenames = sorted(filenames, key=lambda file: -os.path.getmtime(file)) else: - print(f'ERROR: "{dir_name}" is not a directory. Check the path in the settings.', file=sys.stderr) - num = 48 if tabname != "extras" else 12 - max_page_index = len(image_list) // num + 1 - page_index = max_page_index if page_index == -1 else page_index + step - page_index = 1 if page_index < 1 else page_index - page_index = max_page_index if page_index > max_page_index else page_index - idx_frm = (page_index - 1) * num - image_list = image_list[idx_frm:idx_frm + num] - image_index = int(image_index) - if image_index < 0 or image_index > len(image_list) - 1: - current_file = None - hidden = None - else: - current_file = image_list[int(image_index)] - hidden = os.path.join(dir_name, current_file) - return [os.path.join(dir_name, file) for file in image_list], page_index, image_list, current_file, hidden, "" + filenames = traverse_all_files(dir_name, filenames) + total_num = len(filenames) + tmparray = [(os.path.getmtime(file), file) for file in filenames ] + date_stamp = time.mktime(time.strptime(date_to, "%Y%m%d")) + 86400 + filenames = [] + date_list = {date_to:None} + date = time.strftime("%Y%m%d",time.localtime(time.time())) + for t, f in tmparray: + date = time.strftime("%Y%m%d",time.localtime(t)) + date_list[date] = None + if t <= date_stamp: + filenames.append((t, f ,date)) + date_list = sorted(list(date_list.keys()), reverse=True) + sort_array = sorted(filenames, key=lambda x:-x[0]) + if len(sort_array) > batch_size: + date = sort_array[batch_size][2] + filenames = [x[1] for x in sort_array] + else: + date = date_to if len(sort_array) == 0 else sort_array[-1][2] + filenames = [x[1] for x in sort_array] + filenames = [x[1] for x in sort_array if x[2]>= date] + num = len(filenames) + last_date_from = date_to_bak if num == 0 else time.strftime("%Y%m%d", time.localtime(time.mktime(time.strptime(date, "%Y%m%d")) - 1000)) + date = date[:4] + "/" + date[4:6] + "/" + date[6:8] + date_to_bak = date_to_bak[:4] + "/" + date_to_bak[4:6] + "/" + date_to_bak[6:8] + load_info = "
" + load_info += f"{total_num} images in this directory. Loaded {num} images during {date} - {date_to_bak}, divided into {int((num + 1) // opts.images_history_num_per_page + 1)} pages" + load_info += "
" + _, image_list, _, _, visible_num = get_recent_images(1, 0, filenames) + return ( + date_to, + load_info, + filenames, + 1, + image_list, + "", + "", + visible_num, + last_date_from, + gradio.update(visible=total_num > num) + ) - -def first_page_click(dir_name, page_index, image_index, tabname): - return get_recent_images(dir_name, 1, 0, image_index, tabname) - - -def end_page_click(dir_name, page_index, image_index, tabname): - return get_recent_images(dir_name, -1, 0, image_index, tabname) - - -def prev_page_click(dir_name, page_index, image_index, tabname): - return get_recent_images(dir_name, page_index, -1, image_index, tabname) - - -def next_page_click(dir_name, page_index, image_index, tabname): - return get_recent_images(dir_name, page_index, 1, image_index, tabname) - - -def page_index_change(dir_name, page_index, image_index, tabname): - return get_recent_images(dir_name, page_index, 0, image_index, tabname) - - -def show_image_info(num, image_path, filenames): - # print(f"select image {num}") - file = filenames[int(num)] - return file, num, os.path.join(image_path, file) - - -def delete_image(delete_num, tabname, dir_name, name, page_index, filenames, image_index): +def delete_image(delete_num, name, filenames, image_index, visible_num): if name == "": return filenames, delete_num else: delete_num = int(delete_num) + visible_num = int(visible_num) + image_index = int(image_index) index = list(filenames).index(name) i = 0 new_file_list = [] for name in filenames: if i >= index and i < index + delete_num: - path = os.path.join(dir_name, name) - if os.path.exists(path): - print(f"Delete file {path}") - os.remove(path) - txt_file = os.path.splitext(path)[0] + ".txt" + if os.path.exists(name): + if visible_num == image_index: + new_file_list.append(name) + i += 1 + continue + print(f"Delete file {name}") + os.remove(name) + visible_num -= 1 + txt_file = os.path.splitext(name)[0] + ".txt" if os.path.exists(txt_file): os.remove(txt_file) else: - print(f"Not exists file {path}") + print(f"Not exists file {name}") else: new_file_list.append(name) i += 1 - return new_file_list, 1 + return new_file_list, 1, visible_num +def save_image(file_name): + if file_name is not None and os.path.exists(file_name): + shutil.copy(file_name, opts.outdir_save) + +def get_recent_images(page_index, step, filenames): + page_index = int(page_index) + num_of_imgs_per_page = int(opts.images_history_num_per_page) + max_page_index = len(filenames) // num_of_imgs_per_page + 1 + page_index = max_page_index if page_index == -1 else page_index + step + page_index = 1 if page_index < 1 else page_index + page_index = max_page_index if page_index > max_page_index else page_index + idx_frm = (page_index - 1) * num_of_imgs_per_page + image_list = filenames[idx_frm:idx_frm + num_of_imgs_per_page] + length = len(filenames) + visible_num = num_of_imgs_per_page if idx_frm + num_of_imgs_per_page <= length else length % num_of_imgs_per_page + visible_num = num_of_imgs_per_page if visible_num == 0 else visible_num + return page_index, image_list, "", "", visible_num + +def loac_batch_click(date_to): + if date_to is None: + return time.strftime("%Y%m%d",time.localtime(time.time())), [] + else: + return None, [] +def forward_click(last_date_from, date_to_recorder): + if len(date_to_recorder) == 0: + return None, [] + if last_date_from == date_to_recorder[-1]: + date_to_recorder = date_to_recorder[:-1] + if len(date_to_recorder) == 0: + return None, [] + return date_to_recorder[-1], date_to_recorder[:-1] + +def backward_click(last_date_from, date_to_recorder): + if last_date_from is None or last_date_from == "": + return time.strftime("%Y%m%d",time.localtime(time.time())), [] + if len(date_to_recorder) == 0 or last_date_from != date_to_recorder[-1]: + date_to_recorder.append(last_date_from) + return last_date_from, date_to_recorder + + +def first_page_click(page_index, filenames): + return get_recent_images(1, 0, filenames) + +def end_page_click(page_index, filenames): + return get_recent_images(-1, 0, filenames) + +def prev_page_click(page_index, filenames): + return get_recent_images(page_index, -1, filenames) + +def next_page_click(page_index, filenames): + return get_recent_images(page_index, 1, filenames) + +def page_index_change(page_index, filenames): + return get_recent_images(page_index, 0, filenames) + +def show_image_info(tabname_box, num, page_index, filenames): + file = filenames[int(num) + int((page_index - 1) * int(opts.images_history_num_per_page))] + tm = "
