From bb57f30c2de46cfca5419ad01738a41705f96cc3 Mon Sep 17 00:00:00 2001 From: MalumaDev Date: Fri, 14 Oct 2022 10:56:41 +0200 Subject: init --- modules/shared.py | 5 +++++ 1 file changed, 5 insertions(+) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index 5901e605..cf13a10d 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -30,6 +30,8 @@ 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(script_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("--allow-code", action='store_true', help="allow custom script execution from webui") parser.add_argument("--medvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a little speed for low VRM usage") @@ -90,6 +92,9 @@ os.makedirs(cmd_opts.hypernetwork_dir, exist_ok=True) hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir) loaded_hypernetwork = None +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")} + def reload_hypernetworks(): global hypernetworks -- cgit v1.2.3 From 37d7ffb415cd8c69b3c0bb5f61844dde0b169f78 Mon Sep 17 00:00:00 2001 From: MalumaDev Date: Sat, 15 Oct 2022 15:59:37 +0200 Subject: fix to tokens lenght, addend embs generator, add new features to edit the embedding before the generation using text --- modules/aesthetic_clip.py | 78 ++++++++++++++++++++++++ modules/processing.py | 148 +++++++++++++++++++++++++++++++--------------- modules/sd_hijack.py | 111 ++++++++++++++++++++++------------ modules/shared.py | 4 ++ modules/txt2img.py | 10 +++- modules/ui.py | 47 ++++++++++++--- 6 files changed, 302 insertions(+), 96 deletions(-) create mode 100644 modules/aesthetic_clip.py (limited to 'modules/shared.py') diff --git a/modules/aesthetic_clip.py b/modules/aesthetic_clip.py new file mode 100644 index 00000000..f15cfd47 --- /dev/null +++ b/modules/aesthetic_clip.py @@ -0,0 +1,78 @@ +import itertools +import os +from pathlib import Path +import html +import gc + +import gradio as gr +import torch +from PIL import Image +from modules import shared +from modules.shared import device, aesthetic_embeddings +from transformers import CLIPModel, CLIPProcessor + +from tqdm.auto import tqdm + + +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')) + + +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 generate_imgs_embd(name, folder, batch_size): + # clipModel = CLIPModel.from_pretrained( + # shared.sd_model.cond_stage_model.clipModel.name_or_path + # ) + model = CLIPModel.from_pretrained(shared.sd_model.cond_stage_model.clipModel.name_or_path).to(device) + processor = CLIPProcessor.from_pretrained(shared.sd_model.cond_stage_model.clipModel.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 = model.cpu() + del model + del processor + del embs + gc.collect() + torch.cuda.empty_cache() + res = f""" + Done generating embedding for {name}! + Hypernetwork saved to {html.escape(path)} + """ + shared.update_aesthetic_embeddings() + return gr.Dropdown(sorted(aesthetic_embeddings.keys()), label="Imgs embedding", + value=sorted(aesthetic_embeddings.keys())[0] if len( + aesthetic_embeddings) > 0 else None), res, "" diff --git a/modules/processing.py b/modules/processing.py index 9a033759..ab68d63a 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -20,7 +20,6 @@ import modules.images as images import modules.styles import logging - # some of those options should not be changed at all because they would break the model, so I removed them from options. opt_C = 4 opt_f = 8 @@ -52,8 +51,13 @@ def get_correct_sampler(p): elif isinstance(p, modules.processing.StableDiffusionProcessingImg2Img): return sd_samplers.samplers_for_img2img + class StableDiffusionProcessing: - def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt="", styles=None, seed=-1, subseed=-1, subseed_strength=0, seed_resize_from_h=-1, seed_resize_from_w=-1, seed_enable_extras=True, sampler_index=0, batch_size=1, n_iter=1, steps=50, cfg_scale=7.0, width=512, height=512, restore_faces=False, tiling=False, do_not_save_samples=False, do_not_save_grid=False, extra_generation_params=None, overlay_images=None, negative_prompt=None, eta=None): + def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt="", styles=None, seed=-1, + subseed=-1, subseed_strength=0, seed_resize_from_h=-1, seed_resize_from_w=-1, seed_enable_extras=True, + sampler_index=0, batch_size=1, n_iter=1, steps=50, cfg_scale=7.0, width=512, height=512, + restore_faces=False, tiling=False, do_not_save_samples=False, do_not_save_grid=False, + extra_generation_params=None, overlay_images=None, negative_prompt=None, eta=None): self.sd_model = sd_model self.outpath_samples: str = outpath_samples self.outpath_grids: str = outpath_grids @@ -104,7 +108,8 @@ class StableDiffusionProcessing: class Processed: - def __init__(self, p: StableDiffusionProcessing, images_list, seed=-1, info="", subseed=None, all_prompts=None, all_seeds=None, all_subseeds=None, index_of_first_image=0, infotexts=None): + def __init__(self, p: StableDiffusionProcessing, images_list, seed=-1, info="", subseed=None, all_prompts=None, + all_seeds=None, all_subseeds=None, index_of_first_image=0, infotexts=None): self.images = images_list self.prompt = p.prompt self.negative_prompt = p.negative_prompt @@ -141,7 +146,8 @@ class Processed: self.prompt = self.prompt if type(self.prompt) != list else self.prompt[0] self.negative_prompt = self.negative_prompt if type(self.negative_prompt) != list else self.negative_prompt[0] self.seed = int(self.seed if type(self.seed) != list else self.seed[0]) - self.subseed = int(self.subseed if type(self.subseed) != list else self.subseed[0]) if self.subseed is not None else -1 + self.subseed = int( + self.subseed if type(self.subseed) != list else self.subseed[0]) if self.subseed is not None else -1 self.all_prompts = all_prompts or [self.prompt] self.all_seeds = all_seeds or [self.seed] @@ -181,39 +187,43 @@ class Processed: return json.dumps(obj) - def infotext(self, p: StableDiffusionProcessing, index): - return create_infotext(p, self.all_prompts, self.all_seeds, self.all_subseeds, comments=[], position_in_batch=index % self.batch_size, iteration=index // self.batch_size) + def infotext(self, p: StableDiffusionProcessing, index): + return create_infotext(p, self.all_prompts, self.all_seeds, self.all_subseeds, comments=[], + position_in_batch=index % self.batch_size, iteration=index // self.batch_size) # from https://discuss.pytorch.org/t/help-regarding-slerp-function-for-generative-model-sampling/32475/3 def slerp(val, low, high): - low_norm = low/torch.norm(low, dim=1, keepdim=True) - high_norm = high/torch.norm(high, dim=1, keepdim=True) - dot = (low_norm*high_norm).sum(1) + low_norm = low / torch.norm(low, dim=1, keepdim=True) + high_norm = high / torch.norm(high, dim=1, keepdim=True) + dot = (low_norm * high_norm).sum(1) if dot.mean() > 0.9995: return low * val + high * (1 - val) omega = torch.acos(dot) so = torch.sin(omega) - res = (torch.sin((1.0-val)*omega)/so).unsqueeze(1)*low + (torch.sin(val*omega)/so).unsqueeze(1) * high + res = (torch.sin((1.0 - val) * omega) / so).unsqueeze(1) * low + (torch.sin(val * omega) / so).unsqueeze(1) * high return res -def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=0.0, seed_resize_from_h=0, seed_resize_from_w=0, p=None): +def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=0.0, seed_resize_from_h=0, seed_resize_from_w=0, + p=None): xs = [] # if we have multiple seeds, this means we are working with batch size>1; this then # enables the generation of additional tensors with noise that the sampler will use during its processing. # Using those pre-generated tensors instead of simple torch.randn allows a batch with seeds [100, 101] to # produce the same images as with two batches [100], [101]. - if p is not None and p.sampler is not None and (len(seeds) > 1 and opts.enable_batch_seeds or opts.eta_noise_seed_delta > 0): + if p is not None and p.sampler is not None and ( + len(seeds) > 1 and opts.enable_batch_seeds or opts.eta_noise_seed_delta > 0): sampler_noises = [[] for _ in range(p.sampler.number_of_needed_noises(p))] else: sampler_noises = None for i, seed in enumerate(seeds): - noise_shape = shape if seed_resize_from_h <= 0 or seed_resize_from_w <= 0 else (shape[0], seed_resize_from_h//8, seed_resize_from_w//8) + noise_shape = shape if seed_resize_from_h <= 0 or seed_resize_from_w <= 0 else ( + shape[0], seed_resize_from_h // 8, seed_resize_from_w // 8) subnoise = None if subseeds is not None: @@ -241,7 +251,7 @@ def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=0.0, see dx = max(-dx, 0) dy = max(-dy, 0) - x[:, ty:ty+h, tx:tx+w] = noise[:, dy:dy+h, dx:dx+w] + x[:, ty:ty + h, tx:tx + w] = noise[:, dy:dy + h, dx:dx + w] noise = x if sampler_noises is not None: @@ -293,14 +303,20 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration "Seed": all_seeds[index], "Face restoration": (opts.face_restoration_model if p.restore_faces else None), "Size": f"{p.width}x{p.height}", - "Model hash": getattr(p, 'sd_model_hash', None if not opts.add_model_hash_to_info or not shared.sd_model.sd_model_hash else shared.sd_model.sd_model_hash), - "Model": (None if not opts.add_model_name_to_info or not shared.sd_model.sd_checkpoint_info.model_name else shared.sd_model.sd_checkpoint_info.model_name.replace(',', '').replace(':', '')), - "Hypernet": (None if shared.loaded_hypernetwork is None else shared.loaded_hypernetwork.name.replace(',', '').replace(':', '')), + "Model hash": getattr(p, 'sd_model_hash', + None if not opts.add_model_hash_to_info or not shared.sd_model.sd_model_hash else shared.sd_model.sd_model_hash), + "Model": ( + None if not opts.add_model_name_to_info or not shared.sd_model.sd_checkpoint_info.model_name else shared.sd_model.sd_checkpoint_info.model_name.replace( + ',', '').replace(':', '')), + "Hypernet": ( + None if shared.loaded_hypernetwork is None else shared.loaded_hypernetwork.name.replace(',', '').replace( + ':', '')), "Batch size": (None if p.batch_size < 2 else p.batch_size), "Batch pos": (None if p.batch_size < 2 else position_in_batch), "Variation seed": (None if p.subseed_strength == 0 else all_subseeds[index]), "Variation seed strength": (None if p.subseed_strength == 0 else p.subseed_strength), - "Seed resize from": (None if p.seed_resize_from_w == 0 or p.seed_resize_from_h == 0 else f"{p.seed_resize_from_w}x{p.seed_resize_from_h}"), + "Seed resize from": ( + None if p.seed_resize_from_w == 0 or p.seed_resize_from_h == 0 else f"{p.seed_resize_from_w}x{p.seed_resize_from_h}"), "Denoising strength": getattr(p, 'denoising_strength', None), "Eta": (None if p.sampler is None or p.sampler.eta == p.sampler.default_eta else p.sampler.eta), "Clip skip": None if clip_skip <= 1 else clip_skip, @@ -309,7 +325,8 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration generation_params.update(p.extra_generation_params) - generation_params_text = ", ".join([k if k == v else f'{k}: {v}' for k, v in generation_params.items() if v is not None]) + generation_params_text = ", ".join( + [k if k == v else f'{k}: {v}' for k, v in generation_params.items() if v is not None]) negative_prompt_text = "\nNegative prompt: " + p.negative_prompt if p.negative_prompt else "" @@ -317,7 +334,9 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration def process_images(p: StableDiffusionProcessing, aesthetic_lr=0, aesthetic_weight=0, aesthetic_steps=0, - aesthetic_imgs=None,aesthetic_slerp=False) -> Processed: + aesthetic_imgs=None, aesthetic_slerp=False, aesthetic_imgs_text="", + aesthetic_slerp_angle=0.15, + aesthetic_text_negative=False) -> Processed: """this is the main loop that both txt2img and img2img use; it calls func_init once inside all the scopes and func_sample once per batch""" aesthetic_lr = float(aesthetic_lr) @@ -385,7 +404,7 @@ def process_images(p: StableDiffusionProcessing, aesthetic_lr=0, aesthetic_weigh for n in range(p.n_iter): if state.skipped: state.skipped = False - + if state.interrupted: break @@ -396,16 +415,19 @@ def process_images(p: StableDiffusionProcessing, aesthetic_lr=0, aesthetic_weigh if (len(prompts) == 0): break - #uc = p.sd_model.get_learned_conditioning(len(prompts) * [p.negative_prompt]) - #c = p.sd_model.get_learned_conditioning(prompts) + # uc = p.sd_model.get_learned_conditioning(len(prompts) * [p.negative_prompt]) + # c = p.sd_model.get_learned_conditioning(prompts) with devices.autocast(): if hasattr(shared.sd_model.cond_stage_model, "set_aesthetic_params"): - shared.sd_model.cond_stage_model.set_aesthetic_params(0, 0, 0) + shared.sd_model.cond_stage_model.set_aesthetic_params() uc = prompt_parser.get_learned_conditioning(shared.sd_model, len(prompts) * [p.negative_prompt], p.steps) if hasattr(shared.sd_model.cond_stage_model, "set_aesthetic_params"): shared.sd_model.cond_stage_model.set_aesthetic_params(aesthetic_lr, aesthetic_weight, - aesthetic_steps, aesthetic_imgs,aesthetic_slerp) + aesthetic_steps, aesthetic_imgs, + aesthetic_slerp, aesthetic_imgs_text, + aesthetic_slerp_angle, + aesthetic_text_negative) c = prompt_parser.get_multicond_learned_conditioning(shared.sd_model, prompts, p.steps) if len(model_hijack.comments) > 0: @@ -413,13 +435,13 @@ def process_images(p: StableDiffusionProcessing, aesthetic_lr=0, aesthetic_weigh comments[comment] = 1 if p.n_iter > 1: - shared.state.job = f"Batch {n+1} out of {p.n_iter}" + shared.state.job = f"Batch {n + 1} out of {p.n_iter}" with devices.autocast(): - samples_ddim = p.sample(conditioning=c, unconditional_conditioning=uc, seeds=seeds, subseeds=subseeds, subseed_strength=p.subseed_strength) + samples_ddim = p.sample(conditioning=c, unconditional_conditioning=uc, seeds=seeds, subseeds=subseeds, + subseed_strength=p.subseed_strength) if state.interrupted or state.skipped: - # if we are interrupted, sample returns just noise # use the image collected previously in sampler loop samples_ddim = shared.state.current_latent @@ -445,7 +467,9 @@ def process_images(p: StableDiffusionProcessing, aesthetic_lr=0, aesthetic_weigh if p.restore_faces: if opts.save and not p.do_not_save_samples and opts.save_images_before_face_restoration: - images.save_image(Image.fromarray(x_sample), p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-face-restoration") + images.save_image(Image.fromarray(x_sample), p.outpath_samples, "", seeds[i], prompts[i], + opts.samples_format, info=infotext(n, i), p=p, + suffix="-before-face-restoration") devices.torch_gc() @@ -456,7 +480,8 @@ def process_images(p: StableDiffusionProcessing, aesthetic_lr=0, aesthetic_weigh if p.color_corrections is not None and i < len(p.color_corrections): if opts.save and not p.do_not_save_samples and opts.save_images_before_color_correction: - images.save_image(image, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-color-correction") + images.save_image(image, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, + info=infotext(n, i), p=p, suffix="-before-color-correction") image = apply_color_correction(p.color_corrections[i], image) if p.overlay_images is not None and i < len(p.overlay_images): @@ -474,7 +499,8 @@ def process_images(p: StableDiffusionProcessing, aesthetic_lr=0, aesthetic_weigh image = image.convert('RGB') if opts.samples_save and not p.do_not_save_samples: - images.save_image(image, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p) + images.save_image(image, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, + info=infotext(n, i), p=p) text = infotext(n, i) infotexts.append(text) @@ -482,7 +508,7 @@ def process_images(p: StableDiffusionProcessing, aesthetic_lr=0, aesthetic_weigh image.info["parameters"] = text output_images.append(image) - del x_samples_ddim + del x_samples_ddim devices.torch_gc() @@ -504,10 +530,13 @@ def process_images(p: StableDiffusionProcessing, aesthetic_lr=0, aesthetic_weigh 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", all_seeds[0], 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, 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) class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): @@ -543,25 +572,34 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): self.sampler = sd_samplers.create_sampler_with_index(sd_samplers.samplers, self.sampler_index, self.sd_model) if not self.enable_hr: - x = create_random_tensors([opt_C, self.height // opt_f, self.width // opt_f], seeds=seeds, subseeds=subseeds, subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self) + x = create_random_tensors([opt_C, self.height // opt_f, self.width // opt_f], seeds=seeds, + subseeds=subseeds, subseed_strength=self.subseed_strength, + seed_resize_from_h=self.seed_resize_from_h, + seed_resize_from_w=self.seed_resize_from_w, p=self) samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning) return samples - x = create_random_tensors([opt_C, self.firstphase_height // opt_f, self.firstphase_width // opt_f], seeds=seeds, subseeds=subseeds, subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self) + x = create_random_tensors([opt_C, self.firstphase_height // opt_f, self.firstphase_width // opt_f], seeds=seeds, + subseeds=subseeds, subseed_strength=self.subseed_strength, + seed_resize_from_h=self.seed_resize_from_h, + seed_resize_from_w=self.seed_resize_from_w, p=self) samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning) truncate_x = (self.firstphase_width - self.firstphase_width_truncated) // opt_f truncate_y = (self.firstphase_height - self.firstphase_height_truncated) // opt_f - samples = samples[:, :, truncate_y//2:samples.shape[2]-truncate_y//2, truncate_x//2:samples.shape[3]-truncate_x//2] + samples = samples[:, :, truncate_y // 2:samples.shape[2] - truncate_y // 2, + truncate_x // 2:samples.shape[3] - truncate_x // 2] if self.scale_latent: - samples = torch.nn.functional.interpolate(samples, size=(self.height // opt_f, self.width // opt_f), mode="bilinear") + samples = torch.nn.functional.interpolate(samples, size=(self.height // opt_f, self.width // opt_f), + mode="bilinear") else: decoded_samples = decode_first_stage(self.sd_model, samples) if opts.upscaler_for_img2img is None or opts.upscaler_for_img2img == "None": - decoded_samples = torch.nn.functional.interpolate(decoded_samples, size=(self.height, self.width), mode="bilinear") + decoded_samples = torch.nn.functional.interpolate(decoded_samples, size=(self.height, self.width), + mode="bilinear") else: lowres_samples = torch.clamp((decoded_samples + 1.0) / 2.0, min=0.0, max=1.0) @@ -585,13 +623,16 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): self.sampler = sd_samplers.create_sampler_with_index(sd_samplers.samplers, self.sampler_index, self.sd_model) - noise = create_random_tensors(samples.shape[1:], seeds=seeds, subseeds=subseeds, subseed_strength=subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self) + noise = create_random_tensors(samples.shape[1:], seeds=seeds, subseeds=subseeds, + subseed_strength=subseed_strength, seed_resize_from_h=self.seed_resize_from_h, + seed_resize_from_w=self.seed_resize_from_w, p=self) # GC now before running the next img2img to prevent running out of memory x = None devices.torch_gc() - samples = self.sampler.sample_img2img(self, samples, noise, conditioning, unconditional_conditioning, steps=self.steps) + samples = self.sampler.sample_img2img(self, samples, noise, conditioning, unconditional_conditioning, + steps=self.steps) return samples @@ -599,7 +640,9 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): sampler = None - def __init__(self, init_images=None, resize_mode=0, denoising_strength=0.75, mask=None, mask_blur=4, inpainting_fill=0, inpaint_full_res=True, inpaint_full_res_padding=0, inpainting_mask_invert=0, **kwargs): + def __init__(self, init_images=None, resize_mode=0, denoising_strength=0.75, mask=None, mask_blur=4, + inpainting_fill=0, inpaint_full_res=True, inpaint_full_res_padding=0, inpainting_mask_invert=0, + **kwargs): super().