From 192ddc04d6de0d780f73aa5fbaa8c66cd4642e1c Mon Sep 17 00:00:00 2001 From: Vladimir Mandic Date: Tue, 3 Jan 2023 10:34:51 -0500 Subject: add job info to modules --- modules/textual_inversion/preprocess.py | 1 + 1 file changed, 1 insertion(+) (limited to 'modules/textual_inversion/preprocess.py') diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py index 56b9b2eb..feb876c6 100644 --- a/modules/textual_inversion/preprocess.py +++ b/modules/textual_inversion/preprocess.py @@ -124,6 +124,7 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre files = listfiles(src) + shared.state.job = "preprocess" shared.state.textinfo = "Preprocessing..." shared.state.job_count = len(files) -- cgit v1.2.3 From 3f43d8a966ba8462ba019a5ad573f94508cd45f8 Mon Sep 17 00:00:00 2001 From: Vladimir Mandic Date: Wed, 11 Jan 2023 10:28:55 -0500 Subject: set descriptions --- modules/hypernetworks/hypernetwork.py | 4 +++- modules/textual_inversion/preprocess.py | 7 ++++++- modules/textual_inversion/textual_inversion.py | 4 +++- 3 files changed, 12 insertions(+), 3 deletions(-) (limited to 'modules/textual_inversion/preprocess.py') diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 300d3975..194679e8 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -619,7 +619,9 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step, epoch_num = hypernetwork.step // steps_per_epoch epoch_step = hypernetwork.step % steps_per_epoch - pbar.set_description(f"[Epoch {epoch_num}: {epoch_step+1}/{steps_per_epoch}]loss: {loss_step:.7f}") + description = f"Training hypernetwork [Epoch {epoch_num}: {epoch_step+1}/{steps_per_epoch}]loss: {loss_step:.7f}" + pbar.set_description(description) + shared.state.textinfo = description if hypernetwork_dir is not None and steps_done % save_hypernetwork_every == 0: # Before saving, change name to match current checkpoint. hypernetwork_name_every = f'{hypernetwork_name}-{steps_done}' diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py index feb876c6..3c1042ad 100644 --- a/modules/textual_inversion/preprocess.py +++ b/modules/textual_inversion/preprocess.py @@ -135,7 +135,8 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre params.process_caption_deepbooru = process_caption_deepbooru params.preprocess_txt_action = preprocess_txt_action - for index, imagefile in enumerate(tqdm.tqdm(files)): + pbar = tqdm.tqdm(files) + for index, imagefile in enumerate(pbar): params.subindex = 0 filename = os.path.join(src, imagefile) try: @@ -143,6 +144,10 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre except Exception: continue + description = f"Preprocessing [Image {index}/{len(files)}]" + pbar.set_description(description) + shared.state.textinfo = description + params.src = filename existing_caption = None diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index 3866c154..b915b091 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -476,7 +476,9 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_ epoch_num = embedding.step // steps_per_epoch epoch_step = embedding.step % steps_per_epoch - pbar.set_description(f"[Epoch {epoch_num}: {epoch_step+1}/{steps_per_epoch}]loss: {loss_step:.7f}") + description = f"Training textual inversion [Epoch {epoch_num}: {epoch_step+1}/{steps_per_epoch}]loss: {loss_step:.7f}" + pbar.set_description(description) + shared.state.textinfo = description if embedding_dir is not None and steps_done % save_embedding_every == 0: # Before saving, change name to match current checkpoint. embedding_name_every = f'{embedding_name}-{steps_done}' -- cgit v1.2.3 From d8b90ac121cbf0c18b1dc9d56a5e1d14ca51e74e Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sun, 15 Jan 2023 18:50:56 +0300 Subject: big rework of progressbar/preview system to allow multiple users to prompts at the same time and do not get previews of each other --- javascript/progressbar.js | 249 ++++++++++++++++--------- javascript/textualInversion.js | 13 +- javascript/ui.js | 33 +++- modules/call_queue.py | 19 +- modules/hypernetworks/hypernetwork.py | 6 +- modules/img2img.py | 2 +- modules/progress.py | 96 ++++++++++ modules/sd_samplers.py | 2 +- modules/shared.py | 16 +- modules/textual_inversion/preprocess.py | 2 +- modules/textual_inversion/textual_inversion.py | 6 +- modules/txt2img.py | 2 +- modules/ui.py | 41 ++-- modules/ui_progress.py | 101 ---------- style.css | 74 +++++--- webui.py | 3 + 16 files changed, 390 insertions(+), 275 deletions(-) create mode 100644 modules/progress.py delete mode 100644 modules/ui_progress.py (limited to 'modules/textual_inversion/preprocess.py') diff --git a/javascript/progressbar.js b/javascript/progressbar.js index d6323ed9..b7524ef7 100644 --- a/javascript/progressbar.js +++ b/javascript/progressbar.js @@ -1,82 +1,25 @@ // code related to showing and updating progressbar shown as the image is being made -global_progressbars = {} -galleries = {} -galleryObservers = {} - -// this tracks launches of window.setTimeout for progressbar to prevent starting a new timeout when the previous is still running -timeoutIds = {} -function check_progressbar(id_part, id_progressbar, id_progressbar_span, id_skip, id_interrupt, id_preview, id_gallery){ - // gradio 3.8's enlightened approach allows them to create two nested div elements inside each other with same id - // every time you use gr.HTML(elem_id='xxx'), so we handle this here - var progressbar = gradioApp().querySelector("#"+id_progressbar+" #"+id_progressbar) - var progressbarParent - if(progressbar){ - progressbarParent = gradioApp().querySelector("#"+id_progressbar) - } else{ - progressbar = gradioApp().getElementById(id_progressbar) - progressbarParent = null - } - var skip = id_skip ? gradioApp().getElementById(id_skip) : null - var interrupt = gradioApp().getElementById(id_interrupt) - - if(opts.show_progress_in_title && progressbar && progressbar.offsetParent){ - if(progressbar.innerText){ - let newtitle = '[' + progressbar.innerText.trim() + '] Stable Diffusion'; - if(document.title != newtitle){ - document.title = newtitle; - } - }else{ - let newtitle = 'Stable Diffusion' - if(document.title != newtitle){ - document.title = newtitle; - } - } - } - - if(progressbar!= null && progressbar != global_progressbars[id_progressbar]){ - global_progressbars[id_progressbar] = progressbar - - var mutationObserver = new MutationObserver(function(m){ - if(timeoutIds[id_part]) return; - - preview = gradioApp().getElementById(id_preview) - gallery = gradioApp().getElementById(id_gallery) +galleries = {} +storedGallerySelections = {} +galleryObservers = {} - if(preview != null && gallery != null){ - preview.style.width = gallery.clientWidth + "px" - preview.style.height = gallery.clientHeight + "px" - if(progressbarParent) progressbar.style.width = progressbarParent.clientWidth + "px" +function rememberGallerySelection(id_gallery){ + storedGallerySelections[id_gallery] = getGallerySelectedIndex(id_gallery) +} - //only watch gallery if there is a generation process going on - check_gallery(id_gallery); +function getGallerySelectedIndex(id_gallery){ + let galleryButtons = gradioApp().querySelectorAll('#'+id_gallery+' .gallery-item') + let galleryBtnSelected = gradioApp().querySelector('#'+id_gallery+' .gallery-item.\\!ring-2') - var progressDiv = gradioApp().querySelectorAll('#' + id_progressbar_span).length > 0; - if(progressDiv){ - timeoutIds[id_part] = window.setTimeout(function() { - timeoutIds[id_part] = null - requestMoreProgress(id_part, id_progressbar_span, id_skip, id_interrupt) - }, 500) - } else{ - if (skip) { - skip.style.display = "none" - } - interrupt.style.display = "none" + let currentlySelectedIndex = -1 + galleryButtons.forEach(function(v, i){ if(v==galleryBtnSelected) { currentlySelectedIndex = i } }) - //disconnect observer once generation finished, so user can close selected image if they want - if (galleryObservers[id_gallery]) { - galleryObservers[id_gallery].disconnect(); - galleries[id_gallery] = null; - } - } - } - - }); - mutationObserver.observe( progressbar, { childList:true, subtree:true }) - } + return currentlySelectedIndex } +// this is a workaround for https://github.com/gradio-app/gradio/issues/2984 function check_gallery(id_gallery){ let gallery = gradioApp().getElementById(id_gallery) // if gallery has no change, no need to setting up observer again. @@ -85,10 +28,16 @@ function check_gallery(id_gallery){ if(galleryObservers[id_gallery]){ galleryObservers[id_gallery].disconnect(); } - let prevSelectedIndex = selected_gallery_index(); + + storedGallerySelections[id_gallery] = -1 + galleryObservers[id_gallery] = new MutationObserver(function (){ let galleryButtons = gradioApp().querySelectorAll('#'+id_gallery+' .gallery-item') let galleryBtnSelected = gradioApp().querySelector('#'+id_gallery+' .gallery-item.