" + time.strftime("%Y-%m-%d %H:%M:%S",time.localtime(os.path.getmtime(file))) + "
" + return file, tm, num, file + +def enable_page_buttons(): + return gradio.update(visible=True) + +def change_dir(img_dir, date_to): + warning = None + try: + if os.path.exists(img_dir): + try: + f = os.listdir(img_dir) + except: + warning = f"'{img_dir} is not a directory" + else: + warning = "The directory is not exist" + except: + warning = "The format of the directory is incorrect" + if warning is None: + today = time.strftime("%Y%m%d",time.localtime(time.time())) + return gradio.update(visible=False), gradio.update(visible=True), None, None if date_to != today else today, gradio.update(visible=True), gradio.update(visible=True) + else: + return gradio.update(visible=True), gradio.update(visible=False), warning, date_to, gradio.update(visible=False), gradio.update(visible=False) def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict): - if opts.outdir_samples != "": - dir_name = opts.outdir_samples - elif tabname == "txt2img": + custom_dir = False + if tabname == "txt2img": dir_name = opts.outdir_txt2img_samples elif tabname == "img2img": dir_name = opts.outdir_img2img_samples elif tabname == "extras": dir_name = opts.outdir_extras_samples + elif tabname == faverate_tab_name: + dir_name = opts.outdir_save else: - return - with gr.Row(): - renew_page = gr.Button('Renew Page', elem_id=tabname + "_images_history_renew_page") - first_page = gr.Button('First Page') - prev_page = gr.Button('Prev Page') - page_index = gr.Number(value=1, label="Page Index") - next_page = gr.Button('Next Page') - end_page = gr.Button('End Page') - with gr.Row(elem_id=tabname + "_images_history"): - with gr.Row(): - with gr.Column(scale=2): - history_gallery = gr.Gallery(show_label=False, elem_id=tabname + "_images_history_gallery").style(grid=6) - with gr.Row(): - delete_num = gr.Number(value=1, interactive=True, label="number of images to delete consecutively next") - delete = gr.Button('Delete', elem_id=tabname + "_images_history_del_button") - with gr.Column(): - with gr.Row(): - pnginfo_send_to_txt2img = gr.Button('Send to txt2img') - pnginfo_send_to_img2img = gr.Button('Send to img2img') - with gr.Row(): - with gr.Column(): - img_file_info = gr.Textbox(label="Generate Info", interactive=False) - img_file_name = gr.Textbox(label="File Name", interactive=False) - with gr.Row(): + custom_dir = True + dir_name = None + + if not custom_dir: + d = dir_name.split("/") + dir_name = d[0] + for p in d[1:]: + dir_name = os.path.join(dir_name, p) + if not os.path.exists(dir_name): + os.makedirs(dir_name) + + with gr.Column() as page_panel: + with gr.Row(): + with gr.Column(scale=1, visible=not custom_dir) as load_batch_box: + load_batch = gr.Button('Load', elem_id=tabname + "_images_history_start", full_width=True) + with gr.Column(scale=4): + with gr.Row(): + img_path = gr.Textbox(dir_name, label="Images directory", placeholder="Input images directory", interactive=custom_dir) + with gr.Row(): + with gr.Column(visible=False, scale=1) as batch_panel: + with gr.Row(): + forward = gr.Button('Prev batch') + backward = gr.Button('Next batch') + with gr.Column(scale=3): + load_info = gr.HTML(visible=not custom_dir) + with gr.Row(visible=False) as warning: + warning_box = gr.Textbox("Message", interactive=False) + + with gr.Row(visible=not custom_dir, elem_id=tabname + "_images_history") as main_panel: + with gr.Column(scale=2): + with gr.Row(visible=True) as turn_page_buttons: + #date_to = gr.Dropdown(label="Date to") + first_page = gr.Button('First Page') + prev_page = gr.Button('Prev Page') + page_index = gr.Number(value=1, label="Page Index") + next_page = gr.Button('Next Page') + end_page = gr.Button('End Page') + + history_gallery = gr.Gallery(show_label=False, elem_id=tabname + "_images_history_gallery").style(grid=opts.images_history_grid_num) + with gr.Row(): + delete_num = gr.Number(value=1, interactive=True, label="number of images to delete consecutively next") + delete = gr.Button('Delete', elem_id=tabname + "_images_history_del_button") + + with gr.Column(): + with gr.Row(): + with gr.Column(): + img_file_info = gr.Textbox(label="Generate Info", interactive=False, lines=6) + gr.HTML("
") + img_file_name = gr.Textbox(value="", label="File Name", interactive=False) + img_file_time= gr.HTML() + with gr.Row(): + if tabname != faverate_tab_name: + save_btn = gr.Button('Collect') + pnginfo_send_to_txt2img = gr.Button('Send to txt2img') + pnginfo_send_to_img2img = gr.Button('Send to img2img') + + # hiden items + with gr.Row(visible=False): + renew_page = gr.Button('Refresh page', elem_id=tabname + "_images_history_renew_page") + batch_date_to = gr.Textbox(label="Date to") + visible_img_num = gr.Number() + date_to_recorder = gr.State([]) + last_date_from = gr.Textbox() + tabname_box = gr.Textbox(tabname) + image_index = gr.Textbox(value=-1) + set_index = gr.Button('set_index', elem_id=tabname + "_images_history_set_index") + filenames = gr.State() + all_images_list = gr.State() + hidden = gr.Image(type="pil") + info1 = gr.Textbox() + info2 = gr.Textbox() - img_path = gr.Textbox(dir_name.rstrip("/"), visible=False) - tabname_box = gr.Textbox(tabname, visible=False) - image_index = gr.Textbox(value=-1, visible=False) - set_index = gr.Button('set_index', elem_id=tabname + "_images_history_set_index", visible=False) - filenames = gr.State() - hidden = gr.Image(type="pil", visible=False) - info1 = gr.Textbox(visible=False) - info2 = gr.Textbox(visible=False) + img_path.submit(change_dir, inputs=[img_path, batch_date_to], outputs=[warning, main_panel, warning_box, batch_date_to, load_batch_box, load_info]) - # turn pages - gallery_inputs = [img_path, page_index, image_index, tabname_box] - gallery_outputs = [history_gallery, page_index, filenames, img_file_name, hidden, img_file_name] + #change batch + change_date_output = [batch_date_to, load_info, filenames, page_index, history_gallery, img_file_name, img_file_time, visible_img_num, last_date_from, batch_panel] + + batch_date_to.change(archive_images, inputs=[img_path, batch_date_to], outputs=change_date_output) + batch_date_to.change(enable_page_buttons, inputs=None, outputs=[turn_page_buttons]) + batch_date_to.change(fn=None, inputs=[tabname_box], outputs=None, _js="images_history_turnpage") - first_page.click(first_page_click, _js="images_history_turnpage", inputs=gallery_inputs, outputs=gallery_outputs) - next_page.click(next_page_click, _js="images_history_turnpage", inputs=gallery_inputs, outputs=gallery_outputs) - prev_page.click(prev_page_click, _js="images_history_turnpage", inputs=gallery_inputs, outputs=gallery_outputs) - end_page.click(end_page_click, _js="images_history_turnpage", inputs=gallery_inputs, outputs=gallery_outputs) - page_index.submit(page_index_change, _js="images_history_turnpage", inputs=gallery_inputs, outputs=gallery_outputs) - renew_page.click(page_index_change, _js="images_history_turnpage", inputs=gallery_inputs, outputs=gallery_outputs) - # page_index.change(page_index_change, inputs=[tabname_box, img_path, page_index], outputs=[history_gallery, page_index]) + load_batch.click(loac_batch_click, inputs=[batch_date_to], outputs=[batch_date_to, date_to_recorder]) + forward.click(forward_click, inputs=[last_date_from, date_to_recorder], outputs=[batch_date_to, date_to_recorder]) + backward.click(backward_click, inputs=[last_date_from, date_to_recorder], outputs=[batch_date_to, date_to_recorder]) + + + #delete + delete.click(delete_image, inputs=[delete_num, img_file_name, filenames, image_index, visible_img_num], outputs=[filenames, delete_num, visible_img_num]) + delete.click(fn=None, _js="images_history_delete", inputs=[delete_num, tabname_box, image_index], outputs=None) + if tabname != faverate_tab_name: + save_btn.click(save_image, inputs=[img_file_name], outputs=None) + + #turn page + gallery_inputs = [page_index, filenames] + gallery_outputs = [page_index, history_gallery, img_file_name, img_file_time, visible_img_num] + first_page.click(first_page_click, inputs=gallery_inputs, outputs=gallery_outputs) + next_page.click(next_page_click, inputs=gallery_inputs, outputs=gallery_outputs) + prev_page.click(prev_page_click, inputs=gallery_inputs, outputs=gallery_outputs) + end_page.click(end_page_click, inputs=gallery_inputs, outputs=gallery_outputs) + page_index.submit(page_index_change, inputs=gallery_inputs, outputs=gallery_outputs) + renew_page.click(page_index_change, inputs=gallery_inputs, outputs=gallery_outputs) + + first_page.click(fn=None, inputs=[tabname_box], outputs=None, _js="images_history_turnpage") + next_page.click(fn=None, inputs=[tabname_box], outputs=None, _js="images_history_turnpage") + prev_page.click(fn=None, inputs=[tabname_box], outputs=None, _js="images_history_turnpage") + end_page.click(fn=None, inputs=[tabname_box], outputs=None, _js="images_history_turnpage") + page_index.submit(fn=None, inputs=[tabname_box], outputs=None, _js="images_history_turnpage") + renew_page.click(fn=None, inputs=[tabname_box], outputs=None, _js="images_history_turnpage") # other funcitons - set_index.click(show_image_info, _js="images_history_get_current_img", inputs=[tabname_box, img_path, filenames], outputs=[img_file_name, image_index, hidden]) - img_file_name.change(fn=None, _js="images_history_enable_del_buttons", inputs=None, outputs=None) - delete.click(delete_image, _js="images_history_delete", inputs=[delete_num, tabname_box, img_path, img_file_name, page_index, filenames, image_index], outputs=[filenames, delete_num]) + set_index.click(show_image_info, _js="images_history_get_current_img", inputs=[tabname_box, image_index, page_index, filenames], outputs=[img_file_name, img_file_time, image_index, hidden]) + img_file_name.change(fn=None, _js="images_history_enable_del_buttons", inputs=None, outputs=None) hidden.change(fn=run_pnginfo, inputs=[hidden], outputs=[info1, img_file_info, info2]) - - # pnginfo.click(fn=run_pnginfo, inputs=[hidden], outputs=[info1, img_file_info, info2]) switch_dict["fn"](pnginfo_send_to_txt2img, switch_dict["t2i"], img_file_info, 'switch_to_txt2img') switch_dict["fn"](pnginfo_send_to_img2img, switch_dict["i2i"], img_file_info, 'switch_to_img2img_img2img') + -def create_history_tabs(gr, opts, run_pnginfo, switch_dict): +def create_history_tabs(gr, sys_opts, cmp_ops, run_pnginfo, switch_dict): + global opts; + opts = sys_opts + loads_files_num = int(opts.images_history_num_per_page) + num_of_imgs_per_page = int(opts.images_history_num_per_page * opts.images_history_pages_num) + if cmp_ops.browse_all_images: + tabs_list.append(custom_tab_name) with gr.Blocks(analytics_enabled=False) as images_history: with gr.Tabs() as tabs: - with gr.Tab("txt2img history"): - with gr.Blocks(analytics_enabled=False) as images_history_txt2img: - show_images_history(gr, opts, "txt2img", run_pnginfo, switch_dict) - with gr.Tab("img2img history"): - with gr.Blocks(analytics_enabled=False) as images_history_img2img: - show_images_history(gr, opts, "img2img", run_pnginfo, switch_dict) - with gr.Tab("extras history"): - with gr.Blocks(analytics_enabled=False) as images_history_img2img: - show_images_history(gr, opts, "extras", run_pnginfo, switch_dict) + for tab in tabs_list: + with gr.Tab(tab): + with gr.Blocks(analytics_enabled=False) : + show_images_history(gr, opts, tab, run_pnginfo, switch_dict) + gradio.Checkbox(opts.images_history_preload, elem_id="images_history_preload", visible=False) + gradio.Textbox(",".join(tabs_list), elem_id="images_history_tabnames_list", visible=False) + return images_history diff --git a/modules/img2img.py b/modules/img2img.py index eea5199b..8d9f7cf9 100644 --- a/modules/img2img.py +++ b/modules/img2img.py @@ -56,7 +56,7 @@ 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_inpaint, init_mask_inpaint, mask_mode, steps: int, sampler_index: int, mask_blur: int, 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, aesthetic_lr=0, aesthetic_weight=0, aesthetic_steps=0, aesthetic_imgs=None, aesthetic_slerp=False, aesthetic_imgs_text="", aesthetic_slerp_angle=0.15, aesthetic_text_negative=False, *args): +def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, init_img, init_img_with_mask, init_img_inpaint, init_mask_inpaint, mask_mode, steps: int, sampler_index: int, mask_blur: int, 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 @@ -109,7 +109,8 @@ def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, pro inpainting_mask_invert=inpainting_mask_invert, ) - shared.aesthetic_clip.set_aesthetic_params(p, float(aesthetic_lr), float(aesthetic_weight), int(aesthetic_steps), aesthetic_imgs, aesthetic_slerp, aesthetic_imgs_text, aesthetic_slerp_angle, aesthetic_text_negative) + p.scripts = modules.scripts.scripts_txt2img + p.script_args = args if shared.cmd_opts.enable_console_prompts: print(f"\nimg2img: {prompt}", file=shared.progress_print_out) diff --git a/modules/processing.py b/modules/processing.py