__init__(**kwargs) self.init_images = init_images @@ -607,7 +650,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): self.denoising_strength: float = denoising_strength self.init_latent = None self.image_mask = mask - #self.image_unblurred_mask = None + # self.image_unblurred_mask = None self.latent_mask = None self.mask_for_overlay = None self.mask_blur = mask_blur @@ -619,7 +662,8 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): self.nmask = None def init(self, all_prompts, all_seeds, all_subseeds): - self.sampler = sd_samplers.create_sampler_with_index(sd_samplers.samplers_for_img2img, self.sampler_index, self.sd_model) + self.sampler = sd_samplers.create_sampler_with_index(sd_samplers.samplers_for_img2img, self.sampler_index, + self.sd_model) crop_region = None if self.image_mask is not None: @@ -628,7 +672,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): if self.inpainting_mask_invert: self.image_mask = ImageOps.invert(self.image_mask) - #self.image_unblurred_mask = self.image_mask + # self.image_unblurred_mask = self.image_mask if self.mask_blur > 0: self.image_mask = self.image_mask.filter(ImageFilter.GaussianBlur(self.mask_blur)) @@ -642,7 +686,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): mask = mask.crop(crop_region) self.image_mask = images.resize_image(2, mask, self.width, self.height) - self.paste_to = (x1, y1, x2-x1, y2-y1) + self.paste_to = (x1, y1, x2 - x1, y2 - y1) else: self.image_mask = images.resize_image(self.resize_mode, self.image_mask, self.width, self.height) np_mask = np.array(self.image_mask) @@ -665,7 +709,8 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): if self.image_mask is not None: image_masked = Image.new('RGBa', (image.width, image.height)) - image_masked.paste(image.convert("RGBA").convert("RGBa"), mask=ImageOps.invert(self.mask_for_overlay.convert('L'))) + image_masked.paste(image.convert("RGBA").convert("RGBa"), + mask=ImageOps.invert(self.mask_for_overlay.convert('L'))) self.overlay_images.append(image_masked.convert('RGBA')) @@ -714,12 +759,17 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): # this needs to be fixed to be done in sample() using actual seeds for batches if self.inpainting_fill == 2: - self.init_latent = self.init_latent * self.mask + create_random_tensors(self.init_latent.shape[1:], all_seeds[0:self.init_latent.shape[0]]) * self.nmask + self.init_latent = self.init_latent * self.mask + create_random_tensors(self.init_latent.shape[1:], + all_seeds[ + 0:self.init_latent.shape[ + 0]]) * self.nmask elif self.inpainting_fill == 3: self.init_latent = self.init_latent * self.mask def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength): - x = create_random_tensors([opt_C, self.height // opt_f, self.width // opt_f], seeds=seeds, subseeds=subseeds, subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self) + x = create_random_tensors([opt_C, self.height // opt_f, self.width // opt_f], seeds=seeds, subseeds=subseeds, + subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, + seed_resize_from_w=self.seed_resize_from_w, p=self) samples = self.sampler.sample_img2img(self, self.init_latent, x, conditioning, unconditional_conditioning) diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index 6d5196fe..192883b2 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -14,7 +14,8 @@ from modules.sd_hijack_optimizations import invokeAI_mps_available import ldm.modules.attention import ldm.modules.diffusionmodules.model -from transformers import CLIPVisionModel, CLIPModel +from tqdm import trange +from transformers import CLIPVisionModel, CLIPModel, CLIPTokenizer import torch.optim as optim import copy @@ -22,21 +23,25 @@ attention_CrossAttention_forward = ldm.modules.attention.CrossAttention.forward diffusionmodules_model_nonlinearity = ldm.modules.diffusionmodules.model.nonlinearity diffusionmodules_model_AttnBlock_forward = ldm.modules.diffusionmodules.model.AttnBlock.forward + def apply_optimizations(): undo_optimizations() ldm.modules.diffusionmodules.model.nonlinearity = silu - if cmd_opts.force_enable_xformers or (cmd_opts.xformers and shared.xformers_available and torch.version.cuda and (6, 0) <= torch.cuda.get_device_capability(shared.device) <= (8, 6)): + if cmd_opts.force_enable_xformers or (cmd_opts.xformers and shared.xformers_available and torch.version.cuda and ( + 6, 0) <= torch.cuda.get_device_capability(shared.device) <= (8, 6)): print("Applying xformers cross attention optimization.") ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.xformers_attention_forward ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.xformers_attnblock_forward elif cmd_opts.opt_split_attention_v1: print("Applying v1 cross attention optimization.") ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_v1 - elif not cmd_opts.disable_opt_split_attention and (cmd_opts.opt_split_attention_invokeai or not torch.cuda.is_available()): + elif not cmd_opts.disable_opt_split_attention and ( + cmd_opts.opt_split_attention_invokeai or not torch.cuda.is_available()): if not invokeAI_mps_available and shared.device.type == 'mps': - print("The InvokeAI cross attention optimization for MPS requires the psutil package which is not installed.") + print( + "The InvokeAI cross attention optimization for MPS requires the psutil package which is not installed.") print("Applying v1 cross attention optimization.") ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_v1 else: @@ -112,14 +117,16 @@ class StableDiffusionModelHijack: _, remade_batch_tokens, _, _, _, token_count = self.clip.process_text([text]) return remade_batch_tokens[0], token_count, get_target_prompt_token_count(token_count) + 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)) + 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 + res = (torch.sin((1.0 - val) * omega) / so).unsqueeze(1) * low + (torch.sin(val * omega) / so).unsqueeze(1) * high return res + class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): def __init__(self, wrapped, hijack): super().__init__() @@ -128,6 +135,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): self.wrapped.transformer.name_or_path ) del self.clipModel.vision_model + self.tokenizer = CLIPTokenizer.from_pretrained(self.wrapped.transformer.name_or_path) self.hijack: StableDiffusionModelHijack = hijack self.tokenizer = wrapped.tokenizer # self.vision = CLIPVisionModel.from_pretrained(self.wrapped.transformer.name_or_path).eval() @@ -139,7 +147,8 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): self.comma_token = [v for k, v in self.tokenizer.get_vocab().items() if k == ','][0] - tokens_with_parens = [(k, v) for k, v in self.tokenizer.get_vocab().items() if '(' in k or ')' in k or '[' in k or ']' in k] + tokens_with_parens = [(k, v) for k, v in self.tokenizer.get_vocab().items() if + '(' in k or ')' in k or '[' in k or ']' in k] for text, ident in tokens_with_parens: mult = 1.0 for c in text: @@ -155,8 +164,13 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): if mult != 1.0: self.token_mults[ident] = mult - def set_aesthetic_params(self, aesthetic_lr, aesthetic_weight, aesthetic_steps, image_embs_name=None, - aesthetic_slerp=True): + def set_aesthetic_params(self, 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 @@ -180,7 +194,8 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): else: parsed = [[line, 1.0]] - tokenized = self.wrapped.tokenizer([text for text, _ in parsed], truncation=False, add_special_tokens=False)["input_ids"] + tokenized = self.wrapped.tokenizer([text for text, _ in parsed], truncation=False, add_special_tokens=False)[ + "input_ids"] fixes = [] remade_tokens = [] @@ -196,18 +211,20 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): if token == self.comma_token: last_comma = len(remade_tokens) - elif opts.comma_padding_backtrack != 0 and max(len(remade_tokens), 1) % 75 == 0 and last_comma != -1 and len(remade_tokens) - last_comma <= opts.comma_padding_backtrack: + elif opts.comma_padding_backtrack != 0 and max(len(remade_tokens), + 1) % 75 == 0 and last_comma != -1 and len( + remade_tokens) - last_comma <= opts.comma_padding_backtrack: last_comma += 1 reloc_tokens = remade_tokens[last_comma:] reloc_mults = multipliers[last_comma:] remade_tokens = remade_tokens[:last_comma] length = len(remade_tokens) - + rem = int(math.ceil(length / 75)) * 75 - length remade_tokens += [id_end] * rem + reloc_tokens multipliers = multipliers[:last_comma] + [1.0] * rem + reloc_mults - + if embedding is None: remade_tokens.append(token) multipliers.append(weight) @@ -248,7 +265,8 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): if line in cache: remade_tokens, fixes, multipliers = cache[line] else: - remade_tokens, fixes, multipliers, current_token_count = self.tokenize_line(line, used_custom_terms, hijack_comments) + remade_tokens, fixes, multipliers, current_token_count = self.tokenize_line(line, used_custom_terms, + hijack_comments) token_count = max(current_token_count, token_count) cache[line] = (remade_tokens, fixes, multipliers) @@ -259,7 +277,6 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): return batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count - def process_text_old(self, text): id_start = self.wrapped.tokenizer.bos_token_id id_end = self.wrapped.tokenizer.eos_token_id @@ -289,7 +306,8 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): while i < len(tokens): token = tokens[i] - embedding, embedding_length_in_tokens = self.hijack.embedding_db.find_embedding_at_position(tokens, i) + embedding, embedding_length_in_tokens = self.hijack.embedding_db.find_embedding_at_position(tokens, + i) mult_change = self.token_mults.get(token) if opts.enable_emphasis else None if mult_change is not None: @@ -312,11 +330,12 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): ovf = remade_tokens[maxlen - 2:] overflowing_words = [vocab.get(int(x), "") for x in ovf] overflowing_text = self.wrapped.tokenizer.convert_tokens_to_string(''.join(overflowing_words)) - hijack_comments.append(f"Warning: too many input tokens; some ({len(overflowing_words)}) have been truncated:\n{overflowing_text}\n") + hijack_comments.append( + f"Warning: too many input tokens; some ({len(overflowing_words)}) have been truncated:\n{overflowing_text}\n") token_count = len(remade_tokens) remade_tokens = remade_tokens + [id_end] * (maxlen - 2 - len(remade_tokens)) - remade_tokens = [id_start] + remade_tokens[0:maxlen-2] + [id_end] + remade_tokens = [id_start] + remade_tokens[0:maxlen - 2] + [id_end] cache[tuple_tokens] = (remade_tokens, fixes, multipliers) multipliers = multipliers + [1.0] * (maxlen - 2 - len(multipliers)) @@ -326,23 +345,26 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): hijack_fixes.append(fixes) batch_multipliers.append(multipliers) return batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count - + def forward(self, text): use_old = opts.use_old_emphasis_implementation if use_old: - batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count = self.process_text_old(text) + batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count = self.process_text_old( + text) else: - batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count = self.process_text(text) + batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count = self.process_text( + text) self.hijack.comments += hijack_comments if len(used_custom_terms) > 0: - self.hijack.comments.append("Used embeddings: " + ", ".join([f'{word} [{checksum}]' for word, checksum in used_custom_terms])) - + self.hijack.comments.append( + "Used embeddings: " + ", ".join([f'{word} [{checksum}]' for word, checksum in used_custom_terms])) + if use_old: self.hijack.fixes = hijack_fixes return self.process_tokens(remade_batch_tokens, batch_multipliers) - + z = None i = 0 while max(map(len, remade_batch_tokens)) != 0: @@ -356,7 +378,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): if fix[0] == i: fixes.append(fix[1]) self.hijack.fixes.append(fixes) - + tokens = [] multipliers = [] for j in range(len(remade_batch_tokens)): @@ -378,19 +400,30 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): remade_batch_tokens] tokens = torch.asarray(remade_batch_tokens).to(device) + + model = copy.deepcopy(self.clipModel).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( + **self.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(): - model = copy.deepcopy(self.clipModel).to(device) - model.requires_grad_(True) # We optimize the model to maximize the similarity optimizer = optim.Adam( model.text_model.parameters(), lr=self.aesthetic_lr ) - for i in range(self.aesthetic_steps): + for i 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 @ self.image_embs.T + sim = text_embs @ img_embs.T loss = -sim optimizer.zero_grad() loss.mean().backward() @@ -405,6 +438,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): model.cpu() del model + zn = torch.concat([zn for i in range(z.shape[1] // 77)], 1) if self.slerp: z = slerp(z, zn, self.aesthetic_weight) else: @@ -413,15 +447,16 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): remade_batch_tokens = rem_tokens batch_multipliers = rem_multipliers i += 1 - + return z - - + def process_tokens(self, remade_batch_tokens, batch_multipliers): if not opts.use_old_emphasis_implementation: - remade_batch_tokens = [[self.wrapped.tokenizer.bos_token_id] + x[:75] + [self.wrapped.tokenizer.eos_token_id] for x in remade_batch_tokens] + remade_batch_tokens = [ + [self.wrapped.tokenizer.bos_token_id] + x[:75] + [self.wrapped.tokenizer.eos_token_id] for x in + remade_batch_tokens] batch_multipliers = [[1.0] + x[:75] + [1.0] for x in batch_multipliers] - + tokens = torch.asarray(remade_batch_tokens).to(device) outputs = self.wrapped.transformer(input_ids=tokens, output_hidden_states=-opts.CLIP_stop_at_last_layers) @@ -461,8 +496,8 @@ class EmbeddingsWithFixes(torch.nn.Module): for fixes, tensor in zip(batch_fixes, inputs_embeds): for offset, embedding in fixes: emb = embedding.vec - emb_len = min(tensor.shape[0]-offset-1, emb.shape[0]) - tensor = torch.cat([tensor[0:offset+1], emb[0:emb_len], tensor[offset+1+emb_len:]]) + emb_len = min(tensor.shape[0] - offset - 1, emb.shape[0]) + tensor = torch.cat([tensor[0:offset + 1], emb[0:emb_len], tensor[offset + 1 + emb_len:]]) vecs.append(tensor) diff --git a/modules/shared.py b/modules/shared.py index cf13a10d..7cd608ca 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -95,6 +95,10 @@ loaded_hypernetwork = None 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")} +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")} def reload_hypernetworks(): global hypernetworks diff --git a/modules/txt2img.py b/modules/txt2img.py index 78342024..eedcdfe0 100644 --- a/modules/txt2img.py +++ b/modules/txt2img.py @@ -13,7 +13,11 @@ def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: aesthetic_lr=0, aesthetic_weight=0, aesthetic_steps=0, aesthetic_imgs=None, - aesthetic_slerp=False, *args): + aesthetic_slerp=False, + aesthetic_imgs_text="", + aesthetic_slerp_angle=0.15, + aesthetic_text_negative=False, + *args): p = StableDiffusionProcessingTxt2Img( sd_model=shared.sd_model, outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples, @@ -47,7 +51,9 @@ def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: processed = modules.scripts.scripts_txt2img.run(p, *args) if processed is None: - processed = process_images(p, aesthetic_lr, aesthetic_weight, aesthetic_steps, aesthetic_imgs, aesthetic_slerp) + processed = process_images(p, aesthetic_lr, aesthetic_weight, aesthetic_steps, aesthetic_imgs, aesthetic_slerp,aesthetic_imgs_text, + aesthetic_slerp_angle, + aesthetic_text_negative) shared.total_tqdm.clear() diff --git a/modules/ui.py b/modules/ui.py index d961d126..e98e2113 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -41,6 +41,7 @@ from modules import prompt_parser from modules.images import save_image import modules.textual_inversion.ui import modules.hypernetworks.ui +import modules.aesthetic_clip # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI mimetypes.init() @@ -449,7 +450,7 @@ def create_toprow(is_img2img): with gr.Row(): negative_prompt = gr.Textbox(label="Negative prompt", elem_id="negative_prompt", show_label=False, placeholder="Negative prompt", lines=2) with gr.Column(scale=1, elem_id="roll_col"): - sh = gr.Button(elem_id="sh", visible=True) + sh = gr.Button(elem_id="sh", visible=True) with gr.Column(scale=1, elem_id="style_neg_col"): prompt_style2 = gr.Dropdown(label="Style 2", elem_id=f"{id_part}_style2_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())), visible=len(shared.prompt_styles.styles) > 1) @@ -536,9 +537,13 @@ def create_ui(wrap_gradio_gpu_call): height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512) with gr.Group(): - aesthetic_lr = gr.Textbox(label='Learning rate', placeholder="Learning rate", value="0.005") - aesthetic_weight = gr.Slider(minimum=0, maximum=1, step=0.01, label="Aesthetic weight", value=0.7) - aesthetic_steps = gr.Slider(minimum=0, maximum=50, step=1, label="Aesthetic steps", value=50) + aesthetic_lr = gr.Textbox(label='Learning rate', placeholder="Learning rate", value="0.0001") + aesthetic_weight = gr.Slider(minimum=0, maximum=1, step=0.01, label="Aesthetic weight", value=0.9) + aesthetic_steps = gr.Slider(minimum=0, maximum=256, step=1, label="Aesthetic steps", value=5) + 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) aesthetic_imgs = gr.Dropdown(sorted(aesthetic_embeddings.keys()), label="Imgs embedding", value=sorted(aesthetic_embeddings.keys())[0] if len(aesthetic_embeddings) > 0 else None) aesthetic_slerp = gr.Checkbox(label="Slerp interpolation", value=False) @@ -617,7 +622,10 @@ def create_ui(wrap_gradio_gpu_call): aesthetic_weight, aesthetic_steps, aesthetic_imgs, - aesthetic_slerp + aesthetic_slerp, + aesthetic_imgs_text, + aesthetic_slerp_angle, + aesthetic_text_negative ] + custom_inputs, outputs=[ txt2img_gallery, @@ -721,7 +729,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Row(): inpaint_full_res = gr.Checkbox(label='Inpaint at full resolution', value=False) - inpaint_full_res_padding = gr.Slider(label='Inpaint at full resolution padding, pixels', minimum=0, maximum=256, step=4, value=32) + inpaint_full_res_padding = gr.Slider(label='Inpaint at full resolution padding, pixels', minimum=0, maximum=1024, step=4, value=32) with gr.TabItem('Batch img2img', id='batch'): hidden = '
Disabled when launched with --hide-ui-dir-config.' if shared.cmd_opts.hide_ui_dir_config else '' @@ -1071,6 +1079,17 @@ def create_ui(wrap_gradio_gpu_call): with gr.Column(): create_embedding = gr.Button(value="Create embedding", variant='primary') + with gr.Tab(label="Create 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"]) @@ -1139,7 +1158,7 @@ def create_ui(wrap_gradio_gpu_call): fn=modules.textual_inversion.ui.create_embedding, inputs=[ new_embedding_name, - initialization_text, + process_src, nvpt, ], outputs=[ @@ -1149,6 +1168,20 @@ def create_ui(wrap_gradio_gpu_call): ] ) + create_embedding_ae.click( + fn=modules.aesthetic_clip.generate_imgs_embd, + inputs=[ + new_embedding_name_ae, + process_src_ae, + batch_ae + ], + outputs=[ + aesthetic_imgs, + ti_output, + ti_outcome, + ] + ) + create_hypernetwork.click( fn=modules.hypernetworks.ui.create_hypernetwork, inputs=[ -- cgit v1.2.3 From 523140d7805c644700009b8a2483ff4eb4a22304 Mon Sep 17 00:00:00 2001 From: MalumaDev Date: Sun, 16 Oct 2022 10:23:30 +0200 Subject: ui fix --- modules/aesthetic_clip.py | 3 +-- modules/sd_hijack.py | 3 +-- modules/shared.py | 2 ++ modules/ui.py | 24 ++++++++++++++---------- 4 files changed, 18 insertions(+), 14 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/aesthetic_clip.py b/modules/aesthetic_clip.py index 68264284..ccb35c73 100644 --- a/modules/aesthetic_clip.py +++ b/modules/aesthetic_clip.py @@ -74,5 +74,4 @@ def generate_imgs_embd(name, folder, batch_size): """ shared.update_aesthetic_embeddings() return gr.Dropdown.update(choices=sorted(shared.aesthetic_embeddings.keys()), label="Imgs embedding", - value=sorted(shared.aesthetic_embeddings.keys())[0] if len( - shared.aesthetic_embeddings) > 0 else None), res, "" + value="None"), res, "" diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index 01fcb78f..2de2eed5 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -392,8 +392,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): z1 = self.process_tokens(tokens, multipliers) z = z1 if z is None else torch.cat((z, z1), axis=-2) - if len(text[ - 0]) != 0 and self.aesthetic_steps != 0 and self.aesthetic_lr != 0 and self.aesthetic_weight != 0 and self.image_embs_name != None: + if self.aesthetic_steps != 0 and self.aesthetic_lr != 0 and self.aesthetic_weight != 0 and self.image_embs_name != None: if not opts.use_old_emphasis_implementation: remade_batch_tokens = [ [self.wrapped.tokenizer.bos_token_id] + x[:75] + [self.wrapped.tokenizer.eos_token_id] for x in diff --git a/modules/shared.py b/modules/shared.py index 3c5ffef1..e2c98b2d 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -96,11 +96,13 @@ loaded_hypernetwork = None 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 = aesthetic_embeddings | {"None": None} 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 = aesthetic_embeddings | {"None": None} def reload_hypernetworks(): global hypernetworks diff --git a/modules/ui.py b/modules/ui.py index 13ba3142..4069f0d2 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -594,19 +594,23 @@ def create_ui(wrap_gradio_gpu_call): height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512) with gr.Group(): - aesthetic_lr = gr.Textbox(label='Aesthetic learning rate', placeholder="Aesthetic learning rate", value="0.0001") - - 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.