\\!ring-2') + let currentlySelectedIndex = getGallerySelectedIndex(id_gallery) + prevSelectedIndex = storedGallerySelections[id_gallery] + storedGallerySelections[id_gallery] = -1 + if (prevSelectedIndex !== -1 && galleryButtons.length>prevSelectedIndex && !galleryBtnSelected) { // automatically re-open previously selected index (if exists) activeElement = gradioApp().activeElement; @@ -120,30 +69,150 @@ function check_gallery(id_gallery){ } onUiUpdate(function(){ - check_progressbar('txt2img', 'txt2img_progressbar', 'txt2img_progress_span', 'txt2img_skip', 'txt2img_interrupt', 'txt2img_preview', 'txt2img_gallery') - check_progressbar('img2img', 'img2img_progressbar', 'img2img_progress_span', 'img2img_skip', 'img2img_interrupt', 'img2img_preview', 'img2img_gallery') - check_progressbar('ti', 'ti_progressbar', 'ti_progress_span', '', 'ti_interrupt', 'ti_preview', 'ti_gallery') + check_gallery('txt2img_gallery') + check_gallery('img2img_gallery') }) -function requestMoreProgress(id_part, id_progressbar_span, id_skip, id_interrupt){ - btn = gradioApp().getElementById(id_part+"_check_progress"); - if(btn==null) return; - - btn.click(); - var progressDiv = gradioApp().querySelectorAll('#' + id_progressbar_span).length > 0; - var skip = id_skip ? gradioApp().getElementById(id_skip) : null - var interrupt = gradioApp().getElementById(id_interrupt) - if(progressDiv && interrupt){ - if (skip) { - skip.style.display = "block" +function request(url, data, handler, errorHandler){ + var xhr = new XMLHttpRequest(); + var url = url; + xhr.open("POST", url, true); + xhr.setRequestHeader("Content-Type", "application/json"); + xhr.onreadystatechange = function () { + if (xhr.readyState === 4) { + if (xhr.status === 200) { + var js = JSON.parse(xhr.responseText); + handler(js) + } else{ + errorHandler() + } } - interrupt.style.display = "block" + }; + var js = JSON.stringify(data); + xhr.send(js); +} + +function pad2(x){ + return x<10 ? '0'+x : x +} + +function formatTime(secs){ + if(secs > 3600){ + return pad2(Math.floor(secs/60/60)) + ":" + pad2(Math.floor(secs/60)%60) + ":" + pad2(Math.floor(secs)%60) + } else if(secs > 60){ + return pad2(Math.floor(secs/60)) + ":" + pad2(Math.floor(secs)%60) + } else{ + return Math.floor(secs) + "s" } } -function requestProgress(id_part){ - btn = gradioApp().getElementById(id_part+"_check_progress_initial"); - if(btn==null) return; +function randomId(){ + return "task(" + Math.random().toString(36).slice(2, 7) + Math.random().toString(36).slice(2, 7) + Math.random().toString(36).slice(2, 7)+")" +} + +// starts sending progress requests to "/internal/progress" uri, creating progressbar above progressbarContainer element and +// preview inside gallery element. Cleans up all created stuff when the task is over and calls atEnd. +// calls onProgress every time there is a progress update +function requestProgress(id_task, progressbarContainer, gallery, atEnd, onProgress){ + var dateStart = new Date() + var wasEverActive = false + var parentProgressbar = progressbarContainer.parentNode + var parentGallery = gallery.parentNode + + var divProgress = document.createElement('div') + divProgress.className='progressDiv' + var divInner = document.createElement('div') + divInner.className='progress' + + divProgress.appendChild(divInner) + parentProgressbar.insertBefore(divProgress, progressbarContainer) + + var livePreview = document.createElement('div') + livePreview.className='livePreview' + parentGallery.insertBefore(livePreview, gallery) + + var removeProgressBar = function(){ + parentProgressbar.removeChild(divProgress) + parentGallery.removeChild(livePreview) + atEnd() + } + + var fun = function(id_task, id_live_preview){ + request("/internal/progress", {"id_task": id_task, "id_live_preview": id_live_preview}, function(res){ + console.log(res) + + if(res.completed){ + removeProgressBar() + return + } + + var rect = progressbarContainer.getBoundingClientRect() + + if(rect.width){ + divProgress.style.width = rect.width + "px"; + } + + progressText = "" + + divInner.style.width = ((res.progress || 0) * 100.0) + '%' + + if(res.progress > 0){ + progressText = ((res.progress || 0) * 100.0).toFixed(0) + '%' + } + + if(res.eta){ + progressText += " ETA: " + formatTime(res.eta) + } else if(res.textinfo){ + progressText += " " + res.textinfo + } + + divInner.textContent = progressText + + var elapsedFromStart = (new Date() - dateStart) / 1000 + + if(res.active) wasEverActive = true; + + if(! res.active && wasEverActive){ + removeProgressBar() + return + } + + if(elapsedFromStart > 5 && !res.queued && !res.active){ + removeProgressBar() + return + } + + + if(res.live_preview){ + var img = new Image(); + img.onload = function() { + var rect = gallery.getBoundingClientRect() + if(rect.width){ + livePreview.style.width = rect.width + "px" + livePreview.style.height = rect.height + "px" + } + + livePreview.innerHTML = '' + livePreview.appendChild(img) + if(livePreview.childElementCount > 2){ + livePreview.removeChild(livePreview.firstElementChild) + } + } + img.src = res.live_preview; + } + + + if(onProgress){ + onProgress(res) + } + + setTimeout(() => { + fun(id_task, res.id_live_preview); + }, 500) + }, function(){ + removeProgressBar() + }) + } - btn.click(); + fun(id_task, 0) } diff --git a/javascript/textualInversion.js b/javascript/textualInversion.js index 8061be08..0354b860 100644 --- a/javascript/textualInversion.js +++ b/javascript/textualInversion.js @@ -1,8 +1,17 @@ + function start_training_textual_inversion(){ - requestProgress('ti') gradioApp().querySelector('#ti_error').innerHTML='' - return args_to_array(arguments) + var id = randomId() + requestProgress(id, gradioApp().getElementById('ti_output'), gradioApp().getElementById('ti_gallery'), function(){}, function(progress){ + gradioApp().getElementById('ti_progress').innerHTML = progress.textinfo + }) + + var res = args_to_array(arguments) + + res[0] = id + + return res } diff --git a/javascript/ui.js b/javascript/ui.js index f8279124..ecf97cb3 100644 --- a/javascript/ui.js +++ b/javascript/ui.js @@ -126,18 +126,41 @@ function create_submit_args(args){ return res } +function showSubmitButtons(tabname, show){ + gradioApp().getElementById(tabname+'_interrupt').style.display = show ? "none" : "block" + gradioApp().getElementById(tabname+'_skip').style.display = show ? "none" : "block" +} + function submit(){ - requestProgress('txt2img') + rememberGallerySelection('txt2img_gallery') + showSubmitButtons('txt2img', false) + + var id = randomId() + requestProgress(id, gradioApp().getElementById('txt2img_gallery_container'), gradioApp().getElementById('txt2img_gallery'), function(){ + showSubmitButtons('txt2img', true) + + }) - return create_submit_args(arguments) + var res = create_submit_args(arguments) + + res[0] = id + + return res } function submit_img2img(){ - requestProgress('img2img') + rememberGallerySelection('img2img_gallery') + showSubmitButtons('img2img', false) + + var id = randomId() + requestProgress(id, gradioApp().getElementById('img2img_gallery_container'), gradioApp().getElementById('img2img_gallery'), function(){ + showSubmitButtons('img2img', true) + }) - res = create_submit_args(arguments) + var res = create_submit_args(arguments) - res[0] = get_tab_index('mode_img2img') + res[0] = id + res[1] = get_tab_index('mode_img2img') return res } diff --git a/modules/call_queue.py