index ff1ec4c9..372489f7 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -104,6 +104,12 @@ class StableDiffusionProcessing(): self.seed_resize_from_h = 0 self.seed_resize_from_w = 0 + self.scripts = None + self.script_args = None + self.all_prompts = None + self.all_seeds = None + self.all_subseeds = None + def init(self, all_prompts, all_seeds, all_subseeds): pass @@ -350,32 +356,35 @@ def process_images(p: StableDiffusionProcessing) -> Processed: shared.prompt_styles.apply_styles(p) if type(p.prompt) == list: - all_prompts = p.prompt + p.all_prompts = p.prompt else: - all_prompts = p.batch_size * p.n_iter * [p.prompt] + p.all_prompts = p.batch_size * p.n_iter * [p.prompt] if type(seed) == list: - all_seeds = seed + p.all_seeds = seed else: - all_seeds = [int(seed) + (x if p.subseed_strength == 0 else 0) for x in range(len(all_prompts))] + p.all_seeds = [int(seed) + (x if p.subseed_strength == 0 else 0) for x in range(len(p.all_prompts))] if type(subseed) == list: - all_subseeds = subseed + p.all_subseeds = subseed else: - all_subseeds = [int(subseed) + x for x in range(len(all_prompts))] + p.all_subseeds = [int(subseed) + x for x in range(len(p.all_prompts))] def infotext(iteration=0, position_in_batch=0): - return create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration, position_in_batch) + return create_infotext(p, p.all_prompts, p.all_seeds, p.all_subseeds, comments, iteration, position_in_batch) if os.path.exists(cmd_opts.embeddings_dir) and not p.do_not_reload_embeddings: model_hijack.embedding_db.load_textual_inversion_embeddings() + if p.scripts is not None: + p.scripts.run_alwayson_scripts(p) + infotexts = [] output_images = [] with torch.no_grad(), p.sd_model.ema_scope(): with devices.autocast(): - p.init(all_prompts, all_seeds, all_subseeds) + p.init(p.all_prompts, p.all_seeds, p.all_subseeds) if state.job_count == -1: state.job_count = p.n_iter @@ -387,9 +396,9 @@ def process_images(p: StableDiffusionProcessing) -> Processed: if state.interrupted: break - prompts = all_prompts[n * p.batch_size:(n + 1) * p.batch_size] - seeds = all_seeds[n * p.batch_size:(n + 1) * p.batch_size] - subseeds = all_subseeds[n * p.batch_size:(n + 1) * p.batch_size] + prompts = p.all_prompts[n * p.batch_size:(n + 1) * p.batch_size] + seeds = p.all_seeds[n * p.batch_size:(n + 1) * p.batch_size] + subseeds = p.all_subseeds[n * p.batch_size:(n + 1) * p.batch_size] if (len(prompts) == 0): break @@ -490,10 +499,10 @@ def process_images(p: StableDiffusionProcessing) -> Processed: index_of_first_image = 1 if opts.grid_save: - images.save_image(grid, p.outpath_grids, "grid", all_seeds[0], all_prompts[0], opts.grid_format, info=infotext(), short_filename=not opts.grid_extended_filename, p=p, grid=True) + images.save_image(grid, p.outpath_grids, "grid", p.all_seeds[0], p.all_prompts[0], opts.grid_format, info=infotext(), short_filename=not opts.grid_extended_filename, p=p, grid=True) devices.torch_gc() - return Processed(p, output_images, all_seeds[0], infotext() + "".join(["\n\n" + x for x in comments]), subseed=all_subseeds[0], all_prompts=all_prompts, all_seeds=all_seeds, all_subseeds=all_subseeds, index_of_first_image=index_of_first_image, infotexts=infotexts) + return Processed(p, output_images, p.all_seeds[0], infotext() + "".join(["\n\n" + x for x in comments]), subseed=p.all_subseeds[0], all_prompts=p.all_prompts, all_seeds=p.all_seeds, all_subseeds=p.all_subseeds, index_of_first_image=index_of_first_image, infotexts=infotexts) class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): diff --git a/modules/script_callbacks.py b/modules/script_callbacks.py new file mode 100644 index 00000000..866b7acd --- /dev/null +++ b/modules/script_callbacks.py @@ -0,0 +1,42 @@ + +callbacks_model_loaded = [] +callbacks_ui_tabs = [] + + +def clear_callbacks(): + callbacks_model_loaded.clear() + callbacks_ui_tabs.clear() + + +def model_loaded_callback(sd_model): + for callback in callbacks_model_loaded: + callback(sd_model) + + +def ui_tabs_callback(): + res = [] + + for callback in callbacks_ui_tabs: + res += callback() or [] + + return res + + +def on_model_loaded(callback): + """register a function to be called when the stable diffusion model is created; the model is + passed as an argument""" + callbacks_model_loaded.append(callback) + + +def on_ui_tabs(callback): + """register a function to be called when the UI is creating new tabs. + The function must either return a None, which means no new tabs to be added, or a list, where + each element is a tuple: + (gradio_component, title, elem_id) + + gradio_component is a gradio component to be used for contents of the tab (usually gr.Blocks) + title is tab text displayed to user in the UI + elem_id is HTML id for the tab + """ + callbacks_ui_tabs.append(callback) + diff --git a/modules/scripts.py b/modules/scripts.py index 1039fa9c..9323af3e 100644 --- a/modules/scripts.py +++ b/modules/scripts.py @@ -1,86 +1,175 @@ import os import sys import traceback +from collections import namedtuple import modules.ui as ui import gradio as gr from modules.processing import StableDiffusionProcessing -from modules import shared +from modules import shared, paths, script_callbacks + +AlwaysVisible = object() + class Script: filename = None args_from = None args_to = None + alwayson = False + + infotext_fields = None + """if set in ui(), this is a list of pairs of gradio component + text; the text will be used when + parsing infotext to set the value for the component; see ui.py's txt2img_paste_fields for an example + """ - # The title of the script. This is what will be displayed in the dropdown menu. def title(self): + """this function should return the title of the script. This is what will be displayed in the dropdown menu.""" + raise NotImplementedError() - # How the script is displayed in the UI. See https://gradio.app/docs/#components - # for the different UI components you can use and how to create them. - # Most UI components can return a value, such as a boolean for a checkbox. - # The returned values are passed to the run method as parameters. def ui(self, is_img2img): + """this function should create gradio UI elements. See https://gradio.app/docs/#components + The return value should be an array of all components that are used in processing. + Values of those returned componenbts will be passed to run() and process() functions. + """ + pass - # Determines when the script should be shown in the dropdown menu via the - # returned value. As an example: - # is_img2img is True if the current tab is img2img, and False if it