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_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) + 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(aesthetic_embeddings.keys()), + label="Aesthetic imgs embedding", + value="None") - aesthetic_imgs = gr.Dropdown(sorted(aesthetic_embeddings.keys()), label="Aesthetic imgs embedding", value=sorted(aesthetic_embeddings.keys())[0] if len(aesthetic_embeddings) > 0 else None) + 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) - aesthetic_slerp = gr.Checkbox(label="Slerp interpolation", value=False) with gr.Row(): restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1) -- cgit v1.2.3 From 9324cdaa3199d65c182858785dd1eca42b192b8e Mon Sep 17 00:00:00 2001 From: MalumaDev Date: Sun, 16 Oct 2022 17:53:56 +0200 Subject: ui fix, re organization of the code --- modules/aesthetic_clip.py | 154 +++++++++++++++++++++++++++++++++-- modules/img2img.py | 14 +++- modules/processing.py | 29 ++----- modules/sd_hijack.py | 102 ++--------------------- modules/sd_models.py | 5 +- modules/shared.py | 14 +++- modules/textual_inversion/dataset.py | 2 +- modules/txt2img.py | 18 ++-- modules/ui.py | 52 +++++++----- 9 files changed, 233 insertions(+), 157 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/aesthetic_clip.py b/modules/aesthetic_clip.py index ccb35c73..34efa931 100644 --- a/modules/aesthetic_clip.py +++ b/modules/aesthetic_clip.py @@ -1,3 +1,4 @@ +import copy import itertools import os from pathlib import Path @@ -7,11 +8,12 @@ import gc import gradio as gr import torch from PIL import Image -from modules import shared -from modules.shared import device -from transformers import CLIPModel, CLIPProcessor +from torch import optim -from tqdm.auto import tqdm +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): @@ -37,12 +39,39 @@ def iter_to_batched(iterable, n=1): yield chunk +def create_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") + + 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 + + def generate_imgs_embd(name, folder, batch_size): # clipModel = CLIPModel.from_pretrained( # shared.sd_model.cond_stage_model.clipModel.name_or_path # ) - model = CLIPModel.from_pretrained(shared.sd_model.cond_stage_model.clipModel.name_or_path).to(device) - processor = CLIPProcessor.from_pretrained(shared.sd_model.cond_stage_model.clipModel.name_or_path) + model = shared.clip_model.to(device) + processor = CLIPProcessor.from_pretrained(model.name_or_path) with torch.no_grad(): embs = [] @@ -63,7 +92,6 @@ def generate_imgs_embd(name, folder, batch_size): torch.save(embs, path) model = model.cpu() - del model del processor del embs gc.collect() @@ -74,4 +102,114 @@ def generate_imgs_embd(name, folder, batch_size): """ shared.update_aesthetic_embeddings() return gr.Dropdown.update(choices=sorted(shared.aesthetic_embeddings.keys()), label="Imgs embedding", - value="None"), res, "" + 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, 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) + + 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(shared.clip_model).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/img2img.py b/modules/img2img.py index 24126774..4ed80c4b 100644 --- a/modules/img2img.py +++ b/modules/img2img.py @@ -56,7 +56,14 @@ 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, *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, + 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): is_inpaint = mode == 1 is_batch = mode == 2 @@ -109,6 +116,11 @@ 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(float(aesthetic_lr), float(aesthetic_weight), int(aesthetic_steps), + aesthetic_imgs, aesthetic_slerp, aesthetic_imgs_text, + aesthetic_slerp_angle, + aesthetic_text_negative) + 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 1db26c3e..685f9fcd 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -146,7 +146,8 @@ class Processed: self.prompt = self.prompt if type(self.prompt) != list else self.prompt[0] self.negative_prompt = self.negative_prompt if type(self.negative_prompt) != list else self.negative_prompt[0] self.seed = int(self.seed if type(self.seed) != list else self.seed[0]) if self.seed is not None else -1 - self.subseed = int(self.subseed if type(self.subseed) != list else self.subseed[0]) if self.subseed is not None else -1 + self.subseed = int( + self.subseed if type(self.subseed) != list else self.subseed[0]) if self.subseed is not None else -1 self.all_prompts = all_prompts or [self.prompt] self.all_seeds = all_seeds or [self.seed] @@ -332,16 +333,9 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration return f"{all_prompts[index]}{negative_prompt_text}\n{generation_params_text}".strip() -def process_images(p: StableDiffusionProcessing, 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) -> Processed: +def process_images(p: StableDiffusionProcessing) -> Processed: """this is the main loop that both txt2img and img2img use; it calls func_init once inside all the scopes and func_sample once per batch""" - aesthetic_lr = float(aesthetic_lr) - aesthetic_weight = float(aesthetic_weight) - aesthetic_steps = int(aesthetic_steps) - if type(p.prompt) == list: assert (len(p.prompt) > 0) else: @@ -417,16 +411,10 @@ def process_images(p: StableDiffusionProcessing, aesthetic_lr=0, aesthetic_weigh # uc = p.sd_model.get_learned_conditioning(len(prompts) * [p.negative_prompt]) # c = p.sd_model.get_learned_conditioning(prompts) with devices.autocast(): - if hasattr(shared.sd_model.cond_stage_model, "set_aesthetic_params"): - shared.sd_model.cond_stage_model.set_aesthetic_params() + shared.aesthetic_clip.set_skip(True) uc = prompt_parser.get_learned_conditioning(shared.sd_model, len(prompts) * [p.negative_prompt], p.steps) - if hasattr(shared.sd_model.cond_stage_model, "set_aesthetic_params"): - shared.sd_model.cond_stage_model.set_aesthetic_params(aesthetic_lr, aesthetic_weight, - aesthetic_steps, aesthetic_imgs, - aesthetic_slerp, aesthetic_imgs_text, - aesthetic_slerp_angle, - aesthetic_text_negative) + shared.aesthetic_clip.set_skip(False) c = prompt_parser.get_multicond_learned_conditioning(shared.sd_model, prompts, p.steps) if len(model_hijack.comments) > 0: @@ -582,7 +570,6 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): self.truncate_x = int(self.firstphase_width - firstphase_width_truncated) // opt_f self.truncate_y = int(self.firstphase_height - firstphase_height_truncated) // opt_f - def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength): self.sampler = sd_samplers.create_sampler_with_index(sd_samplers.samplers, self.sampler_index, self.sd_model) @@ -600,10 +587,12 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): seed_resize_from_w=self.seed_resize_from_w, p=self) samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning) - samples = samples[:, :, self.truncate_y//2:samples.shape[2]-self.truncate_y//2, self.truncate_x//2:samples.shape[3]-self.truncate_x//2] + samples = samples[:, :, self.truncate_y // 2:samples.shape[2] - self.truncate_y // 2, + self.truncate_x // 2:samples.shape[3] - self.truncate_x // 2] if opts.use_scale_latent_for_hires_fix: - samples = torch.nn.functional.interpolate(samples, size=(self.height // opt_f, self.width // opt_f), mode="bilinear") + samples = torch.nn.functional.interpolate(samples, size=(self.height // opt_f, self.width // opt_f), + mode="bilinear") else: decoded_samples = decode_first_stage(self.sd_model, samples) lowres_samples = torch.clamp((decoded_samples + 1.0) / 2.0, min=0.0, max=1.0) diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index 5d0590af..227e7670 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -29,8 +29,8 @@ def apply_optimizations(): ldm.modules.diffusionmodules.model.nonlinearity = silu - - if cmd_opts.force_enable_xformers or (cmd_opts.xformers and shared.xformers_available and torch.version.cuda and (6, 0) <= torch.cuda.get_device_capability(shared.device) <= (9, 0)): + if cmd_opts.force_enable_xformers or (cmd_opts.xformers and shared.xformers_available and torch.version.cuda and ( + 6, 0) <= torch.cuda.get_device_capability(shared.device) <= (9, 0)): print("Applying xformers cross attention optimization.") ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.xformers_attention_forward ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.xformers_attnblock_forward @@ -118,33 +118,14 @@ class StableDiffusionModelHijack: return remade_batch_tokens[0], token_count, get_target_prompt_token_count(token_count) -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 FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): def __init__(self, wrapped, hijack): super().__init__() self.wrapped = wrapped - self.clipModel = CLIPModel.from_pretrained( - self.wrapped.transformer.name_or_path - ) - del self.clipModel.vision_model - self.tokenizer = CLIPTokenizer.from_pretrained(self.wrapped.transformer.name_or_path) - self.hijack: StableDiffusionModelHijack = hijack - self.tokenizer = wrapped.tokenizer - # self.vision = CLIPVisionModel.from_pretrained(self.wrapped.transformer.name_or_path).eval() - self.image_embs_name = None - self.image_embs = None - self.load_image_embs(None) self.token_mults = {} - + self.hijack: StableDiffusionModelHijack = hijack + self.tokenizer = wrapped.tokenizer self.comma_token = [v for k, v in self.tokenizer.get_vocab().items() if k == ','][0] tokens_with_parens = [(k, v) for k, v in self.tokenizer.get_vocab().items() if @@ -164,28 +145,6 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): if mult != 1.0: self.token_mults[ident] = mult - def set_aesthetic_params(self, 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) - - 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 - 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 tokenize_line(self, line, used_custom_terms, hijack_comments): id_end = self.wrapped.tokenizer.eos_token_id @@ -391,58 +350,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): z1 = self.process_tokens(tokens, multipliers) z = z1 if z is None else torch.cat((z, z1), axis=-2) - - if self.aesthetic_steps != 0 and self.aesthetic_lr != 0 and self.aesthetic_weight != 0 and self.image_embs_name != None: - if not opts.use_old_emphasis_implementation: - remade_batch_tokens = [ - [self.wrapped.tokenizer.bos_token_id] + x[:75] + [self.wrapped.tokenizer.eos_token_id] for x in - remade_batch_tokens] - - tokens = torch.asarray(remade_batch_tokens).to(device) - - model = copy.deepcopy(self.clipModel).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( - **self.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 i 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 - - zn = torch.concat([zn for i in range(z.shape[1] // 77)], 1) - if self.slerp: - z = slerp(z, zn, self.aesthetic_weight) - else: - z = z * (1 - self.aesthetic_weight) + zn * self.aesthetic_weight - + z = shared.aesthetic_clip(z, remade_batch_tokens) remade_batch_tokens = rem_tokens batch_multipliers = rem_multipliers i += 1 diff --git a/modules/sd_models.py b/modules/sd_models.py index 3aa21ec1..8e4ee435 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -20,7 +20,7 @@ checkpoints_loaded = collections.OrderedDict() try: # this silences the annoying "Some weights of the model checkpoint were not used when initializing..." message at start. - from transformers import logging + from transformers import logging, CLIPModel logging.set_verbosity_error() except Exception: @@ -196,6 +196,9 @@ def load_model(): sd_hijack.model_hijack.hijack(sd_model) + if shared.clip_model is None or shared.clip_model.transformer.name_or_path != sd_model.cond_stage_model.wrapped.transformer.name_or_path: + shared.clip_model = CLIPModel.from_pretrained(sd_model.cond_stage_model.wrapped.transformer.name_or_path) + sd_model.eval() print(f"Model loaded.") diff --git a/modules/shared.py b/modules/shared.py index e2c98b2d..e19ca779 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -3,6 +3,7 @@ import datetime import json import os import sys +from collections import OrderedDict import gradio as gr import tqdm @@ -94,15 +95,15 @@ os.makedirs(cmd_opts.hypernetwork_dir, exist_ok=True) hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir) loaded_hypernetwork = None -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 = aesthetic_embeddings | {"None": None} +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 = aesthetic_embeddings | {"None": None} + aesthetic_embeddings = OrderedDict(**{"None": None}, **aesthetic_embeddings) + +update_aesthetic_embeddings() def reload_hypernetworks(): global hypernetworks @@ -381,6 +382,11 @@ sd_upscalers = [] sd_model = None +clip_model = None + +from modules.aesthetic_clip import AestheticCLIP +aesthetic_clip = AestheticCLIP() + progress_print_out = sys.stdout diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py index 68ceffe3..23bb4b6a 100644 --- a/modules/textual_inversion/dataset.py +++ b/modules/textual_inversion/dataset.py @@ -49,7 +49,7 @@ class PersonalizedBase(Dataset): print("Preparing dataset...") for path in tqdm.tqdm(self.image_paths): try: - image = Image.open(path).convert('RGB').resize((self.width, self.height), PIL.Image.Resampling.BICUBIC) + image = Image.open(path).convert('RGB').resize((self.width, self.height), PIL.Image.BICUBIC) except Exception: continue diff --git a/modules/txt2img.py b/modules/txt2img.py index 8f394d05..6cbc50fc 100644 --- a/modules/txt2img.py +++ b/modules/txt2img.py @@ -1,12 +1,17 @@ import modules.scripts -from modules.processing import StableDiffusionProcessing, Processed, StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images +from modules.processing import StableDiffusionProcessing, Processed, StableDiffusionProcessingTxt2Img, \ + StableDiffusionProcessingImg2Img, process_images from modules.shared import opts, cmd_opts import modules.shared as shared 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, +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, @@ -41,15 +46,17 @@ 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(float(aesthetic_lr), float(aesthetic_weight), int(aesthetic_steps), + aesthetic_imgs, aesthetic_slerp, aesthetic_imgs_text, aesthetic_slerp_angle, + aesthetic_text_negative) + if cmd_opts.enable_console_prompts: print(f"\ntxt2img: {prompt}", file=shared.progress_print_out) processed = modules.scripts.scripts_txt2img.run(p, *args) if processed is None: - processed = process_images(p, aesthetic_lr, aesthetic_weight, aesthetic_steps, aesthetic_imgs, aesthetic_slerp,aesthetic_imgs_text, - aesthetic_slerp_angle, - aesthetic_text_negative) + processed = process_images(p) shared.total_tqdm.clear() @@ -61,4 +68,3 @@ def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: processed.images = [] return processed.images, generation_info_js, plaintext_to_html(processed.info) - diff --git a/modules/ui.py b/modules/ui.py index 4069f0d2..0e5d73f0 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -43,7 +43,7 @@ from modules.images import save_image import modules.textual_inversion.ui import modules.hypernetworks.ui -import modules.aesthetic_clip +import modules.aesthetic_clip as aesthetic_clip import modules.images_history as img_his @@ -593,23 +593,25 @@ def create_ui(wrap_gradio_gpu_call): width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512) height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512) - 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(aesthetic_embeddings.keys()), - label="Aesthetic imgs embedding", - value="None") - - 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) + # 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(aesthetic_embeddings.keys()), + # label="Aesthetic imgs embedding", + # value="None") + # + # 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) + + 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.Row(): @@ -840,6 +842,9 @@ def create_ui(wrap_gradio_gpu_call): width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512) height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512) + 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.Row(): restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1) tiling = gr.Checkbox(label='Tiling', value=False) @@ -944,6 +949,14 @@ 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, @@ -1283,7 +1296,7 @@ def create_ui(wrap_gradio_gpu_call): ) create_embedding_ae.click( - fn=modules.aesthetic_clip.generate_imgs_embd, + fn=aesthetic_clip.generate_imgs_embd, inputs=[ new_embedding_name_ae, process_src_ae, @@ -1291,6 +1304,7 @@ def create_ui(wrap_gradio_gpu_call): ], outputs=[ aesthetic_imgs, + aesthetic_imgs_im, ti_output, ti_outcome, ] -- cgit v1.2.3 From eb299527b1e5d1f83a14641647fca72e8fb305ac Mon Sep 17 00:00:00 2001 From: yfszzx Date: Tue, 18 Oct 2022 20:14:11 +0800 Subject: Image browser --- javascript/images_history.js | 19 ++-- modules/images_history.py | 227 ++++++++++++++++++++++++++++--------------- modules/shared.py | 7 +- modules/ui.py | 2 +- uitest.bat | 2 + uitest.py | 124 +++++++++++++++++++++++ 6 files changed, 289 insertions(+), 92 deletions(-) create mode 100644 uitest.bat create mode 100644 uitest.py (limited to 'modules/shared.py') diff --git a/javascript/images_history.js b/javascript/images_history.js index 3c028bc6..182d730b 100644 --- a/javascript/images_history.js +++ b/javascript/images_history.js @@ -145,9 +145,10 @@ function images_history_enable_del_buttons(){ } function images_history_init(){ - var loaded = gradioApp().getElementById("images_history_reconstruct_directory") - if (loaded){ - var init_status = loaded.querySelector("input").checked + // var loaded = gradioApp().getElementById("images_history_reconstruct_directory") + // if (loaded){ + // var init_status = loaded.querySelector("input").checked + if (gradioApp().getElementById("images_history_finish_render")){ for (var i in images_history_tab_list ){ tab = images_history_tab_list[i]; gradioApp().getElementById(tab + '_images_history').classList.add("images_history_cantainor"); @@ -163,19 +164,17 @@ function images_history_init(){ for (var i in images_history_tab_list){ var tabname = images_history_tab_list[i] tab_btns[i].setAttribute("tabname", tabname); - if (init_status){ - tab_btns[i].addEventListener('click', images_history_click_tab); - } - } - if (init_status){ - tab_btns[0].click(); + // if (!init_status){ + // tab_btns[i].addEventListener('click', images_history_click_tab); + // } + tab_btns[i].addEventListener('click', images_history_click_tab); } } else { setTimeout(images_history_init, 500); } } -var images_history_tab_list = ["txt2img", "img2img", "extras", "saved"]; +var images_history_tab_list = ["custom", "txt2img", "img2img", "extras", "saved"]; setTimeout(images_history_init, 500); document.addEventListener("DOMContentLoaded", function() { var mutationObserver = new MutationObserver(function(m){ diff --git a/modules/images_history.py b/modules/images_history.py index 20324557..d56f3a25 100644 --- a/modules/images_history.py +++ b/modules/images_history.py @@ -4,6 +4,7 @@ import time import hashlib import gradio system_bak_path = "webui_log_and_bak" +browser_tabname = "custom" def is_valid_date(date): try: time.strptime(date, "%Y%m%d") @@ -99,13 +100,15 @@ def auto_sorting(dir_name): date_list.append(today) return sorted(date_list, reverse=True) -def archive_images(dir_name, date_to): +def archive_images(dir_name, date_to): + filenames = [] loads_num =int(opts.images_history_num_per_page * opts.images_history_pages_num) + 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 opts.images_history_reconstruct_directory: - date_list = auto_sorting(dir_name) - 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_list = auto_sorting(dir_name) for date in date_list: if date <= date_to: path = os.path.join(dir_name, date) @@ -120,7 +123,7 @@ def archive_images(dir_name, date_to): 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_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)) @@ -133,22 +136,29 @@ def archive_images(dir_name, date_to): date = sort_array[loads_num][2] filenames = [x[1] for x in sort_array] else: - date = None if len(sort_array) == 0 else sort_array[-1][2] + 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] - _, image_list, _, visible_num = get_recent_images(1, 0, filenames) + 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 = f"Loaded {(num + 1) // opts.images_history_pages_num} pades, {num} images, during {date} - {date_to_bak}" + _, image_list, _, _, visible_num = get_recent_images(1, 0, filenames) return ( gradio.Dropdown.update(choices=date_list, value=date_to), - date, + load_info, filenames, 1, image_list, "", - visible_num + "", + visible_num, + last_date_from ) -def newest_click(dir_name, date_to): - return archive_images(dir_name, time.strftime("%Y%m%d",time.localtime(time.time()))) + + def delete_image(delete_num, name, filenames, image_index, visible_num): if name == "": @@ -196,7 +206,29 @@ def get_recent_images(page_index, step, filenames): 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 + return page_index, image_list, "", "", visible_num + +def newest_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) @@ -214,13 +246,33 @@ 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))] - return file, num, file + 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 + else: + return gradio.update(visible=True), gradio.update(visible=False), warning, date_to + def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict): + custom_dir = False if tabname == "txt2img": dir_name = opts.outdir_txt2img_samples elif tabname == "img2img": @@ -229,69 +281,85 