b/modules/call_queue.py index 4cd49533..92097c15 100644 --- a/modules/call_queue.py +++ b/modules/call_queue.py @@ -4,7 +4,7 @@ import threading import traceback import time -from modules import shared +from modules import shared, progress queue_lock = threading.Lock() @@ -22,12 +22,23 @@ def wrap_queued_call(func): def wrap_gradio_gpu_call(func, extra_outputs=None): def f(*args, **kwargs): - shared.state.begin() + # if the first argument is a string that says "task(...)", it is treated as a job id + if len(args) > 0 and type(args[0]) == str and args[0][0:5] == "task(" and args[0][-1] == ")": + id_task = args[0] + progress.add_task_to_queue(id_task) + else: + id_task = None with queue_lock: - res = func(*args, **kwargs) + shared.state.begin() + progress.start_task(id_task) + + try: + res = func(*args, **kwargs) + finally: + progress.finish_task(id_task) - shared.state.end() + shared.state.end() return res diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 3aebefa8..ae6af516 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -453,7 +453,7 @@ def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None, shared.reload_hypernetworks() -def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, varsize, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, create_image_every, save_hypernetwork_every, template_filename, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height): +def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, varsize, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, create_image_every, save_hypernetwork_every, template_filename, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height): # images allows training previews to have infotext. Importing it at the top causes a circular import problem. from modules import images @@ -629,7 +629,6 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step, description = f"Training hypernetwork [Epoch {epoch_num}: {epoch_step+1}/{steps_per_epoch}]loss: {loss_step:.7f}" pbar.set_description(description) - shared.state.textinfo = description if hypernetwork_dir is not None and steps_done % save_hypernetwork_every == 0: # Before saving, change name to match current checkpoint. hypernetwork_name_every = f'{hypernetwork_name}-{steps_done}' @@ -701,7 +700,8 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step, torch.cuda.set_rng_state_all(cuda_rng_state) hypernetwork.train() if image is not None: - shared.state.current_image = image + shared.state.assign_current_image(image) + last_saved_image, last_text_info = images.save_image(image, images_dir, "", p.seed, p.prompt, shared.opts.samples_format, processed.infotexts[0], p=p, forced_filename=forced_filename, save_to_dirs=False) last_saved_image += f", prompt: {preview_text}" diff --git a/modules/img2img.py b/modules/img2img.py index f62783c6..f4a03c57 100644 --- a/modules/img2img.py +++ b/modules/img2img.py @@ -59,7 +59,7 @@ 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, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, *args): +def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, *args): is_batch = mode == 5 if mode == 0: # img2img diff --git a/modules/progress.py b/modules/progress.py new file mode 100644 index 00000000..3327b883 --- /dev/null +++ b/modules/progress.py @@ -0,0 +1,96 @@ +import base64 +import io +import time + +import gradio as gr +from pydantic import BaseModel, Field + +from modules.shared import opts + +import modules.shared as shared + + +current_task = None +pending_tasks = {} +finished_tasks = [] + + +def start_task(id_task): + global current_task + + current_task = id_task + pending_tasks.pop(id_task, None) + + +def finish_task(id_task): + global current_task + + if current_task == id_task: + current_task = None + + finished_tasks.append(id_task) + if len(finished_tasks) > 16: + finished_tasks.pop(0) + + +def add_task_to_queue(id_job): + pending_tasks[id_job] = time.time() + + +class ProgressRequest(BaseModel): + id_task: str = Field(default=None, title="Task ID", description="id of the task to get progress for") + id_live_preview: int = Field(default=-1, title="Live preview image ID", description="id of last received last preview image") + + +class ProgressResponse(BaseModel): + active: bool = Field(title="Whether the task is being worked on right now") + queued: bool = Field(title="Whether the task is in queue") + completed: bool = Field(title="Whether the task has already finished") + progress: float = Field(default=None, title="Progress", description="The progress with a range of 0 to 1") + eta: float = Field(default=None, title="ETA in secs") + live_preview: str = Field(default=None, title="Live preview image", description="Current live preview; a data: uri") + id_live_preview: int = Field(default=None, title="Live preview image ID", description="Send this together with next request to prevent receiving same image") + textinfo: str = Field(default=None, title="Info text", description="Info text used by WebUI.") + + +def setup_progress_api(app): + return app.add_api_route("/internal/progress", progressapi, methods=["POST"], response_model=ProgressResponse) + + +def progressapi(req: ProgressRequest): + active = req.id_task == current_task + queued = req.id_task in pending_tasks + completed = req.id_task in finished_tasks + + if not active: + return ProgressResponse(active=active, queued=queued, completed=completed, id_live_preview=-1, textinfo="In queue..." if queued else "Waiting...") + + progress = 0 + + if shared.state.job_count > 0: + progress += shared.state.job_no / shared.state.job_count + if shared.state.sampling_steps > 0: + progress += 1 / shared.state.job_count * shared.state.sampling_step / shared.state.sampling_steps + + progress = min(progress, 1) + + elapsed_since_start = time.time() - shared.state.time_start + predicted_duration = elapsed_since_start / progress if progress > 0 else None + eta = predicted_duration - elapsed_since_start if predicted_duration is not None else None + + id_live_preview = req.id_live_preview + shared.state.set_current_image() + if opts.live_previews_enable and shared.state.id_live_preview != req.id_live_preview: + image = shared.state.current_image + if image is not None: + buffered = io.BytesIO() + image.save(buffered, format="png") + live_preview = 'data:image/png;base64,' + base64.b64encode(buffered.getvalue()).decode("ascii") + id_live_preview = shared.state.id_live_preview + else: + live_preview = None + else: + live_preview = None + + return ProgressResponse(active=active, queued=queued, completed=completed, progress=progress, eta=eta, live_preview=live_preview, id_live_preview=id_live_preview, textinfo=shared.state.textinfo) + diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py index 7616fded..76e0e0d5 100644 --- a/modules/sd_samplers.py +++ b/modules/sd_samplers.py @@ -140,7 +140,7 @@ def store_latent(decoded): if opts.live_previews_enable and opts.show_progress_every_n_steps > 0 and shared.state.sampling_step % opts.show_progress_every_n_steps == 0: if not shared.parallel_processing_allowed: - shared.state.current_image = sample_to_image(decoded) + shared.state.assign_current_image(sample_to_image(decoded)) class InterruptedException(BaseException): diff --git a/modules/shared.py b/modules/shared.py index 51df056c..de99aca9 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -152,6 +152,7 @@ def reload_hypernetworks(): hypernetwork.load_hypernetwork(opts.sd_hypernetwork) + class State: skipped = False interrupted = False @@ -165,6 +166,7 @@ class State: current_latent = None current_image = None current_image_sampling_step = 0 + id_live_preview = 0 textinfo = None time_start = None need_restart = False @@ -207,6 +209,7 @@ class State: self.current_latent = None self.current_image = None self.current_image_sampling_step = 0 + self.id_live_preview = 0 self.skipped = False self.interrupted = False self.textinfo = None @@ -220,8 +223,8 @@ class State: devices.torch_gc() - """sets self.current_image from self.current_latent if enough sampling steps have been made after the last call to this""" def