is txt2img. - # Thus, return is_img2img to only show the script on the img2img tab. def show(self, is_img2img): + """ + is_img2img is True if this function is called for the img2img interface, and Fasle otherwise + + This function should return: + - False if the script should not be shown in UI at all + - True if the script should be shown in UI if it's scelected in the scripts drowpdown + - script.AlwaysVisible if the script should be shown in UI at all times + """ + return True - # This is where the additional processing is implemented. The parameters include - # self, the model object "p" (a StableDiffusionProcessing class, see - # processing.py), and the parameters returned by the ui method. - # Custom functions can be defined here, and additional libraries can be imported - # to be used in processing. The return value should be a Processed object, which is - # what is returned by the process_images method. - def run(self, *args): + def run(self, p, *args): + """ + This function is called if the script has been selected in the script dropdown. + It must do all processing and return the Processed object with results, same as + one returned by processing.process_images. + + Usually the processing is done by calling the processing.process_images function. + + args contains all values returned by components from ui() + """ + raise NotImplementedError() - # The description method is currently unused. - # To add a description that appears when hovering over the title, amend the "titles" - # dict in script.js to include the script title (returned by title) as a key, and - # your description as the value. + def process(self, p, *args): + """ + This function is called before processing begins for AlwaysVisible scripts. + scripts. You can modify the processing object (p) here, inject hooks, etc. + """ + + pass + def describe(self): + """unused""" return "" +current_basedir = paths.script_path + + +def basedir(): + """returns the base directory for the current script. For scripts in the main scripts directory, + this is the main directory (where webui.py resides), and for scripts in extensions directory + (ie extensions/aesthetic/script/aesthetic.py), this is extension's directory (extensions/aesthetic) + """ + return current_basedir + + scripts_data = [] +ScriptFile = namedtuple("ScriptFile", ["basedir", "filename", "path"]) +ScriptClassData = namedtuple("ScriptClassData", ["script_class", "path", "basedir"]) -def load_scripts(basedir): - if not os.path.exists(basedir): - return +def list_scripts(scriptdirname, extension): + scripts_list = [] - for filename in sorted(os.listdir(basedir)): - path = os.path.join(basedir, filename) + basedir = os.path.join(paths.script_path, scriptdirname) + if os.path.exists(basedir): + for filename in sorted(os.listdir(basedir)): + scripts_list.append(ScriptFile(paths.script_path, filename, os.path.join(basedir, filename))) - if os.path.splitext(path)[1].lower() != '.py': + extdir = os.path.join(paths.script_path, "extensions") + if os.path.exists(extdir): + for dirname in sorted(os.listdir(extdir)): + dirpath = os.path.join(extdir, dirname) + scriptdirpath = os.path.join(dirpath, scriptdirname) + + if not os.path.isdir(scriptdirpath): + continue + + for filename in sorted(os.listdir(scriptdirpath)): + scripts_list.append(ScriptFile(dirpath, filename, os.path.join(scriptdirpath, filename))) + + scripts_list = [x for x in scripts_list if os.path.splitext(x.path)[1].lower() == extension and os.path.isfile(x.path)] + + return scripts_list + + +def list_files_with_name(filename): + res = [] + + dirs = [paths.script_path] + + extdir = os.path.join(paths.script_path, "extensions") + if os.path.exists(extdir): + dirs += [os.path.join(extdir, d) for d in sorted(os.listdir(extdir))] + + for dirpath in dirs: + if not os.path.isdir(dirpath): continue - if not os.path.isfile(path): - continue + path = os.path.join(dirpath, filename) + if os.path.isfile(filename): + res.append(path) + return res + + +def load_scripts(): + global current_basedir + scripts_data.clear() + script_callbacks.clear_callbacks() + + scripts_list = list_scripts("scripts", ".py") + + syspath = sys.path + + for scriptfile in sorted(scripts_list): try: - with open(path, "r", encoding="utf8") as file: + if scriptfile.basedir != paths.script_path: + sys.path = [scriptfile.basedir] + sys.path + current_basedir = scriptfile.basedir + + with open(scriptfile.path, "r", encoding="utf8") as file: text = file.read() from types import ModuleType - compiled = compile(text, path, 'exec') - module = ModuleType(filename) + compiled = compile(text, scriptfile.path, 'exec') + module = ModuleType(scriptfile.filename) exec(compiled, module.__dict__) for key, script_class in module.__dict__.items(): if type(script_class) == type and issubclass(script_class, Script): - scripts_data.append((script_class, path)) + scripts_data.append(ScriptClassData(script_class, scriptfile.path, scriptfile.basedir)) except Exception: - print(f"Error loading script: {filename}", file=sys.stderr) + print(f"Error loading script: {scriptfile.filename}", file=sys.stderr) print(traceback.format_exc(), file=sys.stderr) + finally: + sys.path = syspath + current_basedir = paths.script_path + def wrap_call(func, filename, funcname, *args, default=None, **kwargs): try: @@ -96,56 +185,80 @@ def wrap_call(func, filename, funcname, *args, default=None, **kwargs): class ScriptRunner: def __init__(self): self.scripts = [] + self.selectable_scripts = [] + self.alwayson_scripts = [] self.titles = [] + self.infotext_fields = [] def setup_ui(self, is_img2img): - for script_class, path in scripts_data: + for script_class, path, basedir in scripts_data: script = script_class() script.filename = path - if not script.show(is_img2img): - continue + visibility = script.show(is_img2img) - self.scripts.append(script) + if visibility == AlwaysVisible: + self.scripts.append(script) + self.alwayson_scripts.append(script) + script.alwayson = True - self.titles = [wrap_call(script.title, script.filename, "title") or f"{script.filename} [error]" for script in self.scripts] + elif visibility: + self.scripts.append(script) + self.selectable_scripts.append(script) - dropdown = gr.Dropdown(label="Script", choices=["None"] + self.titles, value="None", type="index") - dropdown.save_to_config = True - inputs = [dropdown] + self.titles = [wrap_call(script.title, script.filename, "title") or f"{script.filename} [error]" for script in self.selectable_scripts] - for script in self.scripts: + inputs = [None] + inputs_alwayson = [True] + + def