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict): dir_name = opts.outdir_extras_samples elif tabname == "saved": dir_name = opts.outdir_save + else: + 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) - 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(visible=False) as turn_page_buttons: - renew_page = gr.Button('Refresh 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.Column(scale=2): - with gr.Row(): - newest = gr.Button('Reload', elem_id=tabname + "_images_history_start") - date_from = gr.Textbox(label="Date from", interactive=False) - date_to = gr.Dropdown(label="Date to") - - 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(): - if tabname != "saved": - save_btn = gr.Button('Save') - 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(value="", label="File Name", interactive=False) + with gr.Column() as page_panel: + with gr.Row(): + img_path = gr.Textbox(dir_name, label="Images directory", placeholder="Input images directory") + 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(): + backward = gr.Button('Backward') + date_to = gr.Dropdown(label="Date to") + forward = gr.Button('Forward') + newest = gr.Button('Reload', elem_id=tabname + "_images_history_start") + with gr.Row(): + load_info = gr.Textbox(show_label=False, interactive=False) + with gr.Row(visible=False) as turn_page_buttons: + renew_page = gr.Button('Refresh 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') + + 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") - # hiden items - with gr.Row(visible=False): - visible_img_num = gr.Number() - img_path = gr.Textbox(dir_name) - 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() + with gr.Column(): + with gr.Row(): + if tabname != "saved": + save_btn = gr.Button('Save') + 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(value="", label="File Name", interactive=False) + img_file_time= gr.Textbox(value="", label="Create Time", interactive=False) - + + # hiden items + with gr.Row(): #visible=False): + 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.submit(change_dir, inputs=[img_path, date_to], outputs=[warning, main_panel, warning_box, date_to]) #change date - change_date_output = [date_to, date_from, filenames, page_index, history_gallery, img_file_name, visible_img_num] - newest.click(newest_click, inputs=[img_path, date_to], outputs=change_date_output) - date_to.change(archive_images, inputs=[img_path, date_to], outputs=change_date_output) - newest.click(fn=None, inputs=[tabname_box], outputs=None, _js="images_history_turnpage") - date_to.change(fn=None, inputs=[tabname_box], outputs=None, _js="images_history_turnpage") - date_to.change(enable_page_buttons, inputs=None, outputs=[turn_page_buttons]) - newest.click(enable_page_buttons, inputs=None, outputs=[turn_page_buttons]) + change_date_output = [date_to, load_info, filenames, page_index, history_gallery, img_file_name, img_file_time, visible_img_num, last_date_from] + + date_to.change(archive_images, inputs=[img_path, date_to], outputs=change_date_output) + date_to.change(enable_page_buttons, inputs=None, outputs=[turn_page_buttons]) + date_to.change(fn=None, inputs=[tabname_box], outputs=None, _js="images_history_turnpage") + + newest.click(newest_click, inputs=[date_to], outputs=[date_to, date_to_recorder]) + forward.click(forward_click, inputs=[last_date_from, date_to_recorder], outputs=[date_to, date_to_recorder]) + backward.click(backward_click, inputs=[last_date_from, date_to_recorder], outputs=[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]) @@ -301,7 +369,7 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict): #turn page gallery_inputs = [page_index, filenames] - gallery_outputs = [page_index, history_gallery, img_file_name, visible_img_num] + 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) @@ -317,12 +385,14 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict): 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, image_index, page_index, filenames], outputs=[img_file_name, image_index, hidden]) + 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]) 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, sys_opts, run_pnginfo, switch_dict): global opts; opts = sys_opts @@ -330,10 +400,11 @@ def create_history_tabs(gr, sys_opts, run_pnginfo, switch_dict): num_of_imgs_per_page = int(opts.images_history_num_per_page * opts.images_history_pages_num) with gr.Blocks(analytics_enabled=False) as images_history: with gr.Tabs() as tabs: - for tab in ["txt2img", "img2img", "extras", "saved"]: + for tab in [browser_tabname, "txt2img", "img2img", "extras", "saved"]: with gr.Tab(tab): - with gr.Blocks(analytics_enabled=False) as images_history_img2img: + with gr.Blocks(analytics_enabled=False) : show_images_history(gr, opts, tab, run_pnginfo, switch_dict) - gradio.Checkbox(opts.images_history_reconstruct_directory, elem_id="images_history_reconstruct_directory", visible=False) + #gradio.Checkbox(opts.images_history_reconstruct_directory, elem_id="images_history_reconstruct_directory", visible=False) + gradio.Checkbox(opts.images_history_reconstruct_directory, elem_id="images_history_finish_render", visible=False) return images_history diff --git a/modules/shared.py b/modules/shared.py index c2ea4186..1811018d 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -309,10 +309,11 @@ 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 history"), { - "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"), +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_num_per_page": OptionInfo(36, "Number of pictures displayed on each page"), - "images_history_pages_num": OptionInfo(6, "Maximum number of pages per load "), + "images_history_pages_num": OptionInfo(6, "Minimum number of pages per load "), + "images_history_grid_num": OptionInfo(6, "Number of grids in each row"), })) diff --git a/modules/ui.py b/modules/ui.py index 43dc88fc..85abac4d 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1548,7 +1548,7 @@ 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"), diff --git a/uitest.bat b/uitest.bat new file mode 100644 index 00000000..ae863af6 --- /dev/null +++ b/uitest.bat @@ -0,0 +1,2 @@ +venv\Scripts\python.exe uitest.py +pause diff --git a/uitest.py b/uitest.py new file mode 100644 index 00000000..393e2d81 --- /dev/null +++ b/uitest.py @@ -0,0 +1,124 @@ +import os +import threading +import time +import importlib +import signal +import threading + +from modules.paths import script_path + +from modules import devices, sd_samplers +import modules.codeformer_model as codeformer +import modules.extras +import modules.face_restoration +import modules.gfpgan_model as gfpgan +import modules.img2img + +import modules.lowvram +import modules.paths +import modules.scripts +import modules.sd_hijack +import modules.sd_models +import modules.shared as shared +import modules.txt2img + +import modules.ui +from modules import devices +from modules import modelloader +from modules.paths import script_path +from modules.shared import cmd_opts + +modelloader.cleanup_models() +modules.sd_models.setup_model() +codeformer.setup_model(cmd_opts.codeformer_models_path) +gfpgan.setup_model(cmd_opts.gfpgan_models_path) +shared.face_restorers.append(modules.face_restoration.FaceRestoration()) +modelloader.load_upscalers() +queue_lock = threading.Lock() + + +def wrap_queued_call(func): + def f(*args, **kwargs): + with queue_lock: + res = func(*args, **kwargs) + + return res + + return f + + +def wrap_gradio_gpu_call(func, extra_outputs=None): + def f(*args, **kwargs): + devices.torch_gc() + + shared.state.sampling_step = 0 + shared.state.job_count = -1 + shared.state.job_no = 0 + shared.state.job_timestamp = shared.state.get_job_timestamp() + shared.state.current_latent = None + shared.state.current_image = None + shared.state.current_image_sampling_step = 0 + shared.state.interrupted = False + shared.state.textinfo = None + + with queue_lock: + res = func(*args, **kwargs) + + shared.state.job = "" + shared.state.job_count = 0 + + devices.torch_gc() + + return res + + return modules.ui.wrap_gradio_call(f, extra_outputs=extra_outputs) + + +modules.scripts.load_scripts(os.path.join(script_path, "scripts")) + +shared.sd_model = None #modules.sd_models.load_model() +#shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights(shared.sd_model))) + + +def webui(): + # make the program just exit at ctrl+c without waiting for anything + def sigint_handler(sig, frame): + print(f'Interrupted with signal {sig} in {frame}') + os._exit(0) + + signal.signal(signal.SIGINT, sigint_handler) + + while 1: + + demo = modules.ui.create_ui(wrap_gradio_gpu_call=wrap_gradio_gpu_call) + + demo.launch( + share=cmd_opts.share, + server_name="0.0.0.0" if cmd_opts.listen else None, + server_port=cmd_opts.port, + debug=cmd_opts.gradio_debug, + auth=[tuple(cred.split(':')) for cred in cmd_opts.gradio_auth.strip('"').split(',')] if cmd_opts.gradio_auth else None, + inbrowser=cmd_opts.autolaunch, + prevent_thread_lock=True + ) + + while 1: + time.sleep(0.5) + if getattr(demo, 'do_restart', False): + time.sleep(0.5) + demo.close() + time.sleep(0.5) + break + + sd_samplers.set_samplers() + + print('Reloading Custom Scripts') + modules.scripts.reload_scripts(os.path.join(script_path, "scripts")) + print('Reloading modules: modules.ui') + importlib.reload(modules.ui) + print('Restarting Gradio') + + + +if __name__ == "__main__": + webui() \ No newline at end of file -- cgit v1.2.3 From 538bc89c269743e56b07ef2b471d1ce0a39b6776 Mon Sep 17 00:00:00 2001 From: yfszzx Date: Wed, 19 Oct 2022 11:27:51 +0800 Subject: Image browser improved --- javascript/images_history.js | 87 ++++++++++++++-------------- modules/images_history.py | 135 ++++++++++++++++++++++++------------------- modules/shared.py | 5 ++ modules/ui.py | 2 +- 4 files changed, 123 insertions(+), 106 deletions(-) (limited to 'modules/shared.py') diff --git a/javascript/images_history.js b/javascript/images_history.js index 182d730b..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_start").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'); @@ -145,57 +137,64 @@ function images_history_enable_del_buttons(){ } function images_history_init(){ - // var loaded = gradioApp().getElementById("images_history_reconstruct_directory") - // if (loaded){ - // var init_status = loaded.querySelector("input").checked - if (gradioApp().getElementById("images_history_finish_render")){ + 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"); + } + + //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() } - 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); - // if (!init_status){ - // tab_btns[i].addEventListener('click', images_history_click_tab); - // } - tab_btns[i].addEventListener('click', images_history_click_tab); - } } else { setTimeout(images_history_init, 500); } } -var images_history_tab_list = ["custom", "txt2img", "img2img", "extras", "saved"]; +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); - }); - - var cls_btn = gradioApp().getElementById(tabname + '_images_history_gallery').querySelector("svg"); - if (cls_btn){ - cls_btn.addEventListener('click', function(){ - gradioApp().getElementById(tabname + '_images_history_del_button').setAttribute('disabled','disabled'); - }, false); - } - - } + 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); + }); + + 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 }); - }); diff --git a/modules/images_history.py b/modules/images_history.py index a40cdc0e..78fd0543 100644 --- a/modules/images_history.py +++ b/modules/images_history.py @@ -4,7 +4,9 @@ import time import hashlib import gradio system_bak_path = "webui_log_and_bak" -browser_tabname = "custom" +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") @@ -122,7 +124,6 @@ def archive_images(dir_name, date_to): else: filenames = traverse_all_files(dir_name, filenames) total_num = len(filenames) - batch_count = len(filenames) + 1 // batch_size + 1 tmparray = [(os.path.getmtime(file), file) for file in filenames ] date_stamp = time.mktime(time.strptime(date_to, "%Y%m%d")) + 86400 filenames = [] @@ -146,10 +147,12 @@ def archive_images(dir_name, date_to): 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 = 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 = "
" + 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 ( - gradio.Dropdown.update(choices=date_list, value=date_to), + date_to, load_info, filenames, 1, @@ -158,7 +161,7 @@ def archive_images(dir_name, date_to): "", visible_num, last_date_from, - #gradio.update(visible=batch_count > 1) + gradio.update(visible=total_num > num) ) def delete_image(delete_num, name, filenames, image_index, visible_num): @@ -209,7 +212,7 @@ def get_recent_images(page_index, step, filenames): visible_num = num_of_imgs_per_page if visible_num == 0 else visible_num return page_index, image_list, "", "", visible_num -def newest_click(date_to): +def loac_batch_click(date_to): if date_to is None: return time.strftime("%Y%m%d",time.localtime(time.time())), [] else: @@ -248,7 +251,7 @@ def page_index_change(page_index, 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))) + tm = "
" + time.strftime("%Y-%m-%d %H:%M:%S",time.localtime(os.path.getmtime(file))) + "
" return file, tm, num, file def enable_page_buttons(): @@ -268,9 +271,9 @@ def change_dir(img_dir, date_to): 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 + 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 + 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): custom_dir = False @@ -280,7 +283,7 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict): dir_name = opts.outdir_img2img_samples elif tabname == "extras": dir_name = opts.outdir_extras_samples - elif tabname == "saved": + elif tabname == faverate_tab_name: dir_name = opts.outdir_save else: custom_dir = True @@ -295,22 +298,26 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict): os.makedirs(dir_name) with gr.Column() as page_panel: - 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(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() as batch_panel: - forward = gr.Button('Forward') - date_to = gr.Dropdown(label="Date to") - backward = gr.Button('Backward') - newest = gr.Button('Reload', elem_id=tabname + "_images_history_start") - with gr.Row(): - load_info = gr.Textbox(show_label=False, interactive=False) - with gr.Row(visible=False) as turn_page_buttons: - renew_page = gr.Button('Refresh page', elem_id=tabname + "_images_history_renew_page") + 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") @@ -322,50 +329,54 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict): 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(): - if tabname != "saved": - save_btn = gr.Button('Save') - pnginfo_send_to_txt2img = gr.Button('Send to txt2img') - pnginfo_send_to_img2img = gr.Button('Send to img2img') + with gr.Column(): with gr.Row(): with gr.Column(): - img_file_info = gr.Textbox(label="Generate Info", interactive=False) + 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.Textbox(value="", label="Create Time", 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): - 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.submit(change_dir, inputs=[img_path, date_to], outputs=[warning, main_panel, warning_box, date_to]) - #change date - change_date_output = [date_to, load_info, filenames, page_index, history_gallery, img_file_name, img_file_time, visible_img_num, last_date_from] + # 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.submit(change_dir, inputs=[img_path, batch_date_to], outputs=[warning, main_panel, warning_box, batch_date_to, load_batch_box, load_info]) + + #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] - date_to.change(archive_images, inputs=[img_path, date_to], outputs=change_date_output) - date_to.change(enable_page_buttons, inputs=None, outputs=[turn_page_buttons]) - date_to.change(fn=None, inputs=[tabname_box], outputs=None, _js="images_history_turnpage") + 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") - newest.click(newest_click, inputs=[date_to], outputs=[date_to, date_to_recorder]) - forward.click(forward_click, inputs=[last_date_from, date_to_recorder], outputs=[date_to, date_to_recorder]) - backward.click(backward_click, inputs=[last_date_from, date_to_recorder], outputs=[date_to, date_to_recorder]) + 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 != "saved": + if tabname != faverate_tab_name: save_btn.click(save_image, inputs=[img_file_name], outputs=None) #turn page @@ -394,18 +405,20 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict): -def create_history_tabs(gr, sys_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: - for tab in [browser_tabname, "txt2img", "img2img", "extras", "saved"]: + 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_reconstruct_directory, elem_id="images_history_reconstruct_directory", visible=False) - gradio.Checkbox(opts.images_history_reconstruct_directory, elem_id="images_history_finish_render", visible=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/shared.py b/modules/shared.py index 1811018d..4d735414 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -74,6 +74,10 @@ parser.add_argument("--disable-console-progressbars", action='store_true', help= parser.add_argument("--enable-console-prompts", action='store_true', help="print prompts to console when generating with txt2img and img2img", default=False) parser.add_argument('--vae-path', type=str, help='Path to Variational Autoencoders model', default=None) parser.add_argument("--disable-safe-unpickle", action='store_true', help="disable checking pytorch models for malicious code", default=False) +parser.add_argument("--browse-all-images", action='store_true', help="Allow browsing all images by Image Browser", default=False) + + +cmd_opts = parser.parse_args() cmd_opts = parser.parse_args() @@ -311,6 +315,7 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters" 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"), diff --git a/modules/ui.py b/modules/ui.py index 85abac4d..88f46659 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1150,7 +1150,7 @@ def create_ui(wrap_gradio_gpu_call): "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): -- cgit v1.2.3 From d07cb46f34b3d9fe7a78b102f899ebef352ea56b Mon Sep 17 00:00:00 2001 From: yfszzx Date: Thu, 20 Oct 2022 23:58:52 +0800 Subject: inspiration pull request --- .gitignore | 3 +- javascript/imageviewer.js | 1 - javascript/inspiration.js | 42 ++++++++++++ modules/inspiration.py | 122 +++++++++++++++++++++++++++++++++++ modules/shared.py | 1 + modules/ui.py | 13 ++-- scripts/create_inspiration_images.py | 45 +++++++++++++ webui.py | 5 ++ 8 files changed, 225 insertions(+), 7 deletions(-) create mode 100644 javascript/inspiration.js create mode 100644 modules/inspiration.py create mode 100644 scripts/create_inspiration_images.py (limited to 'modules/shared.py') diff --git a/.gitignore b/.gitignore index f9c3357c..434d50b7 100644 --- a/.gitignore +++ b/.gitignore @@ -27,4 +27,5 @@ __pycache__ notification.mp3 /SwinIR /textual_inversion -.vscode \ No newline at end of file +.vscode +/inspiration \ No newline at end of file diff --git a/javascript/imageviewer.js b/javascript/imageviewer.js index 9e380c65..d4ab6984 100644 --- a/javascript/imageviewer.js +++ b/javascript/imageviewer.js @@ -116,7 +116,6 @@ function showGalleryImage() { e.dataset.modded = true; if(e && e.parentElement.tagName == 'DIV'){ e.style.cursor='pointer' - e.style.userSelect='none' e.addEventListener('click', function (evt) { if(!opts.js_modal_lightbox) return; modalZoomSet(gradioApp().getElementById('modalImage'), opts.js_modal_lightbox_initially_zoomed) diff --git a/javascript/inspiration.js b/javascript/inspiration.js new file mode 100644 index 00000000..e1c0e114 --- /dev/null +++ b/javascript/inspiration.js @@ -0,0 +1,42 @@ +function public_image_index_in_gallery(item, gallery){ + var index; + var i = 0; + gallery.querySelectorAll("img").forEach(function(e){ + if (e == item) + index = i; + i += 1; + }); + return index; +} + +function inspiration_selected(name, types, name_list){ + var btn = gradioApp().getElementById("inspiration_select_button") + return [gradioApp().getElementById("inspiration_select_button").getAttribute("img-index"), types]; +} +var inspiration_image_click = function(){ + var index = public_image_index_in_gallery(this, gradioApp().getElementById("inspiration_gallery")); + var btn = gradioApp().getElementById("inspiration_select_button") + btn.setAttribute("img-index", index) + setTimeout(function(btn){btn.click();}, 10, btn) +} + +document.addEventListener("DOMContentLoaded", function() { + var mutationObserver = new MutationObserver(function(m){ + var gallery = gradioApp().getElementById("inspiration_gallery") + if (gallery) { + var node = gallery.querySelector(".absolute.backdrop-blur.h-full") + if (node) { + node.style.display = "None"; //parentNode.removeChild(node) + } + + gallery.querySelectorAll('img').forEach(function(e){ + e.onclick = inspiration_image_click + }) + + } + + + }); + mutationObserver.observe( gradioApp(), { childList:true, subtree:true }); + +}); diff --git a/modules/inspiration.py b/modules/inspiration.py new file mode 100644 index 00000000..456bfcb5 --- /dev/null +++ b/modules/inspiration.py @@ -0,0 +1,122 @@ +import os +import random +import gradio +inspiration_path = "inspiration" +inspiration_system_path = os.path.join(inspiration_path, "system") +def read_name_list(file): + if not os.path.exists(file): + return [] + f = open(file, "r") + ret = [] + line = f.readline() + while len(line) > 0: + line = line.rstrip("\n") + ret.append(line) + print(ret) + return ret + +def save_name_list(file, name): + print(file) + f = open(file, "a") + f.write(name + "\n") + +def get_inspiration_images(source, types): + path = os.path.join(inspiration_path , types) + if source == "Favorites": + names = read_name_list(os.path.join(inspiration_system_path, types + "_faverites.txt")) + names = random.sample(names, 25) + elif source == "Abandoned": + names = read_name_list(os.path.join(inspiration_system_path, types + "_abondened.txt")) + names = random.sample(names, 25) + elif source == "Exclude abandoned": + abondened = read_name_list(os.path.join(inspiration_system_path, types + "_abondened.txt")) + all_names = os.listdir(path) + names = [] + while len(names) < 25: + name = random.choice(all_names) + if name not in abondened: + names.append(name) + else: + names = random.sample(os.listdir(path), 25) + names = random.sample(names, 25) + image_list = [] + for a in names: + image_path = os.path.join(path, a) + images = os.listdir(image_path) + image_list.append(os.path.join(image_path, random.choice(images))) + return image_list, names + +def select_click(index, types, name_list): + name = name_list[int(index)] + path = os.path.join(inspiration_path, types, name) + images = os.listdir(path) + return name, [os.path.join(path, x) for x in images] + +def give_up_click(name, types): + file = os.path.join(inspiration_system_path, types + "_abandoned.txt") + name_list = read_name_list(file) + if name not in name_list: + save_name_list(file, name) + +def collect_click(name, types): + file = os.path.join(inspiration_system_path, types + "_faverites.txt") + print(file) + name_list = read_name_list(file) + print(name_list) + if name not in name_list: + save_name_list(file, name) + +def moveout_click(name, types): + file = os.path.join(inspiration_system_path, types + "_faverites.txt") + name_list = read_name_list(file) + if name not in name_list: + save_name_list(file, name) + +def source_change(source): + if source == "Abandoned" or source == "Favorites": + return gradio.Button.update(visible=True, value=f"Move out {source}") + else: + return gradio.Button.update(visible=False) + +def ui(gr, opts): + with gr.Blocks(analytics_enabled=False) as inspiration: + flag = os.path.exists(inspiration_path) + if flag: + types = os.listdir(inspiration_path) + types = [x for x in types if x != "system"] + flag = len(types) > 0 + if not flag: + os.mkdir(inspiration_path) + gr.HTML(""" +