set_current_image(self): + """sets self.current_image from self.current_latent if enough sampling steps have been made after the last call to this""" if not parallel_processing_allowed: return @@ -234,12 +237,16 @@ class State: import modules.sd_samplers if opts.show_progress_grid: - self.current_image = modules.sd_samplers.samples_to_image_grid(self.current_latent) + self.assign_current_image(modules.sd_samplers.samples_to_image_grid(self.current_latent)) else: - self.current_image = modules.sd_samplers.sample_to_image(self.current_latent) + self.assign_current_image(modules.sd_samplers.sample_to_image(self.current_latent)) self.current_image_sampling_step = self.sampling_step + def assign_current_image(self, image): + self.current_image = image + self.id_live_preview += 1 + state = State() state.server_start = time.time() @@ -424,8 +431,6 @@ options_templates.update(options_section(('interrogate', "Interrogate Options"), })) options_templates.update(options_section(('ui', "User interface"), { - "show_progressbar": OptionInfo(True, "Show progressbar"), - "show_progress_grid": OptionInfo(True, "Show previews of all images generated in a batch as a grid"), "return_grid": OptionInfo(True, "Show grid in results for web"), "do_not_show_images": OptionInfo(False, "Do not show any images in results for web"), "add_model_hash_to_info": OptionInfo(True, "Add model hash to generation information"), @@ -446,6 +451,7 @@ options_templates.update(options_section(('ui', "User interface"), { options_templates.update(options_section(('ui', "Live previews"), { "live_previews_enable": OptionInfo(True, "Show live previews of the created image"), + "show_progress_grid": OptionInfo(True, "Show previews of all images generated in a batch as a grid"), "show_progress_every_n_steps": OptionInfo(10, "Show new live preview image every N sampling steps. Set to -1 to show after completion of batch.", gr.Slider, {"minimum": -1, "maximum": 32, "step": 1}), "show_progress_type": OptionInfo("Approx NN", "Image creation progress preview mode", gr.Radio, {"choices": ["Full", "Approx NN", "Approx cheap"]}), "live_preview_content": OptionInfo("Prompt", "Live preview subject", gr.Radio, {"choices": ["Combined", "Prompt", "Negative prompt"]}), diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py index 3c1042ad..64abff4d 100644 --- a/modules/textual_inversion/preprocess.py +++ b/modules/textual_inversion/preprocess.py @@ -12,7 +12,7 @@ from modules.shared import opts, cmd_opts from modules.textual_inversion import autocrop -def preprocess(process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2, process_focal_crop=False, process_focal_crop_face_weight=0.9, process_focal_crop_entropy_weight=0.3, process_focal_crop_edges_weight=0.5, process_focal_crop_debug=False): +def preprocess(id_task, process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2, process_focal_crop=False, process_focal_crop_face_weight=0.9, process_focal_crop_entropy_weight=0.3, process_focal_crop_edges_weight=0.5, process_focal_crop_debug=False): try: if process_caption: shared.interrogator.load() diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index 63935878..7e4a6d24 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -345,7 +345,7 @@ def validate_train_inputs(model_name, learn_rate, batch_size, gradient_step, dat assert log_directory, "Log directory is empty" -def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, varsize, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, create_image_every, save_embedding_every, template_filename, save_image_with_stored_embedding, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height): +def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, varsize, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, create_image_every, save_embedding_every, template_filename, save_image_with_stored_embedding, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height): save_embedding_every = save_embedding_every or 0 create_image_every = create_image_every or 0 template_file = textual_inversion_templates.get(template_filename, None) @@ -510,7 +510,6 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_ description = f"Training textual inversion [Epoch {epoch_num}: {epoch_step+1}/{steps_per_epoch}] loss: {loss_step:.7f}" pbar.set_description(description) - shared.state.textinfo = description if embedding_dir is not None and steps_done % save_embedding_every == 0: # Before saving, change name to match current checkpoint. embedding_name_every = f'{embedding_name}-{steps_done}' @@ -560,7 +559,8 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_ shared.sd_model.first_stage_model.to(devices.cpu) if image is not None: - shared.state.current_image = image + shared.state.assign_current_image(image) + last_saved_image, last_text_info = images.save_image(image, images_dir, "", p.seed, p.prompt, shared.opts.samples_format, processed.infotexts[0], p=p, forced_filename=forced_filename, save_to_dirs=False) last_saved_image += f", prompt: {preview_text}" diff --git a/modules/txt2img.py b/modules/txt2img.py index 38b5f591..ca5d4550 100644 --- a/modules/txt2img.py +++ b/modules/txt2img.py @@ -8,7 +8,7 @@ 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, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, *args): +def txt2img(id_task: str, 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, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, *args): p = StableDiffusionProcessingTxt2Img( sd_model=shared.sd_model, outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples, diff --git a/modules/ui.py b/modules/ui.py index 2425c66f..ff33236b 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -356,7 +356,7 @@ def create_toprow(is_img2img): button_deepbooru = gr.Button('Interrogate\nDeepBooru', elem_id="deepbooru") with gr.Column(scale=1): - with gr.Row(): + with gr.Row(elem_id=f"{id_part}_generate_box"): skip = gr.Button('Skip', elem_id=f"{id_part}_skip") interrupt = gr.Button('Interrupt', elem_id=f"{id_part}_interrupt") submit = gr.Button('Generate', elem_id=f"{id_part}_generate", variant='primary') @@ -384,9 +384,7 @@ def create_toprow(is_img2img): def setup_progressbar(*args, **kwargs): - import modules.ui_progress - - modules.ui_progress.setup_progressbar(*args, **kwargs) + pass def apply_setting(key, value): @@ -479,8 +477,8 @@ Requested path was: {f} else: sp.Popen(["xdg-open", path]) - with gr.Column(variant='panel'): - with gr.Group(): + with gr.Column(variant='panel', elem_id=f"{tabname}_results"): + with gr.Group(elem_id=f"{tabname}_gallery_container"): result_gallery = gr.Gallery(label='Output', show_label=False, elem_id=f"{tabname}_gallery").style(grid=4) generation_info = None @@ -595,15 +593,6 @@ def create_ui(): dummy_component = gr.Label(visible=False) txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="bytes", visible=False) - with gr.Row(elem_id='txt2img_progress_row'): - with gr.Column(scale=1): - pass - - with gr.Column(scale=1): - progressbar = gr.HTML(elem_id="txt2img_progressbar") - txt2img_preview = gr.Image(elem_id='txt2img_preview', visible=False) - setup_progressbar(progressbar, txt2img_preview, 'txt2img') - with gr.Row().style(equal_height=False): with gr.Column(variant='panel', elem_id="txt2img_settings"): for category in ordered_ui_categories(): @@ -682,6 +671,7 @@ def create_ui(): fn=wrap_gradio_gpu_call(modules.txt2img.txt2img, extra_outputs=[None, '', '']), _js="submit", inputs=[ + dummy_component, txt2img_prompt, txt2img_negative_prompt, txt2img_prompt_style, @@ -782,16 +772,7 @@ def create_ui(): with gr.Blocks(analytics_enabled=False) as img2img_interface: img2img_prompt, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste,token_counter, token_button = create_toprow(is_img2img=True) - with gr.Row(elem_id='img2img_progress_row'): - img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="bytes", visible=False) - - with gr.Column(scale=1): - pass - - with gr.Column(scale=1): - progressbar = gr.HTML(elem_id="img2img_progressbar") - img2img_preview = gr.Image(elem_id='img2img_preview', visible=False) - setup_progressbar(progressbar, img2img_preview, 'img2img') + img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="bytes", visible=False) with FormRow().style(equal_height=False): with gr.Column(variant='panel', elem_id="img2img_settings"): @@ -958,6 +939,7 @@ def create_ui(): fn=wrap_gradio_gpu_call(modules.img2img.img2img, extra_outputs=[None, '', '']), _js="submit_img2img", inputs=[ + dummy_component, dummy_component, img2img_prompt, img2img_negative_prompt, @@ -1335,15 +1317,11 @@ def create_ui(): script_callbacks.ui_train_tabs_callback(params) - with gr.Column(): - progressbar = gr.HTML(elem_id="ti_progressbar") + with gr.Column(elem_id='ti_gallery_container'): 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, @@ -1384,6 +1362,7 @@ def create_ui(): fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]), _js="start_training_textual_inversion", inputs=[ + dummy_component, process_src, process_dst, process_width, @@ -1411,6 +1390,7 @@ def create_ui(): fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.train_embedding, extra_outputs=[gr.update()]), _js="start_training_textual_inversion", inputs=[ + dummy_component, train_embedding_name, embedding_learn_rate, batch_size, @@ -1443,6 +1423,7 @@ def create_ui(): fn=wrap_gradio_gpu_call(modules.hypernetworks.ui.train_hypernetwork, extra_outputs=[gr.update()]), _js="start_training_textual_inversion", inputs=[ + dummy_component, train_hypernetwork_name, hypernetwork_learn_rate, batch_size, diff --git a/modules/ui_progress.py b/modules/ui_progress.py deleted file mode 100644 index 7cd312e4..00000000 --- a/modules/ui_progress.py +++ /dev/null @@ -1,101 +0,0 @@ -import time - -import gradio as gr - -from modules.shared import opts - -import modules.shared as shared - - -def calc_time_left(progress, threshold, label, force_display, show_eta): - if progress == 0: - return "" - else: - time_since_start = time.time() - shared.state.time_start - eta = (time_since_start/progress) - eta_relative = eta-time_since_start - if (eta_relative > threshold and show_eta) or force_display: - if eta_relative > 3600: - return label + time.strftime('%H:%M:%S', time.gmtime(eta_relative)) - elif eta_relative > 60: - return label + time.strftime('%M:%S', time.gmtime(eta_relative)) - else: - return label + time.strftime('%Ss', time.gmtime(eta_relative)) - else: - return "" - - -def check_progress_call(id_part): - if shared.state.job_count == 0: - return "", gr.update(visible=False), gr.update(visible=False), gr.update(visible=False) - - progress = 0 - - if shared.state.job_count > 0: - progress += shared.state.job_no / shared.state.job_count - if shared.state.sampling_steps > 0: - progress += 1 / shared.state.job_count * shared.state.sampling_step / shared.state.sampling_steps - - # Show progress percentage and time left at the same moment, and base it also on steps done - show_eta = progress >= 0.01 or shared.state.sampling_step >= 10 - - time_left = calc_time_left(progress, 1, " ETA: ", shared.state.time_left_force_display, show_eta) - if time_left != "": - shared.state.time_left_force_display = True - - progress = min(progress, 1) - - progressbar = "" - if opts.show_progressbar: - progressbar = f"""
{" " * 2 + str(int(progress*100))+"%" + time_left if show_eta else ""}
""" - - image = gr.update(visible=False) - preview_visibility = gr.update(visible=False) - - if opts.live_previews_enable: - shared.state.set_current_image() - image = shared.state.current_image - - if image is None: - image = gr.update(value=None) - else: - preview_visibility = gr.update(visible=True) - - if shared.state.textinfo is not None: - textinfo_result = gr.HTML.update(value=shared.state.textinfo, visible=True) - else: - textinfo_result = gr.update(visible=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 - shared.state.time_start = time.time() - shared.state.time_left_force_display = False - - return check_progress_call(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, textinfo], - ) - - check_progress_initial = gr.Button('Check progress (first)', elem_id=f"{id_part}_check_progress_initial", visible=False) - check_progress_initial.click( - fn=lambda: check_progress_call_initial(id_part), - show_progress=False, - inputs=[], - outputs=[progressbar, preview, preview, textinfo], - ) diff --git a/style.css b/style.css index 2d484e06..786b71d1 100644 --- a/style.css +++ b/style.css @@ -305,26 +305,42 @@ input[type="range"]{ } .progressDiv{ - width: 100%; - height: 20px; - background: #b4c0cc; - border-radius: 8px; + position: absolute; + height: 20px; + top: -20px; + background: #b4c0cc; + border-radius: 8px !important; } .dark .progressDiv{ - background: #424c5b; + background: #424c5b; } .progressDiv .progress{ - width: 0%; - height: 20px; - background: #0060df; - color: white; - font-weight: bold; - line-height: 20px; - padding: 0 8px 0 0; - text-align: right; - border-radius: 8px; + width: 0%; + height: 20px; + background: #0060df; + color: white; + font-weight: bold; + line-height: 20px; + padding: 0 8px 0 0; + text-align: right; + border-radius: 8px; + overflow: visible; + white-space: nowrap; +} + +.livePreview{ + position: absolute; + z-index: 300; + background-color: white; + margin: -4px; +} + +.livePreview img{ + object-fit: contain; + width: 100%; + height: 100%; } #lightboxModal{ @@ -450,23 +466,25 @@ input[type="range"]{ display:none } -#txt2img_interrupt, #img2img_interrupt{ - position: absolute; - width: 50%; - height: 72px; - background: #b4c0cc; - border-radius: 0px; - display: none; +#txt2img_generate_box, #img2img_generate_box{ + position: relative; +} + +#txt2img_interrupt, #img2img_interrupt, #txt2img_skip, #img2img_skip{ + position: absolute; + width: 50%; + height: 100%; + background: #b4c0cc; + display: none; } +#txt2img_interrupt, #img2img_interrupt{ + right: 0; + border-radius: 0 0.5rem 0.5rem 0; +} #txt2img_skip, #img2img_skip{ - position: absolute; - width: 50%; - right: 0px; - height: 72px; - background: #b4c0cc; - border-radius: 0px; - display: none; + left: 0; + border-radius: 0.5rem 0 0 0.5rem; } .red { diff --git a/webui.py b/webui.py index 1fff80da..4624fe18 100644 --- a/webui.py +++ b/webui.py @@ -34,6 +34,7 @@ import modules.sd_vae import modules.txt2img import modules.script_callbacks import modules.textual_inversion.textual_inversion +import modules.progress import modules.ui from modules import modelloader @@ -181,6 +182,8 @@ def webui(): app.add_middleware(GZipMiddleware, minimum_size=1000) + modules.progress.setup_progress_api(app) + if launch_api: create_api(app) -- cgit v1.2.3 From 4688bfff55dd6607e6608524fb219f97dc6fe8bb Mon Sep 17 00:00:00 2001 From: dan Date: Tue, 17 Jan 2023 17:16:43 +0800 Subject: Add auto-sized cropping UI --- modules/textual_inversion/preprocess.py | 38 ++++++++++++++++++++++++++++++--- modules/ui.py | 28 +++++++++++++++++++++++- 2 files changed, 62 insertions(+), 4 deletions(-) (limited to 'modules/textual_inversion/preprocess.py') diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py index 64abff4d..86c1cd33 100644 --- a/modules/textual_inversion/preprocess.py +++ b/modules/textual_inversion/preprocess.py @@ -12,7 +12,7 @@ from modules.shared import opts, cmd_opts from modules.textual_inversion import autocrop -def preprocess(id_task, process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2, process_focal_crop=False, process_focal_crop_face_weight=0.9, process_focal_crop_entropy_weight=0.3, process_focal_crop_edges_weight=0.5, process_focal_crop_debug=False): +def preprocess(id_task, process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2, process_focal_crop=False, process_focal_crop_face_weight=0.9, process_focal_crop_entropy_weight=0.3, process_focal_crop_edges_weight=0.5, process_focal_crop_debug=False, process_multicrop=None, process_multicrop_mindim=None, process_multicrop_maxdim=None, process_multicrop_minarea=None, process_multicrop_maxarea=None, process_multicrop_objective=None, process_multicrop_threshold=None): try: if process_caption: shared.interrogator.load() @@ -20,7 +20,7 @@ def