create_script_ui(script, inputs, inputs_alwayson): script.args_from = len(inputs) script.args_to = len(inputs) controls = wrap_call(script.ui, script.filename, "ui", is_img2img) if controls is None: - continue + return for control in controls: control.custom_script_source = os.path.basename(script.filename) - control.visible = False + if not script.alwayson: + control.visible = False + + if script.infotext_fields is not None: + self.infotext_fields += script.infotext_fields inputs += controls + inputs_alwayson += [script.alwayson for _ in controls] script.args_to = len(inputs) + for script in self.alwayson_scripts: + with gr.Group(): + create_script_ui(script, inputs, inputs_alwayson) + + dropdown = gr.Dropdown(label="Script", choices=["None"] + self.titles, value="None", type="index") + dropdown.save_to_config = True + inputs[0] = dropdown + + for script in self.selectable_scripts: + create_script_ui(script, inputs, inputs_alwayson) + def select_script(script_index): - if 0 < script_index <= len(self.scripts): - script = self.scripts[script_index-1] + if 0 < script_index <= len(self.selectable_scripts): + script = self.selectable_scripts[script_index-1] args_from = script.args_from args_to = script.args_to else: args_from = 0 args_to = 0 - return [ui.gr_show(True if i == 0 else args_from <= i < args_to) for i in range(len(inputs))] + return [ui.gr_show(True if i == 0 else args_from <= i < args_to or is_alwayson) for i, is_alwayson in enumerate(inputs_alwayson)] def init_field(title): if title == 'None': return script_index = self.titles.index(title) - script = self.scripts[script_index] + script = self.selectable_scripts[script_index] for i in range(script.args_from, script.args_to): inputs[i].visible = True @@ -164,7 +277,7 @@ class ScriptRunner: if script_index == 0: return None - script = self.scripts[script_index-1] + script = self.selectable_scripts[script_index-1] if script is None: return None @@ -176,7 +289,16 @@ class ScriptRunner: return processed - def reload_sources(self): + def run_alwayson_scripts(self, p): + for script in self.alwayson_scripts: + try: + script_args = p.script_args[script.args_from:script.args_to] + script.process(p, *script_args) + except Exception: + print(f"Error running alwayson script: {script.filename}", file=sys.stderr) + print(traceback.format_exc(), file=sys.stderr) + + def reload_sources(self, cache): for si, script in list(enumerate(self.scripts)): with open(script.filename, "r", encoding="utf8") as file: args_from = script.args_from @@ -186,9 +308,12 @@ class ScriptRunner: from types import ModuleType - compiled = compile(text, filename, 'exec') - module = ModuleType(script.filename) - exec(compiled, module.__dict__) + module = cache.get(filename, None) + if module is None: + compiled = compile(text, filename, 'exec') + module = ModuleType(script.filename) + exec(compiled, module.__dict__) + cache[filename] = module for key, script_class in module.__dict__.items(): if type(script_class) == type and issubclass(script_class, Script): @@ -197,19 +322,22 @@ class ScriptRunner: self.scripts[si].args_from = args_from self.scripts[si].args_to = args_to + scripts_txt2img = ScriptRunner() scripts_img2img = ScriptRunner() + def reload_script_body_only(): - scripts_txt2img.reload_sources() - scripts_img2img.reload_sources() + cache = {} + scripts_txt2img.reload_sources(cache) + scripts_img2img.reload_sources(cache) -def reload_scripts(basedir): +def reload_scripts(): global scripts_txt2img, scripts_img2img - scripts_data.clear() - load_scripts(basedir) + load_scripts() scripts_txt2img = ScriptRunner() scripts_img2img = ScriptRunner() + diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index 1f8587d1..0f10828e 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -332,7 +332,6 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): multipliers.append([1.0] * 75) z1 = self.process_tokens(tokens, multipliers) - z1 = shared.aesthetic_clip(z1, remade_batch_tokens) z = z1 if z is None else torch.cat((z, z1), axis=-2) remade_batch_tokens = rem_tokens diff --git a/modules/sd_models.py b/modules/sd_models.py index d99dbce8..f9b3063d 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -7,7 +7,7 @@ from omegaconf import OmegaConf from ldm.util import instantiate_from_config -from modules import shared, modelloader, devices +from modules import shared, modelloader, devices, script_callbacks from modules.paths import models_path from modules.sd_hijack_inpainting import do_inpainting_hijack, should_hijack_inpainting @@ -238,6 +238,9 @@ def load_model(checkpoint_info=None): sd_hijack.model_hijack.hijack(sd_model) sd_model.eval() + shared.sd_model = sd_model + + script_callbacks.model_loaded_callback(sd_model) print(f"Model loaded.") return sd_model @@ -252,7 +255,7 @@ def reload_model_weights(sd_model, info=None): if sd_model.sd_checkpoint_info.config != checkpoint_info.config or should_hijack_inpainting(checkpoint_info) != should_hijack_inpainting(sd_model.sd_checkpoint_info): checkpoints_loaded.clear() - shared.sd_model = load_model(checkpoint_info) + load_model(checkpoint_info) return shared.sd_model if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: diff --git a/modules/shared.py b/modules/shared.py index 03032a47..5d83971e 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -31,7 +31,6 @@ parser.add_argument("--no-half-vae", action='store_true', help="do not switch th parser.add_argument("--no-progressbar-hiding", action='store_true', help="do not hide progressbar in gradio UI (we hide it because it slows down ML if you have hardware acceleration in browser)") parser.add_argument("--max-batch-count", type=int, default=16, help="maximum batch count value for the UI") parser.add_argument("--embeddings-dir", type=str, default=os.path.join(script_path, 'embeddings'), help="embeddings directory for textual inversion (default: embeddings)") -parser.add_argument("--aesthetic_embeddings-dir", type=str, default=os.path.join(models_path, 'aesthetic_embeddings'), help="aesthetic_embeddings directory(default: aesthetic_embeddings)") parser.add_argument("--hypernetwork-dir", type=str, default=os.path.join(models_path, 'hypernetworks'), help="hypernetwork directory") parser.add_argument("--localizations-dir", type=str, default=os.path.join(script_path, 'localizations'), help="localizations directory") parser.add_argument("--allow-code", action='store_true', help="allow custom script execution from webui") @@ -81,6 +80,7 @@ parser.add_argument("--disable-safe-unpickle", action='store_true', help="disabl parser.add_argument("--api", action='store_true', help="use