" + """) + return inspiration + if not os.path.exists(inspiration_system_path): + os.mkdir(inspiration_system_path) + gallery, names = get_inspiration_images("Exclude abandoned", types[0]) + with gr.Row(): + with gr.Column(scale=2): + inspiration_gallery = gr.Gallery(gallery, show_label=False, elem_id="inspiration_gallery").style(grid=5, height='auto') + with gr.Column(scale=1): + types = gr.Dropdown(choices=types, value=types[0], label="Type", visible=len(types) > 1) + with gr.Row(): + source = gr.Dropdown(choices=["All", "Favorites", "Exclude abandoned", "Abandoned"], value="Exclude abandoned", label="Source") + get_inspiration = gr.Button("Get inspiration") + name = gr.Textbox(show_label=False, interactive=False) + with gr.Row(): + send_to_txt2img = gr.Button('to txt2img') + send_to_img2img = gr.Button('to img2img') + style_gallery = gr.Gallery(show_label=False, elem_id="inspiration_style_gallery").style(grid=2, height='auto') + + collect = gr.Button('Collect') + give_up = gr.Button("Don't show any more") + moveout = gr.Button("Move out", visible=False) + with gr.Row(): + select_button = gr.Button('set button', elem_id="inspiration_select_button") + name_list = gr.State(names) + source.change(source_change, inputs=[source], outputs=[moveout]) + get_inspiration.click(get_inspiration_images, inputs=[source, types], outputs=[inspiration_gallery, name_list]) + select_button.click(select_click, _js="inspiration_selected", inputs=[name, types, name_list], outputs=[name, style_gallery]) + give_up.click(give_up_click, inputs=[name, types], outputs=None) + collect.click(collect_click, inputs=[name, types], outputs=None) + return inspiration diff --git a/modules/shared.py b/modules/shared.py index faede821..ae033710 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -78,6 +78,7 @@ parser.add_argument('--vae-path', type=str, help='Path to Variational Autoencode parser.add_argument("--disable-safe-unpickle", action='store_true', help="disable checking pytorch models for malicious code", default=False) 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("--ui-debug-mode", action='store_true', help="Don't load model to quickly launch UI") cmd_opts = parser.parse_args() restricted_opts = [ diff --git a/modules/ui.py b/modules/ui.py index a2dbd41e..6a0a3c3b 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -41,7 +41,8 @@ from modules import prompt_parser from modules.images import save_image import modules.textual_inversion.ui import modules.hypernetworks.ui -import modules.images_history as img_his +import modules.images_history as images_history +import modules.inspiration as inspiration # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI mimetypes.init() @@ -1082,9 +1083,9 @@ def create_ui(wrap_gradio_gpu_call): upscaling_resize_w = gr.Number(label="Width", value=512, precision=0) upscaling_resize_h = gr.Number(label="Height", value=512, precision=0) upscaling_crop = gr.Checkbox(label='Crop to fit', value=True) - + with gr.Group(): - extras_upscaler_1 = gr.Radio(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index") + extras_upscaler_1 = gr.Radio(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers] , value=shared.sd_upscalers[0].name, type="index") with gr.Group(): extras_upscaler_2 = gr.Radio(label='Upscaler 2', elem_id="extras_upscaler_2", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index") @@ -1178,7 +1179,8 @@ def create_ui(wrap_gradio_gpu_call): "i2i":img2img_paste_fields } - images_history = img_his.create_history_tabs(gr, opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict) + browser_interface = images_history.create_history_tabs(gr, opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict) + inspiration_interface = inspiration.ui(gr, opts) with gr.Blocks() as modelmerger_interface: with gr.Row().style(equal_height=False): @@ -1595,7 +1597,8 @@ Requested path was: {f} (img2img_interface, "img2img", "img2img"), (extras_interface, "Extras", "extras"), (pnginfo_interface, "PNG Info", "pnginfo"), - (images_history, "History", "images_history"), + (browser_interface, "History", "images_history"), + (inspiration_interface, "Inspiration", "inspiration"), (modelmerger_interface, "Checkpoint Merger", "modelmerger"), (train_interface, "Train", "ti"), (settings_interface, "Settings", "settings"), diff --git a/scripts/create_inspiration_images.py b/scripts/create_inspiration_images.py new file mode 100644 index 00000000..6a20def8 --- /dev/null +++ b/scripts/create_inspiration_images.py @@ -0,0 +1,45 @@ +import csv, os, shutil +import modules.scripts as scripts +from modules import processing, shared, sd_samplers, images +from modules.processing import Processed + + +class Script(scripts.Script): + def title(self): + return "Create artists style image" + + def show(self, is_img2img): + return not is_img2img + + def ui(self, is_img2img): + return [] + def show(self, is_img2img): + return not is_img2img + + def run(self, p): #, max_snapshoots_num): + path = os.path.join("style_snapshoot", "artist") + if not os.path.exists(path): + os.makedirs(path) + p.do_not_save_samples = True + p.do_not_save_grid = True + p.negative_prompt = "portrait photo" + f = open('artists.csv') + f_csv = csv.reader(f) + for row in f_csv: + name = row[0] + artist_path = os.path.join(path, name) + if not os.path.exists(artist_path): + os.mkdir(artist_path) + if len(os.listdir(artist_path)) > 0: + continue + print(name) + p.prompt = name + processed = processing.process_images(p) + for img in processed.images: + i = 0 + filename = os.path.join(artist_path, format(0, "03d") + ".jpg") + while os.path.exists(filename): + i += 1 + filename = os.path.join(artist_path, format(i, "03d") + ".jpg") + img.save(filename, quality=70) + return processed diff --git a/webui.py b/webui.py index 177bef74..5923905f 100644 --- a/webui.py +++ b/webui.py @@ -72,6 +72,11 @@ def wrap_gradio_gpu_call(func, extra_outputs=None): return modules.ui.wrap_gradio_call(f, extra_outputs=extra_outputs) def initialize(): + if cmd_opts.ui_debug_mode: + class enmpty(): + name = None + shared.sd_upscalers = [enmpty()] + return modelloader.cleanup_models() modules.sd_models.setup_model() codeformer.setup_model(cmd_opts.codeformer_models_path) -- cgit v1.2.3 From a3b047b7c74dc6ca07f40aee778997fc1889d72f Mon Sep 17 00:00:00 2001 From: papuSpartan Date: Thu, 20 Oct 2022 19:28:58 -0500 Subject: add settings option to toggle button visibility --- javascript/ui.js | 1 - modules/shared.py | 1 + modules/ui.py | 2 +- 3 files changed, 2 insertions(+), 2 deletions(-) (limited to 'modules/shared.py') diff --git a/javascript/ui.js b/javascript/ui.js index 39eae1f7..f19af550 100644 --- a/javascript/ui.js +++ b/javascript/ui.js @@ -163,7 +163,6 @@ function selected_tab_id() { } function trash_prompt(_,_, is_img2img) { -//txt2img_token_button if(!confirm("Delete prompt?")) return false diff --git a/modules/shared.py b/modules/shared.py index faede821..7e9c2696 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -300,6 +300,7 @@ options_templates.update(options_section(('ui', "User interface"), { "js_modal_lightbox": OptionInfo(True, "Enable full page image viewer"), "js_modal_lightbox_initially_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"), "show_progress_in_title": OptionInfo(True, "Show generation progress in window title."), + "trash_prompt_visible": OptionInfo(True, "Show trash prompt button"), 'quicksettings': OptionInfo("sd_model_checkpoint", "Quicksettings list"), 'localization': OptionInfo("None", "Localization (requires restart)", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)), })) diff --git a/modules/ui.py b/modules/ui.py index bde546cc..13c0b4ca 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -509,7 +509,7 @@ def create_toprow(is_img2img): paste = gr.Button(value=paste_symbol, elem_id="paste") save_style = gr.Button(value=save_style_symbol, elem_id="style_create") prompt_style_apply = gr.Button(value=apply_style_symbol, elem_id="style_apply") - trash_prompt = gr.Button(value=trash_prompt_symbol, elem_id="trash_prompt") + trash_prompt = gr.Button(value=trash_prompt_symbol, elem_id="trash_prompt", visible=opts.trash_prompt_visible) token_counter = gr.HTML(value="", elem_id=f"{id_part}_token_counter") token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button") -- cgit v1.2.3 From 02e4d4694dd9254a6ca9f05c2eb7b01ea508abc7 Mon Sep 17 00:00:00 2001 From: Rcmcpe Date: Fri, 21 Oct 2022 15:53:35 +0800 Subject: Change option description of unload_models_when_training --- modules/shared.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index 5c675b80..41d7f08e 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -266,7 +266,7 @@ options_templates.update(options_section(('system', "System"), { })) options_templates.update(options_section(('training', "Training"), { - "unload_models_when_training": OptionInfo(False, "Unload VAE and CLIP from VRAM when training"), + "unload_models_when_training": OptionInfo(False, "Move VAE and CLIP to RAM when training hypernetwork. Saves VRAM."), "dataset_filename_word_regex": OptionInfo("", "Filename word regex"), "dataset_filename_join_string": OptionInfo(" ", "Filename join string"), "training_image_repeats_per_epoch": OptionInfo(1, "Number of repeats for a single input image per epoch; used only for displaying epoch number", gr.Number, {"precision": 0}), -- cgit v1.2.3 From bb0f1a2cdae3410a41d06ae878f56e29b8154c41 Mon Sep 17 00:00:00 2001 From: yfszzx Date: Sat, 22 Oct 2022 01:23:00 +0800 Subject: inspiration finished --- javascript/inspiration.js | 27 ++++--- modules/inspiration.py | 192 ++++++++++++++++++++++++++++++---------------- modules/shared.py | 6 ++ modules/ui.py | 2 +- webui.py | 3 +- 5 files changed, 151 insertions(+), 79 deletions(-) (limited to 'modules/shared.py') diff --git a/javascript/inspiration.js b/javascript/inspiration.js index e1c0e114..791a80c9 100644 --- a/javascript/inspiration.js +++ b/javascript/inspiration.js @@ -1,25 +1,31 @@ function public_image_index_in_gallery(item, gallery){ + var imgs = gallery.querySelectorAll("img.h-full") var index; var i = 0; - gallery.querySelectorAll("img").forEach(function(e){ + imgs.forEach(function(e){ if (e == item) index = i; i += 1; }); + var num = imgs.length / 2 + index = (index < num) ? index : (index - num) return index; } -function inspiration_selected(name, types, name_list){ +function inspiration_selected(name, name_list){ var btn = gradioApp().getElementById("inspiration_select_button") - return [gradioApp().getElementById("inspiration_select_button").getAttribute("img-index"), types]; -} + return [gradioApp().getElementById("inspiration_select_button").getAttribute("img-index")]; +} +function inspiration_click_get_button(){ + gradioApp().getElementById("inspiration_get_button").click(); +} var inspiration_image_click = function(){ var index = public_image_index_in_gallery(this, gradioApp().getElementById("inspiration_gallery")); - var btn = gradioApp().getElementById("inspiration_select_button") - btn.setAttribute("img-index", index) - setTimeout(function(btn){btn.click();}, 10, btn) + var btn = gradioApp().getElementById("inspiration_select_button"); + btn.setAttribute("img-index", index); + setTimeout(function(btn){btn.click();}, 10, btn); } - + document.addEventListener("DOMContentLoaded", function() { var mutationObserver = new MutationObserver(function(m){ var gallery = gradioApp().getElementById("inspiration_gallery") @@ -27,11 +33,10 @@ document.addEventListener("DOMContentLoaded", function() { var node = gallery.querySelector(".absolute.backdrop-blur.h-full") if (node) { node.style.display = "None"; //parentNode.removeChild(node) - } - + } gallery.querySelectorAll('img').forEach(function(e){ e.onclick = inspiration_image_click - }) + }); } diff --git a/modules/inspiration.py b/modules/inspiration.py index 456bfcb5..f72ebf3a 100644 --- a/modules/inspiration.py +++ b/modules/inspiration.py @@ -1,122 +1,182 @@ import os import random -import gradio -inspiration_path = "inspiration" -inspiration_system_path = os.path.join(inspiration_path, "system") -def read_name_list(file): +import gradio +from modules.shared import opts +inspiration_system_path = os.path.join(opts.inspiration_dir, "system") +def read_name_list(file, types=None, keyword=None): if not os.path.exists(file): return [] - f = open(file, "r") ret = [] + f = open(file, "r") line = f.readline() while len(line) > 0: line = line.rstrip("\n") - ret.append(line) - print(ret) + if types is not None: + dirname = os.path.split(line) + if dirname[0] in types and keyword in dirname[1]: + ret.append(line) + else: + ret.append(line) + line = f.readline() return ret def save_name_list(file, name): - print(file) - f = open(file, "a") - f.write(name + "\n") + with open(file, "a") as f: + f.write(name + "\n") -def get_inspiration_images(source, types): - path = os.path.join(inspiration_path , types) +def get_types_list(): + files = os.listdir(opts.inspiration_dir) + types = [] + for x in files: + path = os.path.join(opts.inspiration_dir, x) + if x[0] == ".": + continue + if not os.path.isdir(path): + continue + if path == inspiration_system_path: + continue + types.append(x) + return types + +def get_inspiration_images(source, types, keyword): + get_num = int(opts.inspiration_rows_num * opts.inspiration_cols_num) if source == "Favorites": - names = read_name_list(os.path.join(inspiration_system_path, types + "_faverites.txt")) - names = random.sample(names, 25) + names = read_name_list(os.path.join(inspiration_system_path, "faverites.txt"), types, keyword) + names = random.sample(names, get_num) if len(names) > get_num else names elif source == "Abandoned": - names = read_name_list(os.path.join(inspiration_system_path, types + "_abondened.txt")) - names = random.sample(names, 25) - elif source == "Exclude abandoned": - abondened = read_name_list(os.path.join(inspiration_system_path, types + "_abondened.txt")) - all_names = os.listdir(path) - names = [] - while len(names) < 25: - name = random.choice(all_names) - if name not in abondened: - names.append(name) + names = read_name_list(os.path.join(inspiration_system_path, "abandoned.txt"), types, keyword) + print(names) + names = random.sample(names, get_num) if len(names) > get_num else names + elif source == "Exclude abandoned": + abandoned = read_name_list(os.path.join(inspiration_system_path, "abandoned.txt"), types, keyword) + all_names = [] + for tp in types: + name_list = os.listdir(os.path.join(opts.inspiration_dir, tp)) + all_names += [os.path.join(tp, x) for x in name_list if keyword in x] + + if len(all_names) > get_num: + names = [] + while len(names) < get_num: + name = random.choice(all_names) + if name not in abandoned: + names.append(name) + else: + names = all_names else: - names = random.sample(os.listdir(path), 25) - names = random.sample(names, 25) + all_names = [] + for tp in types: + name_list = os.listdir(os.path.join(opts.inspiration_dir, tp)) + all_names += [os.path.join(tp, x) for x in name_list if keyword in x] + names = random.sample(all_names, get_num) if len(all_names) > get_num else all_names image_list = [] for a in names: - image_path = os.path.join(path, a) + image_path = os.path.join(opts.inspiration_dir, a) images = os.listdir(image_path) - image_list.append(os.path.join(image_path, random.choice(images))) - return image_list, names + image_list.append((os.path.join(image_path, random.choice(images)), a)) + return image_list, names, "" -def select_click(index, types, name_list): +def select_click(index, name_list): name = name_list[int(index)] - path = os.path.join(inspiration_path, types, name) + path = os.path.join(opts.inspiration_dir, name) images = os.listdir(path) - return name, [os.path.join(path, x) for x in images] + return name, [os.path.join(path, x) for x in images], "" -def give_up_click(name, types): - file = os.path.join(inspiration_system_path, types + "_abandoned.txt") +def give_up_click(name): + file = os.path.join(inspiration_system_path, "abandoned.txt") name_list = read_name_list(file) if name not in name_list: save_name_list(file, name) + return "Added to abandoned list" -def collect_click(name, types): - file = os.path.join(inspiration_system_path, types + "_faverites.txt") - print(file) +def collect_click(name): + file = os.path.join(inspiration_system_path, "faverites.txt") name_list = read_name_list(file) - print(name_list) if name not in name_list: save_name_list(file, name) + return "Added to faverite list" -def moveout_click(name, types): - file = os.path.join(inspiration_system_path, types + "_faverites.txt") +def moveout_click(name, source): + if source == "Abandoned": + file = os.path.join(inspiration_system_path, "abandoned.txt") + if source == "Favorites": + file = os.path.join(inspiration_system_path, "faverites.txt") + else: + return None name_list = read_name_list(file) - if name not in name_list: - save_name_list(file, name) + os.remove(file) + with open(file, "a") as f: + for a in name_list: + if a != name: + f.write(a) + return "Moved out {name} from {source} list" def source_change(source): - if source == "Abandoned" or source == "Favorites": - return gradio.Button.update(visible=True, value=f"Move out {source}") + if source in ["Abandoned", "Favorites"]: + return gradio.update(visible=True), [] else: - return gradio.Button.update(visible=False) + return gradio.update(visible=False), [] +def add_to_prompt(name, prompt): + print(name, prompt) + name = os.path.basename(name) + return prompt + "," + name -def ui(gr, opts): +def ui(gr, opts, txt2img_prompt, img2img_prompt): with gr.Blocks(analytics_enabled=False) as inspiration: - flag = os.path.exists(inspiration_path) + flag = os.path.exists(opts.inspiration_dir) if flag: - types = os.listdir(inspiration_path) - types = [x for x in types if x != "system"] + types = get_types_list() flag = len(types) > 0 - if not flag: - os.mkdir(inspiration_path) + else: + os.makedirs(opts.inspiration_dir) + if not flag: gr.HTML(""" -
" +