preprocess(id_task, process_src, process_dst, process_width, process_height, if process_caption_deepbooru: deepbooru.model.start() - preprocess_work(process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru, split_threshold, overlap_ratio, process_focal_crop, process_focal_crop_face_weight, process_focal_crop_entropy_weight, process_focal_crop_edges_weight, process_focal_crop_debug) + preprocess_work(process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru, split_threshold, overlap_ratio, process_focal_crop, process_focal_crop_face_weight, process_focal_crop_entropy_weight, process_focal_crop_edges_weight, process_focal_crop_debug, process_multicrop, process_multicrop_mindim, process_multicrop_maxdim, process_multicrop_minarea, process_multicrop_maxarea, process_multicrop_objective, process_multicrop_threshold) finally: @@ -109,8 +109,32 @@ def split_pic(image, inverse_xy, width, height, overlap_ratio): splitted = image.crop((0, y, to_w, y + to_h)) yield splitted +# not using torchvision.transforms.CenterCrop because it doesn't allow float regions +def center_crop(image: Image, w: int, h: int): + iw, ih = image.size + if ih / h < iw / w: + sw = w * ih / h + box = (iw - sw) / 2, 0, iw - (iw - sw) / 2, ih + else: + sh = h * iw / w + box = 0, (ih - sh) / 2, iw, ih - (ih - sh) / 2 + return image.resize((w, h), Image.Resampling.LANCZOS, box) + -def preprocess_work(process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2, process_focal_crop=False, process_focal_crop_face_weight=0.9, process_focal_crop_entropy_weight=0.3, process_focal_crop_edges_weight=0.5, process_focal_crop_debug=False): +def multicrop_pic(image: Image, mindim, maxdim, minarea, maxarea, objective, threshold): + iw, ih = image.size + err = lambda w, h: 1-(lambda x: x if x < 1 else 1/x)(iw/ih/(w/h)) + try: + w, h = max(((w, h) for w in range(mindim, maxdim+1, 64) for h in range(mindim, maxdim+1, 64) + if minarea <= w * h <= maxarea and err(w, h) <= threshold), + key= lambda wh: ((objective=='Maximize area')*wh[0]*wh[1], -err(*wh)) + ) + except ValueError: + return + return center_crop(image, w, h) + + +def preprocess_work(process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2, process_focal_crop=False, process_focal_crop_face_weight=0.9, process_focal_crop_entropy_weight=0.3, process_focal_crop_edges_weight=0.5, process_focal_crop_debug=False, process_multicrop=None, process_multicrop_mindim=None, process_multicrop_maxdim=None, process_multicrop_minarea=None, process_multicrop_maxarea=None, process_multicrop_objective=None, process_multicrop_threshold=None): width = process_width height = process_height src = os.path.abspath(process_src) @@ -194,6 +218,14 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre save_pic(focal, index, params, existing_caption=existing_caption) process_default_resize = False + if process_multicrop: + cropped = multicrop_pic(img, process_multicrop_mindim, process_multicrop_maxdim, process_multicrop_minarea, process_multicrop_maxarea, process_multicrop_objective, process_multicrop_threshold) + if cropped is not None: + save_pic(cropped, index, params, existing_caption=existing_caption) + else: + print(f"skipped {img.width}x{img.height} image {filename} (can't find suitable size within error threshold)") + process_default_resize = False + if process_default_resize: img = images.resize_image(1, img, width, height) save_pic(img, index, params, existing_caption=existing_caption) diff --git a/modules/ui.py b/modules/ui.py index 20b66165..bbce9acd 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1226,6 +1226,7 @@ def create_ui(): process_flip = gr.Checkbox(label='Create flipped copies', elem_id="train_process_flip") process_split = gr.Checkbox(label='Split oversized images', elem_id="train_process_split") process_focal_crop = gr.Checkbox(label='Auto focal point crop', elem_id="train_process_focal_crop") + process_multicrop = gr.Checkbox(label='Auto-sized crop', elem_id="train_process_multicrop") process_caption = gr.Checkbox(label='Use BLIP for caption', elem_id="train_process_caption") process_caption_deepbooru = gr.Checkbox(label='Use deepbooru for caption', visible=True, elem_id="train_process_caption_deepbooru") @@ -1238,7 +1239,19 @@ def create_ui(): process_focal_crop_entropy_weight = gr.Slider(label='Focal point entropy weight', value=0.15, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_entropy_weight") process_focal_crop_edges_weight = gr.Slider(label='Focal point edges weight', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_edges_weight") process_focal_crop_debug = gr.Checkbox(label='Create debug image', elem_id="train_process_focal_crop_debug") - + + with gr.Column(visible=False) as process_multicrop_col: + gr.Markdown('Each image is center-cropped with an automatically chosen width and height.') + with gr.Row(): + process_multicrop_mindim = gr.Slider(minimum=64, maximum=2048, step=8, label="Dimension lower bound", value=384, elem_id="train_process_multicrop_mindim") + process_multicrop_maxdim = gr.Slider(minimum=64, maximum=2048, step=8, label="Dimension upper bound", value=768, elem_id="train_process_multicrop_maxdim") + with gr.Row(): + process_multicrop_minarea = gr.Slider(minimum=64*64, maximum=2048*2048, step=1, label="Area lower bound", value=64*64, elem_id="train_process_multicrop_minarea") + process_multicrop_maxarea = gr.Slider(minimum=64*64, maximum=2048*2048, step=1, label="Area upper bound", value=640*640, elem_id="train_process_multicrop_maxarea") + with gr.Row(): + process_multicrop_objective = gr.Radio(["Maximize area", "Minimize error"], value="Maximize area", label="Resizing objective", elem_id="train_process_multicrop_objective") + process_multicrop_threshold = gr.Slider(minimum=0, maximum=1, step=0.01, label="Error threshold", value=0.1, elem_id="train_process_multicrop_threshold") + with gr.Row(): with gr.Column(scale=3): gr.HTML(value="") @@ -1260,6 +1273,12 @@ def create_ui(): outputs=[process_focal_crop_row], ) + process_multicrop.change( + fn=lambda show: gr_show(show), + inputs=[process_multicrop], + outputs=[process_multicrop_col], + ) + def get_textual_inversion_template_names(): return sorted([x for x in textual_inversion.textual_inversion_templates]) @@ -1379,6 +1398,13 @@ def create_ui(): process_focal_crop_entropy_weight, process_focal_crop_edges_weight, process_focal_crop_debug, + process_multicrop, + process_multicrop_mindim, + process_multicrop_maxdim, + process_multicrop_minarea, + process_multicrop_maxarea, + process_multicrop_objective, + process_multicrop_threshold, ], outputs=[ ti_output, -- cgit v1.2.3 From 18a09c7e0032e2e655269e8e2b4f1ca6ed0cc7d3 Mon Sep 17 00:00:00 2001 From: dan Date: Thu, 19 Jan 2023 17:36:23 +0800 Subject: Simplification and bugfix --- modules/textual_inversion/preprocess.py | 12 +++++------- 1 file changed, 5 insertions(+), 7 deletions(-) (limited to 'modules/textual_inversion/preprocess.py') diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py index 86c1cd33..454dcc36 100644 --- a/modules/textual_inversion/preprocess.py +++ b/modules/textual_inversion/preprocess.py @@ -124,13 +124,11 @@ def center_crop(image: Image, w: int, h: int): def multicrop_pic(image: Image, mindim, maxdim, minarea, maxarea, objective, threshold): iw, ih = image.size err = lambda w, h: 1-(lambda x: x if x < 1 else 1/x)(iw/ih/(w/h)) - try: - w, h = max(((w, h) for w in range(mindim, maxdim+1, 64) for h in range(mindim, maxdim+1, 64) - if minarea <= w * h <= maxarea and err(w, h) <= threshold), - key= lambda wh: ((objective=='Maximize area')*wh[0]*wh[1], -err(*wh)) - ) - except ValueError: - return + w, h = max(((w, h) for w in range(mindim, maxdim+1, 64) for h in range(mindim, maxdim+1, 64) + if minarea <= w * h <= maxarea and err(w, h) <= threshold), + key= lambda wh: (wh[0]*wh[1], -err(*wh))[::1 if objective=='Maximize area' else -1], + default=None + ) return center_crop(image, w, h) -- cgit v1.2.3 From 2985b317d719f0f0580d2ff93f3008ccabb9c251 Mon Sep 17 00:00:00 2001 From: dan Date: Thu, 19 Jan 2023 17:39:30 +0800 Subject: Fix of fix --- modules/textual_inversion/preprocess.