api=True to launch the api with the webui") parser.add_argument("--nowebui", action='store_true', help="use api=True to launch the api instead of the webui") parser.add_argument("--device-id", type=str, help="Select the default CUDA device to use (export CUDA_VISIBLE_DEVICES=0,1,etc might be needed before)", default=None) +parser.add_argument("--browse-all-images", action='store_true', help="Allow browsing all images by Image Browser", default=False) cmd_opts = parser.parse_args() restricted_opts = [ @@ -109,21 +109,6 @@ os.makedirs(cmd_opts.hypernetwork_dir, exist_ok=True) hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir) loaded_hypernetwork = None - -os.makedirs(cmd_opts.aesthetic_embeddings_dir, exist_ok=True) -aesthetic_embeddings = {} - - -def update_aesthetic_embeddings(): - global aesthetic_embeddings - aesthetic_embeddings = {f.replace(".pt", ""): os.path.join(cmd_opts.aesthetic_embeddings_dir, f) for f in - os.listdir(cmd_opts.aesthetic_embeddings_dir) if f.endswith(".pt")} - aesthetic_embeddings = OrderedDict(**{"None": None}, **aesthetic_embeddings) - - -update_aesthetic_embeddings() - - def reload_hypernetworks(): global hypernetworks @@ -333,6 +318,14 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters" 'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}), })) +options_templates.update(options_section(('images-history', "Images Browser"), { + #"images_history_reconstruct_directory": OptionInfo(False, "Reconstruct output directory structure.This can greatly improve the speed of loading , but will change the original output directory structure"), + "images_history_preload": OptionInfo(False, "Preload images at startup"), + "images_history_num_per_page": OptionInfo(36, "Number of pictures displayed on each page"), + "images_history_pages_num": OptionInfo(6, "Minimum number of pages per load "), + "images_history_grid_num": OptionInfo(6, "Number of grids in each row"), + +})) class Options: data = None @@ -407,9 +400,6 @@ sd_model = None clip_model = None -from modules.aesthetic_clip import AestheticCLIP -aesthetic_clip = AestheticCLIP() - progress_print_out = sys.stdout diff --git a/modules/txt2img.py b/modules/txt2img.py index 1761cfa2..c9d5a090 100644 --- a/modules/txt2img.py +++ b/modules/txt2img.py @@ -7,7 +7,7 @@ import modules.processing as processing from modules.ui import plaintext_to_html -def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: 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, enable_hr: bool, denoising_strength: float, firstphase_width: int, firstphase_height: int, aesthetic_lr=0, aesthetic_weight=0, aesthetic_steps=0, aesthetic_imgs=None, aesthetic_slerp=False, aesthetic_imgs_text="", aesthetic_slerp_angle=0.15, aesthetic_text_negative=False, *args): +def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: 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, enable_hr: bool, denoising_strength: float, firstphase_width: int, firstphase_height: int, *args): p = StableDiffusionProcessingTxt2Img( sd_model=shared.sd_model, outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples, @@ -36,7 +36,8 @@ def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: firstphase_height=firstphase_height if enable_hr else None, ) - shared.aesthetic_clip.set_aesthetic_params(p, float(aesthetic_lr), float(aesthetic_weight), int(aesthetic_steps), aesthetic_imgs, aesthetic_slerp, aesthetic_imgs_text, aesthetic_slerp_angle, aesthetic_text_negative) + p.scripts = modules.scripts.scripts_txt2img + p.script_args = args if cmd_opts.enable_console_prompts: print(f"\ntxt2img: {prompt}", file=shared.progress_print_out) diff --git a/modules/ui.py b/modules/ui.py index 75f98f86..29986124 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -23,10 +23,10 @@ import gradio as gr import gradio.utils import gradio.routes -from modules import sd_hijack, sd_models, localization +from modules import sd_hijack, sd_models, localization, script_callbacks from modules.paths import script_path -from modules.shared import opts, cmd_opts, restricted_opts, aesthetic_embeddings +from modules.shared import opts, cmd_opts, restricted_opts if cmd_opts.deepdanbooru: from modules.deepbooru import get_deepbooru_tags @@ -44,7 +44,6 @@ from modules.images import save_image import modules.textual_inversion.ui import modules.hypernetworks.ui -import modules.aesthetic_clip as aesthetic_clip import modules.images_history as img_his @@ -662,8 +661,6 @@ def create_ui(wrap_gradio_gpu_call): seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs() - aesthetic_weight, aesthetic_steps, aesthetic_lr, aesthetic_slerp, aesthetic_imgs, aesthetic_imgs_text, aesthetic_slerp_angle, aesthetic_text_negative = aesthetic_clip.create_ui() - with gr.Group(): custom_inputs = modules.scripts.scripts_txt2img.setup_ui(is_img2img=False) @@ -718,14 +715,6 @@ def create_ui(wrap_gradio_gpu_call): denoising_strength, firstphase_width, firstphase_height, - aesthetic_lr, - aesthetic_weight, - aesthetic_steps, - aesthetic_imgs, - aesthetic_slerp, - aesthetic_imgs_text, - aesthetic_slerp_angle, - aesthetic_text_negative ] + custom_inputs, outputs=[ @@ -804,14 +793,7 @@ def create_ui(wrap_gradio_gpu_call): (hr_options, lambda d: gr.Row.update(visible="Denoising strength" in d)), (firstphase_width, "First pass size-1"), (firstphase_height, "First pass size-2"), - (aesthetic_lr, "Aesthetic LR"), - (aesthetic_weight, "Aesthetic weight"), - (aesthetic_steps, "Aesthetic steps"), - (aesthetic_imgs, "Aesthetic embedding"), - (aesthetic_slerp, "Aesthetic slerp"), - (aesthetic_imgs_text, "Aesthetic text"), - (aesthetic_text_negative, "Aesthetic text negative"), - (aesthetic_slerp_angle, "Aesthetic slerp angle"), + *modules.scripts.scripts_txt2img.infotext_fields ] txt2img_preview_params = [ @@ -896,8 +878,6 @@ def create_ui(wrap_gradio_gpu_call): seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs() - aesthetic_weight_im, aesthetic_steps_im, aesthetic_lr_im, aesthetic_slerp_im, aesthetic_imgs_im, aesthetic_imgs_text_im, aesthetic_slerp_angle_im, aesthetic_text_negative_im = aesthetic_clip.create_ui() - with gr.Group(): custom_inputs = modules.scripts.scripts_img2img.setup_ui(is_img2img=True) @@ -988,14 +968,6 @@ def create_ui(wrap_gradio_gpu_call): inpainting_mask_invert, img2img_batch_input_dir, img2img_batch_output_dir, - aesthetic_lr_im, - aesthetic_weight_im, - aesthetic_steps_im, - aesthetic_imgs_im, - aesthetic_slerp_im, - aesthetic_imgs_text_im, - aesthetic_slerp_angle_im, - aesthetic_text_negative_im, ] + custom_inputs, outputs=[ img2img_gallery, @@ -1087,14 +1059,7 @@ def create_ui(wrap_gradio_gpu_call): (seed_resize_from_w, "Seed resize from-1"), (seed_resize_from_h, "Seed resize from-2"), (denoising_strength, "Denoising strength"), - (aesthetic_lr_im, "Aesthetic LR"), - (aesthetic_weight_im, "Aesthetic weight"), - (aesthetic_steps_im, "Aesthetic steps"), - (aesthetic_imgs_im, "Aesthetic embedding"), - (aesthetic_slerp_im, "Aesthetic slerp"), - (aesthetic_imgs_text_im, "Aesthetic text"), - (aesthetic_text_negative_im, "Aesthetic text negative"), - (aesthetic_slerp_angle_im, "Aesthetic slerp angle"), + *modules.scripts.scripts_img2img.infotext_fields ] token_button.click(fn=update_token_counter, inputs=[img2img_prompt, steps], outputs=[token_counter]) @@ -1217,12 +1182,12 @@ def create_ui(wrap_gradio_gpu_call): ) #images history images_history_switch_dict = { - "fn":modules.generation_parameters_copypaste.connect_paste, - "t2i":txt2img_paste_fields, - "i2i":img2img_paste_fields + "fn": modules.generation_parameters_copypaste.connect_paste, + "t2i": txt2img_paste_fields, + "i2i": img2img_paste_fields } - images_history = img_his.create_history_tabs(gr, opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict) + images_history = img_his.create_history_tabs(gr, opts, cmd_opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict) with gr.Blocks() as modelmerger_interface: with gr.Row().style(equal_height=False): @@ -1264,18 +1229,6 @@ def create_ui(wrap_gradio_gpu_call): with gr.Column(): create_embedding = gr.Button(value="Create embedding", variant='primary') - with gr.Tab(label="Create aesthetic images embedding"): - - new_embedding_name_ae = gr.Textbox(label="Name") - process_src_ae = gr.Textbox(label='Source directory') - batch_ae = gr.Slider(minimum=1, maximum=1024, step=1, label="Batch size", value=256) - with gr.Row(): - with gr.Column(scale=3): - gr.HTML(value="") - - with gr.Column(): - create_embedding_ae = gr.Button(value="Create images embedding", variant='primary') - with gr.Tab(label="Create hypernetwork"): new_hypernetwork_name = gr.Textbox(label="Name") new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "320", "640", "1280"]) @@ -1375,21 +1328,6 @@ def create_ui(wrap_gradio_gpu_call): ] ) - create_embedding_ae.click( - fn=aesthetic_clip.generate_imgs_embd, - inputs=[ - new_embedding_name_ae, - process_src_ae, - batch_ae - ], - outputs=[ - aesthetic_imgs, - aesthetic_imgs_im, - ti_output, - ti_outcome, - ] - ) - create_hypernetwork.click( fn=modules.hypernetworks.ui.create_hypernetwork, inputs=[ @@ -1580,10 +1518,10 @@ Requested path was: {f} if not opts.same_type(value, opts.data_labels[key].default): return gr.update(visible=True), opts.dumpjson() + oldval = opts.data.get(key, None) if cmd_opts.hide_ui_dir_config and key in restricted_opts: return gr.update(value=oldval), opts.dumpjson() - oldval = opts.data.get(key, None) opts.data[key] = value if oldval != value: @@ -1689,19 +1627,24 @@ Requested path was: {f} (img2img_interface, "img2img", "img2img"), (extras_interface, "Extras", "extras"), (pnginfo_interface, "PNG Info", "pnginfo"), - (images_history, "History", "images_history"), + (images_history, "Image Browser", "images_history"), (modelmerger_interface, "Checkpoint Merger", "modelmerger"), (train_interface, "Train", "ti"), - (settings_interface, "Settings", "settings"), ] - with open(os.path.join(script_path, "style.css"), "r", encoding="utf8") as file: - css = file.read() + interfaces += script_callbacks.ui_tabs_callback() + + interfaces += [(settings_interface, "Settings", "settings")] + + css = "" + + for cssfile in modules.scripts.list_files_with_name("style.css"): + with open(cssfile, "r", encoding="utf8") as file: + css += file.read() + "\n" if os.path.exists(os.path.join(script_path, "user.css")): with open(os.path.join(script_path, "user.css"), "r", encoding="utf8") as file: - usercss = file.read() - css += usercss + css += file.read() + "\n" if not cmd_opts.no_progressbar_hiding: css += css_hide_progressbar @@ -1924,9 +1867,9 @@ def load_javascript(raw_response): with open(os.path.join(script_path, "script.js"), "r", encoding="utf8") as jsfile: javascript = f'' - jsdir = os.path.join(script_path, "javascript") - for filename in sorted(os.listdir(jsdir)): - with open(os.path.join(jsdir, filename), "r", encoding="utf8") as jsfile: + scripts_list = modules.scripts.list_scripts("javascript", ".js") + for basedir, filename, path in scripts_list: + with open(path, "r", encoding="utf8") as jsfile: javascript += f"\n" if cmd_opts.theme is not None: @@ -1944,6 +1887,5 @@ def load_javascript(raw_response): gradio.routes.templates.TemplateResponse = template_response -reload_javascript = partial(load_javascript, - gradio.routes.templates.TemplateResponse) +reload_javascript = partial(load_javascript, gradio.routes.templates.TemplateResponse) reload_javascript() diff --git a/style.css b/style.css index 5d2bacc9..26ae36a5 100644 --- a/style.css +++ b/style.css @@ -477,7 +477,7 @@ input[type="range"]{ padding: 0; } -#refresh_sd_model_checkpoint, #refresh_sd_hypernetwork, #refresh_train_hypernetwork_name, #refresh_train_embedding_name, #refresh_localization, #refresh_aesthetic_embeddings{ +#refresh_sd_model_checkpoint, #refresh_sd_hypernetwork, #refresh_train_hypernetwork_name, #refresh_train_embedding_name, #refresh_localization{ max-width: 2.5em; min-width: 2.5em; height: 2.4em; diff --git a/webui.py b/webui.py index 87589064..b1deca1b 100644 --- a/webui.py +++ b/webui.py @@ -71,6 +71,7 @@ def wrap_gradio_gpu_call(func, extra_outputs=None): return modules.ui.wrap_gradio_call(f, extra_outputs=extra_outputs) + def initialize(): modelloader.cleanup_models() modules.sd_models.setup_model() @@ -79,9 +80,9 @@ def initialize(): shared.face_restorers.append(modules.face_restoration.FaceRestoration()) modelloader.load_upscalers() - modules.scripts.load_scripts(os.path.join(script_path, "scripts")) + modules.scripts.load_scripts() - shared.sd_model = modules.sd_models.load_model() + modules.sd_models.load_model() shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights(shared.sd_model))) shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetworks.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork))) shared.opts.onchange("sd_hypernetwork_strength", modules.hypernetworks.hypernetwork.apply_strength) @@ -145,7 +146,7 @@ def webui(): sd_samplers.set_samplers() print('Reloading Custom Scripts') - modules.scripts.reload_scripts(os.path.join(script_path, "scripts")) + modules.scripts.reload_scripts() print('Reloading modules: modules.ui') importlib.reload(modules.ui) print('Refreshing Model List')