To activate inspiration function, you need get "inspiration" images first.


+ You can create these images by run "Create inspiration images" script in txt2img page,
you can get the artists or art styles list from here
+ https://github.com/pharmapsychotic/clip-interrogator/tree/main/data
+ download these files, and select these files in the "Create inspiration images" script UI
+ There about 6000 artists and art styles in these files.
This takes server hours depending on your GPU type and how many pictures you generate for each artist/style +
I suggest at least four images for each


+

You can also download generated pictures from here:


+ https://huggingface.co/datasets/yfszzx/inspiration
+ unzip the file to the project directory of webui
+ and restart webui, and enjoy the joy of creation!
""") return inspiration if not os.path.exists(inspiration_system_path): os.mkdir(inspiration_system_path) - gallery, names = get_inspiration_images("Exclude abandoned", types[0]) with gr.Row(): with gr.Column(scale=2): - inspiration_gallery = gr.Gallery(gallery, show_label=False, elem_id="inspiration_gallery").style(grid=5, height='auto') + inspiration_gallery = gr.Gallery(show_label=False, elem_id="inspiration_gallery").style(grid=opts.inspiration_cols_num, height='auto') with gr.Column(scale=1): - types = gr.Dropdown(choices=types, value=types[0], label="Type", visible=len(types) > 1) + print(types) + types = gr.CheckboxGroup(choices=types, value=types) + keyword = gr.Textbox("", label="Key word") with gr.Row(): source = gr.Dropdown(choices=["All", "Favorites", "Exclude abandoned", "Abandoned"], value="Exclude abandoned", label="Source") - get_inspiration = gr.Button("Get inspiration") + get_inspiration = gr.Button("Get inspiration", elem_id="inspiration_get_button") name = gr.Textbox(show_label=False, interactive=False) with gr.Row(): send_to_txt2img = gr.Button('to txt2img') send_to_img2img = gr.Button('to img2img') - style_gallery = gr.Gallery(show_label=False, elem_id="inspiration_style_gallery").style(grid=2, height='auto') - + style_gallery = gr.Gallery(show_label=False).style(grid=2, height='auto') collect = gr.Button('Collect') - give_up = gr.Button("Don't show any more") + give_up = gr.Button("Don't show again") moveout = gr.Button("Move out", visible=False) - with gr.Row(): + warning = gr.HTML() + with gr.Row(visible=False): select_button = gr.Button('set button', elem_id="inspiration_select_button") - name_list = gr.State(names) - source.change(source_change, inputs=[source], outputs=[moveout]) - get_inspiration.click(get_inspiration_images, inputs=[source, types], outputs=[inspiration_gallery, name_list]) - select_button.click(select_click, _js="inspiration_selected", inputs=[name, types, name_list], outputs=[name, style_gallery]) - give_up.click(give_up_click, inputs=[name, types], outputs=None) - collect.click(collect_click, inputs=[name, types], outputs=None) + name_list = gr.State() + + get_inspiration.click(get_inspiration_images, inputs=[source, types, keyword], outputs=[inspiration_gallery, name_list, keyword]) + source.change(source_change, inputs=[source], outputs=[moveout, style_gallery]) + source.change(fn=None, _js="inspiration_click_get_button", inputs=None, outputs=None) + keyword.submit(fn=None, _js="inspiration_click_get_button", inputs=None, outputs=None) + select_button.click(select_click, _js="inspiration_selected", inputs=[name, name_list], outputs=[name, style_gallery, warning]) + give_up.click(give_up_click, inputs=[name], outputs=[warning]) + collect.click(collect_click, inputs=[name], outputs=[warning]) + moveout.click(moveout_click, inputs=[name, source], outputs=[warning]) + send_to_txt2img.click(add_to_prompt, inputs=[name, txt2img_prompt], outputs=[txt2img_prompt]) + send_to_img2img.click(add_to_prompt, inputs=[name, img2img_prompt], outputs=[img2img_prompt]) + send_to_txt2img.click(None, _js='switch_to_txt2img', inputs=None, outputs=None) + send_to_img2img.click(None, _js="switch_to_img2img_img2img", inputs=None, outputs=None) return inspiration diff --git a/modules/shared.py b/modules/shared.py index ae033710..564b1b8d 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -316,6 +316,12 @@ 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(('inspiration', "Inspiration"), { + "inspiration_dir": OptionInfo("inspiration", "Directory of inspiration", component_args=hide_dirs), + "inspiration_max_samples": OptionInfo(4, "Maximum number of samples, used to determine which folders to skip when continue running the create script", gr.Slider, {"minimum": 1, "maximum": 20, "step": 1}), + "inspiration_rows_num": OptionInfo(4, "Rows of inspiration interface frame", gr.Slider, {"minimum": 4, "maximum": 16, "step": 1}), + "inspiration_cols_num": OptionInfo(8, "Columns of inspiration interface frame", gr.Slider, {"minimum": 4, "maximum": 16, "step": 1}), +})) class Options: data = None diff --git a/modules/ui.py b/modules/ui.py index 6a0a3c3b..b651eb9c 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1180,7 +1180,7 @@ def create_ui(wrap_gradio_gpu_call): } browser_interface = images_history.create_history_tabs(gr, opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict) - inspiration_interface = inspiration.ui(gr, opts) + inspiration_interface = inspiration.ui(gr, opts, txt2img_prompt, img2img_prompt) with gr.Blocks() as modelmerger_interface: with gr.Row().style(equal_height=False): diff --git a/webui.py b/webui.py index 5923905f..5ccae715 100644 --- a/webui.py +++ b/webui.py @@ -72,6 +72,7 @@ def wrap_gradio_gpu_call(func, extra_outputs=None): return modules.ui.wrap_gradio_call(f, extra_outputs=extra_outputs) def initialize(): + modules.scripts.load_scripts(os.path.join(script_path, "scripts")) if cmd_opts.ui_debug_mode: class enmpty(): name = None @@ -84,7 +85,7 @@ def initialize(): shared.face_restorers.append(modules.face_restoration.FaceRestoration()) modelloader.load_upscalers() - modules.scripts.load_scripts(os.path.join(script_path, "scripts")) + shared.sd_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))) -- cgit v1.2.3 From 9e40520f00d836cfa93187f7f1e81e2a7bd100b9 Mon Sep 17 00:00:00 2001 From: papuSpartan Date: Fri, 21 Oct 2022 15:13:12 -0500 Subject: refactor internal terminology to use 'clear' instead of 'trash' like #2728 --- javascript/ui.js | 2 +- modules/shared.py | 2 +- modules/ui.py | 22 +++++++++++----------- 3 files changed, 13 insertions(+), 13 deletions(-) (limited to 'modules/shared.py') diff --git a/javascript/ui.js b/javascript/ui.js index acd57565..45d93a5c 100644 --- a/javascript/ui.js +++ b/javascript/ui.js @@ -162,7 +162,7 @@ function selected_tab_id() { } -function trash_prompt(_, confirmed,_steps) { +function clear_prompt(_, confirmed,_steps) { if(confirm("Delete prompt?")) { confirmed = true diff --git a/modules/shared.py b/modules/shared.py index 1585d532..ab5a0e9a 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -317,7 +317,7 @@ options_templates.update(options_section(('ui', "User interface"), { "js_modal_lightbox": OptionInfo(True, "Enable full page image viewer"), "js_modal_lightbox_initially_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"), "show_progress_in_title": OptionInfo(True, "Show generation progress in window title."), - "trash_prompt_visible": OptionInfo(True, "Show trash prompt button"), + "clear_prompt_visible": OptionInfo(True, "Show clear prompt button"), 'quicksettings': OptionInfo("sd_model_checkpoint", "Quicksettings list"), 'localization': OptionInfo("None", "Localization (requires restart)", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)), })) diff --git a/modules/ui.py b/modules/ui.py index d3a89bf7..31150800 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -88,7 +88,7 @@ folder_symbol = '\U0001f4c2' # 📂 refresh_symbol = '\U0001f504' # 🔄 save_style_symbol = '\U0001f4be' # 💾 apply_style_symbol = '\U0001f4cb' # 📋 -trash_prompt_symbol = '\U0001F5D1' # +clear_prompt_symbol = '\U0001F5D1' # 🗑️ def plaintext_to_html(text): @@ -430,14 +430,14 @@ def create_seed_inputs(): -def connect_trash_prompt(_prompt, confirmed, _token_counter): +def clear_prompt(_prompt, confirmed, _token_counter): if(confirmed): return ["", confirmed, update_token_counter("", 1)] -def trash_prompt_click(button, prompt, _dummy_confirmed, token_counter): +def connect_clear_prompt(button, prompt, _dummy_confirmed, token_counter): button.click( - _js="trash_prompt", - fn=connect_trash_prompt, + _js="clear_prompt", + fn=clear_prompt, inputs=[prompt, _dummy_confirmed, token_counter], outputs=[prompt, _dummy_confirmed, token_counter], ) @@ -518,7 +518,7 @@ def create_toprow(is_img2img): paste = gr.Button(value=paste_symbol, elem_id="paste") save_style = gr.Button(value=save_style_symbol, elem_id="style_create") prompt_style_apply = gr.Button(value=apply_style_symbol, elem_id="style_apply") - trash_prompt = gr.Button(value=trash_prompt_symbol, elem_id="trash_prompt", visible=opts.trash_prompt_visible) + clear_prompt_button = gr.Button(value=clear_prompt_symbol, elem_id="clear_prompt", visible=opts.clear_prompt_visible) token_counter = gr.HTML(value="", elem_id=f"{id_part}_token_counter") token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button") @@ -559,7 +559,7 @@ def create_toprow(is_img2img): prompt_style2 = gr.Dropdown(label="Style 2", elem_id=f"{id_part}_style2_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys()))) prompt_style2.save_to_config = True - return prompt, roll, prompt_style, negative_prompt, prompt_style2, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button, trash_prompt + return prompt, roll, prompt_style, negative_prompt, prompt_style2, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button, clear_prompt_button def setup_progressbar(progressbar, preview, id_part, textinfo=None): @@ -640,7 +640,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Blocks(analytics_enabled=False) as txt2img_interface: txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _,\ txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter,\ - token_button, trash_prompt_button = create_toprow(is_img2img=False) + token_button, clear_prompt_button = create_toprow(is_img2img=False) dummy_component = gr.Label(visible=False) txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="bytes", visible=False) @@ -716,7 +716,7 @@ def create_ui(wrap_gradio_gpu_call): connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False) connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True) - trash_prompt_click(trash_prompt_button, txt2img_prompt, dummy_component, token_counter) + connect_clear_prompt(clear_prompt_button, txt2img_prompt, dummy_component, token_counter) txt2img_args = dict( fn=wrap_gradio_gpu_call(modules.txt2img.txt2img), @@ -853,7 +853,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Blocks(analytics_enabled=False) as img2img_interface: img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit,\ img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste,\ - token_counter, token_button, trash_prompt_button = create_toprow(is_img2img=True) + token_counter, token_button, clear_prompt_button = create_toprow(is_img2img=True) with gr.Row(elem_id='img2img_progress_row'): @@ -954,7 +954,7 @@ def create_ui(wrap_gradio_gpu_call): connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False) connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True) - trash_prompt_click(trash_prompt_button, img2img_prompt, dummy_component, token_counter) + connect_clear_prompt(clear_prompt_button, img2img_prompt, dummy_component, token_counter) img2img_prompt_img.change( fn=modules.images.image_data, -- cgit v1.2.3 From 29bfacd63cb5c73b9643d94f255cca818fd49d9c Mon Sep 17 00:00:00 2001 From: Extraltodeus Date: Sat, 22 Oct 2022 00:12:46 +0200 Subject: implement CUDA device selection, --device-id arg --- modules/shared.py | 1 + 1 file changed, 1 insertion(+) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index 41d7f08e..03032a47 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -80,6 +80,7 @@ parser.add_argument('--vae-path', type=str, help='Path to Variational Autoencode parser.add_argument("--disable-safe-unpickle", action='store_true', help="disable checking pytorch models for malicious code", default=False) 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) cmd_opts = parser.parse_args() restricted_opts = [ -- cgit v1.2.3 From 2b91251637078e04472c91a06a8d9c4db9c1dcf0 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 22 Oct 2022 12:23:45 +0300 Subject: removed aesthetic gradients as built-in added support for extensions --- .gitignore | 2 +- extensions/put extension here.txt | 0 modules/aesthetic_clip.py | 241 -------------------------------------- modules/images_history.py | 2 +- modules/img2img.py | 5 +- modules/processing.py | 35 ++++-- modules/script_callbacks.py | 42 +++++++ modules/scripts.py | 210 ++++++++++++++++++++++++--------- modules/sd_hijack.py | 1 - modules/sd_models.py | 7 +- modules/shared.py | 19 --- modules/txt2img.py | 5 +- modules/ui.py | 83 ++----------- webui.py | 7 +- 14 files changed, 249 insertions(+), 410 deletions(-) create mode 100644 extensions/put extension here.txt delete mode 100644 modules/aesthetic_clip.py create mode 100644 modules/script_callbacks.py (limited to 'modules/shared.py') diff --git a/.gitignore b/.gitignore index f9c3357c..2f1e08ed 100644 --- a/.gitignore +++ b/.gitignore @@ -27,4 +27,4 @@ __pycache__ notification.mp3 /SwinIR /textual_inversion -.vscode \ No newline at end of file +.vscode diff --git a/extensions/put extension here.txt b/extensions/put extension here.txt new file mode 100644 index 00000000..e69de29b 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 78fd0543..bc5cf11f 100644 --- a/modules/images_history.py +++ b/modules/images_history.py @@ -310,7 +310,7 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict): forward = gr.Button('Prev batch') backward = gr.Button('Next batch') with gr.Column(scale=3): - load_info = gr.HTML(visible=not custom_dir) + load_info = gr.HTML(visible=not custom_dir) with gr.Row(visible=False) as warning: warning_box = gr.Textbox("Message", interactive=False) 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..65f25f49 100644 --- a/modules/scripts.py +++ b/modules/scripts.py @@ -1,86 +1,153 @@ 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 list_scripts(scriptdirname, extension): + scripts_list = [] + + 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))) + + 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) + if not os.path.isdir(dirpath): + continue + for filename in sorted(os.listdir(os.path.join(dirpath, scriptdirname))): + scripts_list.append(ScriptFile(dirpath, filename, os.path.join(dirpath, scriptdirname, filename))) -def load_scripts(basedir): - if not os.path.exists(basedir): - return + scripts_list = [x for x in scripts_list if os.path.splitext(x.path)[1].lower() == extension and os.path.isfile(x.path)] - for filename in sorted(os.listdir(basedir)): - path = os.path.join(basedir, filename) + return scripts_list - if os.path.splitext(path)[1].lower() != '.py': - continue - if not os.path.isfile(path): - continue +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 +163,80 @@ 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] + + inputs = [None] + inputs_alwayson = [True] - for script in self.scripts: + 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 +255,7 @@ 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 @@ -176,6 +267,15 @@ class ScriptRunner: return processed + 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): for si, script in list(enumerate(self.scripts)): with open(script.filename, "r", encoding="utf8") as file: @@ -197,19 +297,21 @@ 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() -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 0dbe360d..7d786f07 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") @@ -109,21 +108,6 @@ 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 @@ -415,9 +399,6 @@ 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 70a9cf10..c977482c 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]) @@ -1217,9 +1182,9 @@ 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, cmd_opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict) @@ -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: @@ -1692,9 +1630,12 @@ Requested path was: {f} (images_history, "Image Browser", "images_history"), (modelmerger_interface, "Checkpoint Merger", "modelmerger"), (train_interface, "Train", "ti"), - (settings_interface, "Settings", "settings"), ] + interfaces += script_callbacks.ui_tabs_callback() + + interfaces += [(settings_interface, "Settings", "settings")] + with open(os.path.join(script_path, "style.css"), "r", encoding="utf8") as file: css = file.read() 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') -- cgit v1.2.3 From d37cfffd537cd29309afbcb192c4f979995c6a34 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 22 Oct 2022 19:18:56 +0300 Subject: added callback for creating new settings in extensions --- modules/script_callbacks.py | 11 +++++++++++ modules/shared.py | 19 +++++++++++++++++-- modules/ui.py | 6 +++++- 3 files changed, 33 insertions(+), 3 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/script_callbacks.py b/modules/script_callbacks.py index 866b7acd..1270e50f 100644 --- a/modules/script_callbacks.py +++ b/modules/script_callbacks.py @@ -1,6 +1,7 @@ callbacks_model_loaded = [] callbacks_ui_tabs = [] +callbacks_ui_settings = [] def clear_callbacks(): @@ -22,6 +23,11 @@ def ui_tabs_callback(): return res +def ui_settings_callback(): + for callback in callbacks_ui_settings: + callback() + + 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""" @@ -40,3 +46,8 @@ def on_ui_tabs(callback): """ callbacks_ui_tabs.append(callback) + +def on_ui_settings(callback): + """register a function to be called before UI settingsare populated; add your settings + by using shared.opts.add_option(shared.OptionInfo(...)) """ + callbacks_ui_settings.append(callback) diff --git a/modules/shared.py b/modules/shared.py index 5d83971e..d9cb65ef 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -165,13 +165,13 @@ def realesrgan_models_names(): class OptionInfo: - def __init__(self, default=None, label="", component=None, component_args=None, onchange=None, show_on_main_page=False, refresh=None): + def __init__(self, default=None, label="", component=None, component_args=None, onchange=None, section=None, refresh=None): self.default = default self.label = label self.component = component self.component_args = component_args self.onchange = onchange - self.section = None + self.section = section self.refresh = refresh @@ -327,6 +327,7 @@ options_templates.update(options_section(('images-history', "Images Browser"), { })) + class Options: data = None data_labels = options_templates @@ -389,6 +390,20 @@ class Options: d = {k: self.data.get(k, self.data_labels.get(k).default) for k in self.data_labels.keys()} return json.dumps(d) + def add_option(self, key, info): + self.data_labels[key] = info + + def reorder(self): + """reorder settings so that all items related to section always go together""" + + section_ids = {} + settings_items = self.data_labels.items() + for k, item in settings_items: + if item.section not in section_ids: + section_ids[item.section] = len(section_ids) + + self.data_labels = {k: v for k, v in sorted(settings_items, key=lambda x: section_ids[x[1].section])} + opts = Options() if os.path.exists(config_filename): diff --git a/modules/ui.py b/modules/ui.py index d8d52db1..2849b111 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1461,6 +1461,9 @@ def create_ui(wrap_gradio_gpu_call): components = [] component_dict = {} + script_callbacks.ui_settings_callback() + opts.reorder() + def open_folder(f): if not os.path.exists(f): print(f'Folder "{f}" does not exist. After you create an image, the folder will be created.') @@ -1564,7 +1567,8 @@ Requested path was: {f} previous_section = item.section - gr.HTML(elem_id="settings_header_text_{}".format(item.section[0]), value='