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) (limited to 'modules/textual_inversion/preprocess.py') diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py index 454dcc36..c0ac11d3 100644 --- a/modules/textual_inversion/preprocess.py +++ b/modules/textual_inversion/preprocess.py @@ -124,12 +124,12 @@ def center_crop(image: Image, w: int, h: int): def multicrop_pic(image: Image, mindim, maxdim, minarea, maxarea, objective, threshold): iw, ih = image.size err = lambda w, h: 1-(lambda x: x if x < 1 else 1/x)(iw/ih/(w/h)) - w, h = max(((w, h) for w in range(mindim, maxdim+1, 64) for h in range(mindim, maxdim+1, 64) + wh = max(((w, h) for w in range(mindim, maxdim+1, 64) for h in range(mindim, maxdim+1, 64) if minarea <= w * h <= maxarea and err(w, h) <= threshold), key= lambda wh: (wh[0]*wh[1], -err(*wh))[::1 if objective=='Maximize area' else -1], default=None ) - return center_crop(image, w, h) + return wh and center_crop(image, *wh) def preprocess_work(process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2, process_focal_crop=False, process_focal_crop_face_weight=0.9, process_focal_crop_entropy_weight=0.3, process_focal_crop_edges_weight=0.5, process_focal_crop_debug=False, process_multicrop=None, process_multicrop_mindim=None, process_multicrop_maxdim=None, process_multicrop_minarea=None, process_multicrop_maxarea=None, process_multicrop_objective=None, process_multicrop_threshold=None): -- cgit v1.2.3 From 5eee2ac39863f9e44591b50d0710dd2615416a13 Mon Sep 17 00:00:00 2001 From: Max Audron Date: Wed, 25 Jan 2023 17:15:42 +0100 Subject: add data-dir flag and set all user data directories based on it --- modules/extensions.py | 2 +- modules/generation_parameters_copypaste.py | 4 ++-- modules/gfpgan_model.py | 5 ++--- modules/hashes.py | 4 +++- modules/interrogate.py | 2 +- modules/paths.py | 10 +++++++++- modules/processing.py | 3 ++- modules/sd_models.py | 6 +++--- modules/sd_vae.py | 5 ++--- modules/shared.py | 11 ++++++----- modules/textual_inversion/preprocess.py | 5 ++--- modules/ui.py | 6 +++--- modules/ui_extensions.py | 2 +- modules/upscaler.py | 5 ++--- 14 files changed, 39 insertions(+), 31 deletions(-) (limited to 'modules/textual_inversion/preprocess.py') diff --git a/modules/extensions.py b/modules/extensions.py index b522125c..92ee8144 100644 --- a/modules/extensions.py +++ b/modules/extensions.py @@ -7,7 +7,7 @@ import git from modules import paths, shared extensions = [] -extensions_dir = os.path.join(paths.script_path, "extensions") +extensions_dir = os.path.join(paths.data_path, "extensions") extensions_builtin_dir = os.path.join(paths.script_path, "extensions-builtin") diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 46e12dc6..35f72808 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -6,7 +6,7 @@ import re from pathlib import Path import gradio as gr -from modules.shared import script_path +from modules.paths import data_path, script_path from modules import shared, ui_tempdir, script_callbacks import tempfile from PIL import Image @@ -289,7 +289,7 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model def connect_paste(button, paste_fields, input_comp, jsfunc=None): def paste_func(prompt): if not prompt and not shared.cmd_opts.hide_ui_dir_config: - filename = os.path.join(script_path, "params.txt") + filename = os.path.join(data_path, "params.txt") if os.path.exists(filename): with open(filename, "r", encoding="utf8") as file: prompt = file.read() diff --git a/modules/gfpgan_model.py b/modules/gfpgan_model.py index 1e2dbc32..fbe6215a 100644 --- a/modules/gfpgan_model.py +++ b/modules/gfpgan_model.py @@ -6,12 +6,11 @@ import facexlib import gfpgan import modules.face_restoration -from modules import shared, devices, modelloader -from modules.paths import models_path +from modules import paths, shared, devices, modelloader model_dir = "GFPGAN" user_path = None -model_path = os.path.join(models_path, model_dir) +model_path = os.path.join(paths.models_path, model_dir) model_url = "https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth" have_gfpgan = False loaded_gfpgan_model = None diff --git a/modules/hashes.py b/modules/hashes.py index b85a7580..819362a3 100644 --- a/modules/hashes.py +++ b/modules/hashes.py @@ -4,8 +4,10 @@ import os.path import filelock +from modules.paths import data_path -cache_filename = "cache.json" + +cache_filename = os.path.join(data_path, "cache.json") cache_data = None diff --git a/modules/interrogate.py b/modules/interrogate.py index c72ff694..cbb80683 100644 --- a/modules/interrogate.py +++ b/modules/interrogate.py @@ -12,7 +12,7 @@ from torchvision import transforms from torchvision.transforms.functional import InterpolationMode import modules.shared as shared -from modules import devices, paths, lowvram, modelloader, errors +from modules import devices, paths, shared, lowvram, modelloader, errors blip_image_eval_size = 384 clip_model_name = 'ViT-L/14' diff --git a/modules/paths.py b/modules/paths.py index 20b3e4d8..08e6f9b9 100644 --- a/modules/paths.py +++ b/modules/paths.py @@ -4,7 +4,15 @@ import sys import modules.safe script_path = os.path.dirname(os.path.dirname(os.path.realpath(__file__))) -models_path = os.path.join(script_path, "models") + +# Parse the --data-dir flag first so we can use it as a base for our other argument default values +parser = argparse.ArgumentParser() +parser.add_argument("--data-dir", type=str, default=os.path.dirname(os.path.dirname(os.path.realpath(__file__))), help="base path where all user data is stored",) +cmd_opts_pre = parser.parse_known_args()[0] +data_path = cmd_opts_pre.data_dir +models_path = os.path.join(data_path, "models") + +# data_path = cmd_opts_pre.data sys.path.insert(0, script_path) # search for directory of stable diffusion in following places diff --git a/modules/processing.py b/modules/processing.py index 262806a1..5072fc40 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -17,6 +17,7 @@ from modules import devices, prompt_parser, masking, sd_samplers, lowvram, gener from modules.sd_hijack import model_hijack from modules.shared import opts, cmd_opts, state import modules.shared as shared +import modules.paths as paths import modules.face_restoration import modules.images as images import modules.styles @@ -584,7 +585,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: if not p.disable_extra_networks: extra_networks.activate(p, extra_network_data) - with open(os.path.join(shared.script_path, "params.txt"), "w", encoding="utf8") as file: + with open(os.path.join(paths.data_path, "params.txt"), "w", encoding="utf8") as file: processed = Processed(p, [], p.seed, "") file.write(processed.infotext(p, 0)) diff --git a/modules/sd_models.py b/modules/sd_models.py index 37dad18d..b2d48a51 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -12,13 +12,13 @@ import ldm.modules.midas as midas from ldm.util import instantiate_from_config -from modules import shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes, sd_models_config +from modules import paths, shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes, sd_models_config from modules.paths import models_path from modules.sd_hijack_inpainting import do_inpainting_hijack from modules.timer import Timer model_dir = "Stable-diffusion" -model_path = os.path.abspath(os.path.join(models_path, model_dir)) +model_path = os.path.abspath(os.path.join(paths.models_path, model_dir)) checkpoints_list = {} checkpoint_alisases = {} @@ -307,7 +307,7 @@ def enable_midas_autodownload(): location automatically. """ - midas_path = os.path.join(models_path, 'midas') + midas_path = os.path.join(paths.models_path, 'midas') # stable-diffusion-stability-ai hard-codes the midas model path to # a location that differs from where other scripts using this model look. diff --git a/modules/sd_vae.py b/modules/sd_vae.py index 4ce238b8..9b00f76e 100644 --- a/modules/sd_vae.py +++ b/modules/sd_vae.py @@ -3,13 +3,12 @@ import safetensors.torch import os import collections from collections import namedtuple -from modules import shared, devices, script_callbacks, sd_models -from modules.paths import models_path +from modules import paths, shared, devices, script_callbacks, sd_models import glob from copy import deepcopy -vae_path = os.path.abspath(os.path.join(models_path, "VAE")) +vae_path = os.path.abspath(os.path.join(paths.models_path, "VAE")) vae_ignore_keys = {"model_ema.decay", "model_ema.num_updates"} vae_dict = {} diff --git a/modules/shared.py b/modules/shared.py index 14be993d..474fcc42 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -14,7 +14,7 @@ import modules.memmon import modules.styles import modules.devices as devices from modules import localization, extensions, script_loading, errors, ui_components, shared_items -from modules.paths import models_path, script_path +from modules.paths import models_path, script_path, data_path demo = None @@ -25,6 +25,7 @@ sd_model_file = os.path.join(script_path, 'model.ckpt') default_sd_model_file = sd_model_file parser = argparse.ArgumentParser() +parser.add_argument("--data-dir", type=str, default=os.path.dirname(os.path.dirname(os.path.realpath(__file__))), help="base path where all user data is stored",) parser.add_argument("--config", type=str, default=sd_default_config, help="path to config which constructs model",) parser.add_argument("--ckpt", type=str, default=sd_model_file, help="path to checkpoint of stable diffusion model; if specified, this checkpoint will be added to the list of checkpoints and loaded",) parser.add_argument("--ckpt-dir", type=str, default=None, help="Path to directory with stable diffusion checkpoints") @@ -35,7 +36,7 @@ parser.add_argument("--no-half", action='store_true', help="do not switch the mo parser.add_argument("--no-half-vae", action='store_true', help="do not switch the VAE model to 16-bit floats") 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("--embeddings-dir", type=str, default=os.path.join(data_path, 'embeddings'), help="embeddings directory for textual inversion (default: embeddings)") parser.add_argument("--textual-inversion-templates-dir", type=str, default=os.path.join(script_path, 'textual_inversion_templates'), help="directory with textual inversion templates") 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") @@ -74,16 +75,16 @@ parser.add_argument("--use-cpu", nargs='+', help="use CPU as torch device for sp parser.add_argument("--listen", action='store_true', help="launch gradio with 0.0.0.0 as server name, allowing to respond to network requests") parser.add_argument("--port", type=int, help="launch gradio with given server port, you need root/admin rights for ports < 1024, defaults to 7860 if available", default=None) parser.add_argument("--show-negative-prompt", action='store_true', help="does not do anything", default=False) -parser.add_argument("--ui-config-file", type=str, help="filename to use for ui configuration", default=os.path.join(script_path, 'ui-config.json')) +parser.add_argument("--ui-config-file", type=str, help="filename to use for ui configuration", default=os.path.join(data_path, 'ui-config.json')) parser.add_argument("--hide-ui-dir-config", action='store_true', help="hide directory configuration from webui", default=False) parser.add_argument("--freeze-settings", action='store_true', help="disable editing settings", default=False) -parser.add_argument("--ui-settings-file", type=str, help="filename to use for ui settings", default=os.path.join(script_path, 'config.json')) +parser.add_argument("--ui-settings-file", type=str, help="filename to use for ui settings", default=os.path.join(data_path, 'config.json')) parser.add_argument("--gradio-debug", action='store_true', help="launch gradio with --debug option") parser.add_argument("--gradio-auth", type=str, help='set gradio authentication like "username:password"; or comma-delimit multiple like "u1:p1,u2:p2,u3:p3"', default=None) parser.add_argument("--gradio-img2img-tool", type=str, help='does not do anything') parser.add_argument("--gradio-inpaint-tool", type=str, help="does not do anything") parser.add_argument("--opt-channelslast", action='store_true', help="change memory type for stable diffusion to channels last") -parser.add_argument("--styles-file", type=str, help="filename to use for styles", default=os.path.join(script_path, 'styles.csv')) +parser.add_argument("--styles-file", type=str, help="filename to use for styles", default=os.path.join(data_path, 'styles.csv')) parser.add_argument("--autolaunch", action='store_true', help="open the webui URL in the system's default browser upon launch", default=False) parser.add_argument("--theme", type=str, help="launches the UI with light or dark theme", default=None) parser.add_argument("--use-textbox-seed", action='store_true', help="use textbox for seeds in UI (no up/down, but possible to input long seeds)", default=False) diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py index c0ac11d3..2239cb84 100644 --- a/modules/textual_inversion/preprocess.py +++ b/modules/textual_inversion/preprocess.py @@ -6,8 +6,7 @@ import sys import tqdm import time -from modules import shared, images, deepbooru -from modules.paths import models_path +from modules import paths, shared, images, deepbooru from modules.shared import opts, cmd_opts from modules.textual_inversion import autocrop @@ -199,7 +198,7 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre dnn_model_path = None try: - dnn_model_path = autocrop.download_and_cache_models(os.path.join(models_path, "opencv")) + dnn_model_path = autocrop.download_and_cache_models(os.path.join(paths.models_path, "opencv")) except Exception as e: print("Unable to load face detection model for auto crop selection. Falling back to lower quality haar method.", e) diff --git a/modules/ui.py b/modules/ui.py index 85ae62c7..0117df3e 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -21,7 +21,7 @@ from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_grad from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks, postprocessing, ui_components, ui_common, ui_postprocessing from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML -from modules.paths import script_path +from modules.paths import script_path, data_path from modules.shared import opts, cmd_opts, restricted_opts @@ -1497,8 +1497,8 @@ def create_ui(): 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: + if os.path.exists(os.path.join(data_path, "user.css")): + with open(os.path.join(data_path, "user.css"), "r", encoding="utf8") as file: css += file.read() + "\n" if not cmd_opts.no_progressbar_hiding: diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py index 742e745e..66a41865 100644 --- a/modules/ui_extensions.py +++ b/modules/ui_extensions.py @@ -132,7 +132,7 @@ def install_extension_from_url(dirname, url): normalized_url = normalize_git_url(url) assert len([x for x in extensions.extensions if normalize_git_url(x.remote) == normalized_url]) == 0, 'Extension with this URL is already installed' - tmpdir = os.path.join(paths.script_path, "tmp", dirname) + tmpdir = os.path.join(paths.data_path, "tmp", dirname) try: shutil.rmtree(tmpdir, True) diff --git a/modules/upscaler.py b/modules/upscaler.py index a5bf5acb..e2eaa730 100644 --- a/modules/upscaler.py +++ b/modules/upscaler.py @@ -11,7 +11,6 @@ from modules import modelloader, shared LANCZOS = (Image.Resampling.LANCZOS if hasattr(Image, 'Resampling') else Image.LANCZOS) NEAREST = (Image.Resampling.NEAREST if hasattr(Image, 'Resampling') else Image.NEAREST) -from modules.paths import models_path class Upscaler: @@ -39,7 +38,7 @@ class Upscaler: self.mod_scale = None if self.model_path is None and self.name: - self.model_path = os.path.join(models_path, self.name) + self.model_path = os.path.join(shared.models_path, self.name) if self.model_path and create_dirs: os.makedirs(self.model_path, exist_ok=True) @@ -143,4 +142,4 @@ class UpscalerNearest(Upscaler): def __init__(self, dirname=None): super().__init__(False) self.name = "Nearest" - self.scalers = [UpscalerData("Nearest", None, self)] \ No newline at end of file + self.scalers = [UpscalerData("Nearest", None, self)] -- cgit v1.2.3