{}

'.format(item.section[1])) + elem_id, text = item.section + gr.HTML(elem_id="settings_header_text_{}".format(elem_id), value='

{}

'.format(text)) if k in quicksettings_names: quicksettings_list.append((i, k, item)) -- cgit v1.2.3 From 4fdb53c1e9962507fc8336dad9a0fabfe6c418c0 Mon Sep 17 00:00:00 2001 From: Unnoen Date: Wed, 19 Oct 2022 21:38:10 +1100 Subject: Generate grid preview for progress image --- modules/sd_samplers.py | 26 +++++++++++++++++++++++++- modules/shared.py | 1 + modules/ui.py | 5 ++++- 3 files changed, 30 insertions(+), 2 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py index f58a29b9..74a480e5 100644 --- a/modules/sd_samplers.py +++ b/modules/sd_samplers.py @@ -7,7 +7,7 @@ import inspect import k_diffusion.sampling import ldm.models.diffusion.ddim import ldm.models.diffusion.plms -from modules import prompt_parser, devices, processing +from modules import prompt_parser, devices, processing, images from modules.shared import opts, cmd_opts, state import modules.shared as shared @@ -89,6 +89,30 @@ def sample_to_image(samples): x_sample = x_sample.astype(np.uint8) return Image.fromarray(x_sample) +def samples_to_image_grid(samples): + progress_images = [] + for i in range(len(samples)): + # Decode the samples individually to reduce VRAM usage at the cost of a bit of speed. + x_sample = processing.decode_first_stage(shared.sd_model, samples[i:i+1])[0] + x_sample = torch.clamp((x_sample + 1.0) / 2.0, min=0.0, max=1.0) + x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2) + x_sample = x_sample.astype(np.uint8) + progress_images.append(Image.fromarray(x_sample)) + + return images.image_grid(progress_images) + +def samples_to_image_grid_combined(samples): + progress_images = [] + # Decode all samples at once to increase speed at the cost of VRAM usage. + x_samples = processing.decode_first_stage(shared.sd_model, samples) + x_samples = torch.clamp((x_samples + 1.0) / 2.0, min=0.0, max=1.0) + + for x_sample in x_samples: + x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2) + x_sample = x_sample.astype(np.uint8) + progress_images.append(Image.fromarray(x_sample)) + + return images.image_grid(progress_images) def store_latent(decoded): state.current_latent = decoded diff --git a/modules/shared.py b/modules/shared.py index d9cb65ef..95d6e225 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -294,6 +294,7 @@ options_templates.update(options_section(('interrogate', "Interrogate Options"), options_templates.update(options_section(('ui', "User interface"), { "show_progressbar": OptionInfo(True, "Show progressbar"), "show_progress_every_n_steps": OptionInfo(0, "Show image creation progress every N sampling steps. Set 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 32, "step": 1}), + "progress_decode_combined": OptionInfo(False, "Decode all progress images at once. (Slighty speeds up progress generation but consumes significantly more VRAM with large batches.)"), "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"), diff --git a/modules/ui.py b/modules/ui.py index 56c233ab..de0abc7e 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -318,7 +318,10 @@ def check_progress_call(id_part): if shared.parallel_processing_allowed: if shared.state.sampling_step - shared.state.current_image_sampling_step >= opts.show_progress_every_n_steps and shared.state.current_latent is not None: - shared.state.current_image = modules.sd_samplers.sample_to_image(shared.state.current_latent) + if opts.progress_decode_combined: + shared.state.current_image = modules.sd_samplers.samples_to_image_grid_combined(shared.state.current_latent) + else: + shared.state.current_image = modules.sd_samplers.samples_to_image_grid(shared.state.current_latent) shared.state.current_image_sampling_step = shared.state.sampling_step image = shared.state.current_image -- cgit v1.2.3 From d213d6ca6f90094cb45c11e2f3cb37d25a8d1f94 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 22 Oct 2022 20:48:13 +0300 Subject: removed the option to use 2x more memory when generating previews added an option to always only show one image in previews removed duplicate code --- modules/sd_samplers.py | 35 ++++++++++------------------------- modules/shared.py | 2 +- modules/ui.py | 6 +++--- 3 files changed, 14 insertions(+), 29 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py index 74a480e5..0b408a70 100644 --- a/modules/sd_samplers.py +++ b/modules/sd_samplers.py @@ -71,6 +71,7 @@ sampler_extra_params = { 'sample_dpm_2': ['s_churn', 's_tmin', 's_tmax', 's_noise'], } + def setup_img2img_steps(p, steps=None): if opts.img2img_fix_steps or steps is not None: steps = int((steps or p.steps) / min(p.denoising_strength, 0.999)) if p.denoising_strength > 0 else 0 @@ -82,37 +83,21 @@ def setup_img2img_steps(p, steps=None): return steps, t_enc -def sample_to_image(samples): - x_sample = processing.decode_first_stage(shared.sd_model, samples[0:1])[0] +def single_sample_to_image(sample): + x_sample = processing.decode_first_stage(shared.sd_model, sample.unsqueeze(0))[0] x_sample = torch.clamp((x_sample + 1.0) / 2.0, min=0.0, max=1.0) x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2) x_sample = x_sample.astype(np.uint8) return Image.fromarray(x_sample) + +def sample_to_image(samples): + return single_sample_to_image(samples[0]) + + def samples_to_image_grid(samples): - progress_images = [] - for i in range(len(samples)): - # Decode the samples individually to reduce VRAM usage at the cost of a bit of speed. - x_sample = processing.decode_first_stage(shared.sd_model, samples[i:i+1])[0] - x_sample = torch.clamp((x_sample + 1.0) / 2.0, min=0.0, max=1.0) - x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2) - x_sample = x_sample.astype(np.uint8) - progress_images.append(Image.fromarray(x_sample)) - - return images.image_grid(progress_images) - -def samples_to_image_grid_combined(samples): - progress_images = [] - # Decode all samples at once to increase speed at the cost of VRAM usage. - x_samples = processing.decode_first_stage(shared.sd_model, samples) - x_samples = torch.clamp((x_samples + 1.0) / 2.0, min=0.0, max=1.0) - - for x_sample in x_samples: - x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2) - x_sample = x_sample.astype(np.uint8) - progress_images.append(Image.fromarray(x_sample)) - - return images.image_grid(progress_images) + return images.image_grid([single_sample_to_image(sample) for sample in samples]) + def store_latent(decoded): state.current_latent = decoded diff --git a/modules/shared.py b/modules/shared.py index 95d6e225..25bfc895 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -294,7 +294,7 @@ options_templates.update(options_section(('interrogate', "Interrogate Options"), options_templates.update(options_section(('ui', "User interface"), { "show_progressbar": OptionInfo(True, "Show progressbar"), "show_progress_every_n_steps": OptionInfo(0, "Show image creation progress every N sampling steps. Set 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 32, "step": 1}), - "progress_decode_combined": OptionInfo(False, "Decode all progress images at once. (Slighty speeds up progress generation but consumes significantly more VRAM with large batches.)"), + "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"), diff --git a/modules/ui.py b/modules/ui.py index de0abc7e..ffa14cac 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -318,10 +318,10 @@ def check_progress_call(id_part): if shared.parallel_processing_allowed: if shared.state.sampling_step - shared.state.current_image_sampling_step >= opts.show_progress_every_n_steps and shared.state.current_latent is not None: - if opts.progress_decode_combined: - shared.state.current_image = modules.sd_samplers.samples_to_image_grid_combined(shared.state.current_latent) - else: + if opts.show_progress_grid: shared.state.current_image = modules.sd_samplers.samples_to_image_grid(shared.state.current_latent) + else: + shared.state.current_image = modules.sd_samplers.sample_to_image(shared.state.current_latent) shared.state.current_image_sampling_step = shared.state.sampling_step image = shared.state.current_image -- cgit v1.2.3 From be748e8b086bd9834d08bdd9160649a5e7700af7 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 22 Oct 2022 22:05:22 +0300 Subject: add --freeze-settings commandline argument to disable changing settings --- modules/shared.py | 1 + modules/ui.py | 11 +++++++++-- 2 files changed, 10 insertions(+), 2 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index 25bfc895..b55371d3 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -64,6 +64,7 @@ parser.add_argument("--port", type=int, help="launch gradio with given server po 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("--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("--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) diff --git a/modules/ui.py b/modules/ui.py index ffa14cac..2311572c 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -580,6 +580,9 @@ def apply_setting(key, value): if value is None: return gr.update() + if shared.cmd_opts.freeze_settings: + return gr.update() + # dont allow model to be swapped when model hash exists in prompt if key == "sd_model_checkpoint" and opts.disable_weights_auto_swap: return gr.update() @@ -1501,6 +1504,8 @@ Requested path was: {f} def run_settings(*args): changed = 0 + assert not shared.cmd_opts.freeze_settings, "changing settings is disabled" + for key, value, comp in zip(opts.data_labels.keys(), args, components): if comp != dummy_component and not opts.same_type(value, opts.data_labels[key].default): return f"Bad value for setting {key}: {value}; expecting {type(opts.data_labels[key].default).__name__}", opts.dumpjson() @@ -1530,6 +1535,8 @@ Requested path was: {f} return f'{changed} settings changed.', opts.dumpjson() def run_settings_single(value, key): + assert not shared.cmd_opts.freeze_settings, "changing settings is disabled" + if not opts.same_type(value, opts.data_labels[key].default): return gr.update(visible=True), opts.dumpjson() @@ -1582,7 +1589,7 @@ Requested path was: {f} elem_id, text = item.section gr.HTML(elem_id="settings_header_text_{}".format(elem_id), value='

{}

'.format(text)) - if k in quicksettings_names: + if k in quicksettings_names and not shared.cmd_opts.freeze_settings: quicksettings_list.append((i, k, item)) components.append(dummy_component) else: @@ -1615,7 +1622,7 @@ Requested path was: {f} def reload_scripts(): modules.scripts.reload_script_body_only() - reload_javascript() # need to refresh the html page + reload_javascript() # need to refresh the html page reload_script_bodies.click( fn=reload_scripts, -- cgit v1.2.3 From 124e44cf1eed1edc68954f63a2a9bc428aabbcec Mon Sep 17 00:00:00 2001 From: yfszzx Date: Mon, 24 Oct 2022 09:51:56 +0800 Subject: remove browser to extension --- .gitignore | 1 - javascript/images_history.js | 200 -------------------- javascript/inspiration.js | 48 ----- modules/images_history.py | 424 ------------------------------------------- modules/inspiration.py | 193 -------------------- modules/script_callbacks.py | 2 - modules/shared.py | 15 -- modules/ui.py | 20 +- 8 files changed, 4 insertions(+), 899 deletions(-) delete mode 100644 javascript/images_history.js delete mode 100644 javascript/inspiration.js delete mode 100644 modules/images_history.py delete mode 100644 modules/inspiration.py (limited to 'modules/shared.py') diff --git a/.gitignore b/.gitignore index 8d01bc6a..70660c51 100644 --- a/.gitignore +++ b/.gitignore @@ -29,5 +29,4 @@ notification.mp3 /textual_inversion .vscode /extensions - /inspiration diff --git a/javascript/images_history.js b/javascript/images_history.js deleted file mode 100644 index c9aa76f8..00000000 --- a/javascript/images_history.js +++ /dev/null @@ -1,200 +0,0 @@ -var images_history_click_image = function(){ - if (!this.classList.contains("transform")){ - var gallery = images_history_get_parent_by_class(this, "images_history_cantainor"); - var buttons = gallery.querySelectorAll(".gallery-item"); - var i = 0; - var hidden_list = []; - buttons.forEach(function(e){ - if (e.style.display == "none"){ - hidden_list.push(i); - } - i += 1; - }) - if (hidden_list.length > 0){ - setTimeout(images_history_hide_buttons, 10, hidden_list, gallery); - } - } - images_history_set_image_info(this); -} - -function images_history_disabled_del(){ - gradioApp().querySelectorAll(".images_history_del_button").forEach(function(btn){ - btn.setAttribute('disabled','disabled'); - }); -} - -function images_history_get_parent_by_class(item, class_name){ - var parent = item.parentElement; - while(!parent.classList.contains(class_name)){ - parent = parent.parentElement; - } - return parent; -} - -function images_history_get_parent_by_tagname(item, tagname){ - var parent = item.parentElement; - tagname = tagname.toUpperCase() - while(parent.tagName != tagname){ - parent = parent.parentElement; - } - return parent; -} - -function images_history_hide_buttons(hidden_list, gallery){ - var buttons = gallery.querySelectorAll(".gallery-item"); - var num = 0; - buttons.forEach(function(e){ - if (e.style.display == "none"){ - num += 1; - } - }); - if (num == hidden_list.length){ - setTimeout(images_history_hide_buttons, 10, hidden_list, gallery); - } - for( i in hidden_list){ - buttons[hidden_list[i]].style.display = "none"; - } -} - -function images_history_set_image_info(button){ - var buttons = images_history_get_parent_by_tagname(button, "DIV").querySelectorAll(".gallery-item"); - var index = -1; - var i = 0; - buttons.forEach(function(e){ - if(e == button){ - index = i; - } - if(e.style.display != "none"){ - i += 1; - } - }); - var gallery = images_history_get_parent_by_class(button, "images_history_cantainor"); - var set_btn = gallery.querySelector(".images_history_set_index"); - var curr_idx = set_btn.getAttribute("img_index", index); - if (curr_idx != index) { - set_btn.setAttribute("img_index", index); - images_history_disabled_del(); - } - set_btn.click(); - -} - -function images_history_get_current_img(tabname, img_index, files){ - return [ - tabname, - gradioApp().getElementById(tabname + '_images_history_set_index').getAttribute("img_index"), - files - ]; -} - -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"); - var buttons = []; - tab.querySelectorAll(".gallery-item").forEach(function(e){ - if (e.style.display != 'none'){ - buttons.push(e); - } - }); - 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(); - }, 30, tabname); - } else { - var next_img - for (var i = 0; i < del_num; i++){ - 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 - 1]; - } else { - btn = buttons[next_img]; - } - setTimeout(function(btn){btn.click()}, 30, btn); - } - images_history_disabled_del(); - -} - -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'; - }) -} - -function images_history_enable_del_buttons(){ - gradioApp().querySelectorAll(".images_history_del_button").forEach(function(btn){ - btn.removeAttribute('disabled'); - }) -} - -function images_history_init(){ - 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 ){ - 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_start").setAttribute("style","padding:20px;font-size:25px"); - } - - //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 = ""; -setTimeout(images_history_init, 500); -document.addEventListener("DOMContentLoaded", function() { - var mutationObserver = new MutationObserver(function(m){ - 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); - }); - - 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 }); -}); - - diff --git a/javascript/inspiration.js b/javascript/inspiration.js deleted file mode 100644 index 39844544..00000000 --- a/javascript/inspiration.js +++ /dev/null @@ -1,48 +0,0 @@ -function public_image_index_in_gallery(item, gallery){ - var imgs = gallery.querySelectorAll("img.h-full") - var index; - var i = 0; - imgs.forEach(function(e){ - if (e == item) - index = i; - i += 1; - }); - var all_imgs = gallery.querySelectorAll("img") - if (all_imgs.length > imgs.length){ - var num = imgs.length / 2 - index = (index < num) ? index : (index - num) - } - return index; -} - -function inspiration_selected(name, name_list){ - var btn = gradioApp().getElementById("inspiration_select_button") - return [gradioApp().getElementById("inspiration_select_button").getAttribute("img-index")]; -} - -function inspiration_click_get_button(){ - gradioApp().getElementById("inspiration_get_button").click(); -} - -var inspiration_image_click = function(){ - var index = public_image_index_in_gallery(this, gradioApp().getElementById("inspiration_gallery")); - var btn = gradioApp().getElementById("inspiration_select_button"); - btn.setAttribute("img-index", index); - setTimeout(function(btn){btn.click();}, 10, btn); -} - -document.addEventListener("DOMContentLoaded", function() { - var mutationObserver = new MutationObserver(function(m){ - var gallery = gradioApp().getElementById("inspiration_gallery") - if (gallery) { - var node = gallery.querySelector(".absolute.backdrop-blur.h-full") - if (node) { - node.style.display = "None"; - } - gallery.querySelectorAll('img').forEach(function(e){ - e.onclick = inspiration_image_click - }); - } - }); - mutationObserver.observe( gradioApp(), { childList:true, subtree:true }); -}); diff --git a/modules/images_history.py b/modules/images_history.py deleted file mode 100644 index bc5cf11f..00000000 --- a/modules/images_history.py +++ /dev/null @@ -1,424 +0,0 @@ -import os -import shutil -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 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 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 = os.path.join(curr_path, file) - if (not all_type) and (file[-4:] == ".txt" or file[-4:] == ".csv"): - pass - elif os.path.isfile(file) and file[-10:].rfind(".") > 0: - image_list.append(file) - else: - 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) - - 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: - 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 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: - 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 {name}") - else: - new_file_list.append(name) - i += 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): - 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: - 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.submit(change_dir, inputs=[img_path, batch_date_to], outputs=[warning, main_panel, warning_box, batch_date_to, load_batch_box, load_info]) - - #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") - - 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, 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]) - 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, 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: - 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/inspiration.py b/modules/inspiration.py deleted file mode 100644 index 29cf8297..00000000 --- a/modules/inspiration.py +++ /dev/null @@ -1,193 +0,0 @@ -import os -import random -import gradio -from modules.shared import opts -inspiration_system_path = os.path.join(opts.inspiration_dir, "system") -def read_name_list(file, types=None, keyword=None): - if not os.path.exists(file): - return [] - ret = [] - f = open(file, "r") - line = f.readline() - while len(line) > 0: - line = line.rstrip("\n") - if types is not None: - dirname = os.path.split(line) - if dirname[0] in types and keyword in dirname[1].lower(): - ret.append(line) - else: - ret.append(line) - line = f.readline() - return ret - -def save_name_list(file, name): - name_list = read_name_list(file) - if name not in name_list: - with open(file, "a") as f: - f.write(name + "\n") - -def get_types_list(): - files = os.listdir(opts.inspiration_dir) - types = [] - for x in files: - path = os.path.join(opts.inspiration_dir, x) - if x[0] == ".": - continue - if not os.path.isdir(path): - continue - if path == inspiration_system_path: - continue - types.append(x) - return types - -def get_inspiration_images(source, types, keyword): - keyword = keyword.strip(" ").lower() - get_num = int(opts.inspiration_rows_num * opts.inspiration_cols_num) - if source == "Favorites": - names = read_name_list(os.path.join(inspiration_system_path, "faverites.txt"), types, keyword) - names = random.sample(names, get_num) if len(names) > get_num else names - elif source == "Abandoned": - names = read_name_list(os.path.join(inspiration_system_path, "abandoned.txt"), types, keyword) - names = random.sample(names, get_num) if len(names) > get_num else names - elif source == "Exclude abandoned": - abandoned = read_name_list(os.path.join(inspiration_system_path, "abandoned.txt"), types, keyword) - all_names = [] - for tp in types: - name_list = os.listdir(os.path.join(opts.inspiration_dir, tp)) - all_names += [os.path.join(tp, x) for x in name_list if keyword in x.lower()] - - if len(all_names) > get_num: - names = [] - while len(names) < get_num: - name = random.choice(all_names) - if name not in abandoned: - names.append(name) - else: - names = all_names - else: - all_names = [] - for tp in types: - name_list = os.listdir(os.path.join(opts.inspiration_dir, tp)) - all_names += [os.path.join(tp, x) for x in name_list if keyword in x.lower()] - names = random.sample(all_names, get_num) if len(all_names) > get_num else all_names - image_list = [] - for a in names: - image_path = os.path.join(opts.inspiration_dir, a) - images = os.listdir(image_path) - if len(images) > 0: - image_list.append((os.path.join(image_path, random.choice(images)), a)) - else: - print(image_path) - return image_list, names - -def select_click(index, name_list): - name = name_list[int(index)] - path = os.path.join(opts.inspiration_dir, name) - images = os.listdir(path) - return name, [os.path.join(path, x) for x in images], "" - -def give_up_click(name): - file = os.path.join(inspiration_system_path, "abandoned.txt") - save_name_list(file, name) - return "Added to abandoned list" - -def collect_click(name): - file = os.path.join(inspiration_system_path, "faverites.txt") - save_name_list(file, name) - return "Added to faverite list" - -def moveout_click(name, source): - if source == "Abandoned": - file = os.path.join(inspiration_system_path, "abandoned.txt") - elif source == "Favorites": - file = os.path.join(inspiration_system_path, "faverites.txt") - else: - return None - name_list = read_name_list(file) - os.remove(file) - with open(file, "a") as f: - for a in name_list: - if a != name: - f.write(a + "\n") - return f"Moved out {name} from {source} list" - -def source_change(source): - if source in ["Abandoned", "Favorites"]: - return gradio.update(visible=True), [] - else: - return gradio.update(visible=False), [] -def add_to_prompt(name, prompt): - name = os.path.basename(name) - return prompt + "," + name - -def clear_keyword(): - return "" - -def ui(gr, opts, txt2img_prompt, img2img_prompt): - with gr.Blocks(analytics_enabled=False) as inspiration: - flag = os.path.exists(opts.inspiration_dir) - if flag: - types = get_types_list() - flag = len(types) > 0 - else: - os.makedirs(opts.inspiration_dir) - if not flag: - gr.HTML(""" -

To activate inspiration function, you need get "inspiration" images first.


- You can create these images by run "Create inspiration images" script in txt2img page,
you can get the artists or art styles list from here
- https://github.com/pharmapsychotic/clip-interrogator/tree/main/data
- download these files, and select these files in the "Create inspiration images" script UI
- There about 6000 artists and art styles in these files.
This takes server hours depending on your GPU type and how many pictures you generate for each artist/style -
I suggest at least four images for each


-

You can also download generated pictures from here:


- https://huggingface.co/datasets/yfszzx/inspiration
- unzip the file to the project directory of webui
- and restart webui, and enjoy the joy of creation!
- """) - return inspiration - if not os.path.exists(inspiration_system_path): - os.mkdir(inspiration_system_path) - with gr.Row(): - with gr.Column(scale=2): - inspiration_gallery = gr.Gallery(show_label=False, elem_id="inspiration_gallery").style(grid=opts.inspiration_cols_num, height='auto') - with gr.Column(scale=1): - types = gr.CheckboxGroup(choices=types, value=types) - with gr.Row(): - source = gr.Dropdown(choices=["All", "Favorites", "Exclude abandoned", "Abandoned"], value="Exclude abandoned", label="Source") - keyword = gr.Textbox("", label="Key word") - get_inspiration = gr.Button("Get inspiration", elem_id="inspiration_get_button") - name = gr.Textbox(show_label=False, interactive=False) - with gr.Row(): - send_to_txt2img = gr.Button('to txt2img') - send_to_img2img = gr.Button('to img2img') - collect = gr.Button('Collect') - give_up = gr.Button("Don't show again") - moveout = gr.Button("Move out", visible=False) - warning = gr.HTML() - style_gallery = gr.Gallery(show_label=False).style(grid=2, height='auto') - - - - with gr.Row(visible=False): - select_button = gr.Button('set button', elem_id="inspiration_select_button") - name_list = gr.State() - - get_inspiration.click(get_inspiration_images, inputs=[source, types, keyword], outputs=[inspiration_gallery, name_list]) - keyword.submit(fn=None, _js="inspiration_click_get_button", inputs=None, outputs=None) - source.change(source_change, inputs=[source], outputs=[moveout, style_gallery]) - source.change(fn=clear_keyword, _js="inspiration_click_get_button", inputs=None, outputs=[keyword]) - types.change(fn=clear_keyword, _js="inspiration_click_get_button", inputs=None, outputs=[keyword]) - - select_button.click(select_click, _js="inspiration_selected", inputs=[name, name_list], outputs=[name, style_gallery, warning]) - give_up.click(give_up_click, inputs=[name], outputs=[warning]) - collect.click(collect_click, inputs=[name], outputs=[warning]) - moveout.click(moveout_click, inputs=[name, source], outputs=[warning]) - moveout.click(fn=None, _js="inspiration_click_get_button", inputs=None, outputs=None) - - send_to_txt2img.click(add_to_prompt, inputs=[name, txt2img_prompt], outputs=[txt2img_prompt]) - send_to_img2img.click(add_to_prompt, inputs=[name, img2img_prompt], outputs=[img2img_prompt]) - send_to_txt2img.click(collect_click, inputs=[name], outputs=[warning]) - send_to_img2img.click(collect_click, inputs=[name], outputs=[warning]) - send_to_txt2img.click(None, _js='switch_to_txt2img', inputs=None, outputs=None) - send_to_img2img.click(None, _js="switch_to_img2img_img2img", inputs=None, outputs=None) - return inspiration diff --git a/modules/script_callbacks.py b/modules/script_callbacks.py index 5bcccd67..66666a56 100644 --- a/modules/script_callbacks.py +++ b/modules/script_callbacks.py @@ -1,4 +1,3 @@ - callbacks_model_loaded = [] callbacks_ui_tabs = [] callbacks_ui_settings = [] @@ -16,7 +15,6 @@ def model_loaded_callback(sd_model): def ui_tabs_callback(): res = [] - for callback in callbacks_ui_tabs: res += callback() or [] diff --git a/modules/shared.py b/modules/shared.py index 0aaaadac..5dfd7927 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -321,21 +321,6 @@ 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(('inspiration', "Inspiration"), { - "inspiration_dir": OptionInfo("inspiration", "Directory of inspiration", component_args=hide_dirs), - "inspiration_max_samples": OptionInfo(4, "Maximum number of samples, used to determine which folders to skip when continue running the create script", gr.Slider, {"minimum": 1, "maximum": 20, "step": 1}), - "inspiration_rows_num": OptionInfo(4, "Rows of inspiration interface frame", gr.Slider, {"minimum": 4, "maximum": 16, "step": 1}), - "inspiration_cols_num": OptionInfo(8, "Columns of inspiration interface frame", gr.Slider, {"minimum": 4, "maximum": 16, "step": 1}), -})) - -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 diff --git a/modules/ui.py b/modules/ui.py index a73175f5..fa42712e 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -49,14 +49,12 @@ from modules.sd_hijack import model_hijack from modules.sd_samplers import samplers, samplers_for_img2img import modules.textual_inversion.ui import modules.hypernetworks.ui -import modules.images_history as images_history -import modules.inspiration as inspiration - - # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI mimetypes.init() mimetypes.add_type('application/javascript', '.js') +txt2img_paste_fields = [] +img2img_paste_fields = [] if not cmd_opts.share and not cmd_opts.listen: @@ -1193,16 +1191,7 @@ def create_ui(wrap_gradio_gpu_call): inputs=[image], outputs=[html, generation_info, html2], ) - #images history - images_history_switch_dict = { - "fn": modules.generation_parameters_copypaste.connect_paste, - "t2i": txt2img_paste_fields, - "i2i": img2img_paste_fields - } - - browser_interface = images_history.create_history_tabs(gr, opts, cmd_opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict) - inspiration_interface = inspiration.ui(gr, opts, txt2img_prompt, img2img_prompt) - + with gr.Blocks() as modelmerger_interface: with gr.Row().style(equal_height=False): with gr.Column(variant='panel'): @@ -1651,8 +1640,6 @@ Requested path was: {f} (img2img_interface, "img2img", "img2img"), (extras_interface, "Extras", "extras"), (pnginfo_interface, "PNG Info", "pnginfo"), - (inspiration_interface, "Inspiration", "inspiration"), - (browser_interface , "Image Browser", "images_history"), (modelmerger_interface, "Checkpoint Merger", "modelmerger"), (train_interface, "Train", "ti"), ] @@ -1896,6 +1883,7 @@ def load_javascript(raw_response): javascript = f'' scripts_list = modules.scripts.list_scripts("javascript", ".js") + scripts_list += modules.scripts.list_scripts("scripts", ".js") for basedir, filename, path in scripts_list: with open(path, "r", encoding="utf8") as jsfile: javascript += f"\n" -- cgit v1.2.3 From cef1b89aa2e6c7647db7e93a4cd4ec020da3f2da Mon Sep 17 00:00:00 2001 From: yfszzx Date: Mon, 24 Oct 2022 10:10:33 +0800 Subject: remove browser to extension --- modules/script_callbacks.py | 2 ++ modules/shared.py | 1 - modules/ui.py | 2 +- scripts/create_inspiration_images.py | 57 ------------------------------------ 4 files changed, 3 insertions(+), 59 deletions(-) delete mode 100644 scripts/create_inspiration_images.py (limited to 'modules/shared.py') diff --git a/modules/script_callbacks.py b/modules/script_callbacks.py index 66666a56..f46d3d9a 100644 --- a/modules/script_callbacks.py +++ b/modules/script_callbacks.py @@ -1,3 +1,4 @@ + callbacks_model_loaded = [] callbacks_ui_tabs = [] callbacks_ui_settings = [] @@ -15,6 +16,7 @@ def model_loaded_callback(sd_model): def ui_tabs_callback(): res = [] + for callback in callbacks_ui_tabs: res += callback() or [] diff --git a/modules/shared.py b/modules/shared.py index 5dfd7927..6541e679 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -82,7 +82,6 @@ parser.add_argument("--api", action='store_true', help="use api=True to launch t parser.add_argument("--nowebui", action='store_true', help="use api=True to launch the api instead of the webui") parser.add_argument("--ui-debug-mode", action='store_true', help="Don't load model to quickly launch UI") 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 = [ diff --git a/modules/ui.py b/modules/ui.py index fa42712e..a32f7259 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1104,7 +1104,7 @@ def create_ui(wrap_gradio_gpu_call): upscaling_crop = gr.Checkbox(label='Crop to fit', value=True) with gr.Group(): - extras_upscaler_1 = gr.Radio(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers] , value=shared.sd_upscalers[0].name, type="index") + extras_upscaler_1 = gr.Radio(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index") with gr.Group(): extras_upscaler_2 = gr.Radio(label='Upscaler 2', elem_id="extras_upscaler_2", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index") diff --git a/scripts/create_inspiration_images.py b/scripts/create_inspiration_images.py deleted file mode 100644 index 2fd30578..00000000 --- a/scripts/create_inspiration_images.py +++ /dev/null @@ -1,57 +0,0 @@ -import csv, os, shutil -import modules.scripts as scripts -from modules import processing, shared, sd_samplers, images -from modules.processing import Processed -from modules.shared import opts -import gradio -class Script(scripts.Script): - def title(self): - return "Create inspiration images" - - def show(self, is_img2img): - return True - - def ui(self, is_img2img): - file = gradio.Files(label="Artist or styles name list. '.txt' files with one name per line",) - with gradio.Row(): - prefix = gradio.Textbox("a painting in", label="Prompt words before artist or style name", file_count="multiple") - suffix= gradio.Textbox("style", label="Prompt words after artist or style name") - negative_prompt = gradio.Textbox("picture frame, portrait photo", label="Negative Prompt") - with gradio.Row(): - batch_size = gradio.Number(1, label="Batch size") - batch_count = gradio.Number(2, label="Batch count") - return [batch_size, batch_count, prefix, suffix, negative_prompt, file] - - def run(self, p, batch_size, batch_count, prefix, suffix, negative_prompt, files): - p.batch_size = int(batch_size) - p.n_iterint = int(batch_count) - p.negative_prompt = negative_prompt - p.do_not_save_samples = True - p.do_not_save_grid = True - for file in files: - tp = file.orig_name.split(".")[0] - print(tp) - path = os.path.join(opts.inspiration_dir, tp) - if not os.path.exists(path): - os.makedirs(path) - f = open(file.name, "r") - line = f.readline() - while len(line) > 0: - name = line.rstrip("\n").split(",")[0] - line = f.readline() - artist_path = os.path.join(path, name) - if not os.path.exists(artist_path): - os.mkdir(artist_path) - if len(os.listdir(artist_path)) >= opts.inspiration_max_samples: - continue - p.prompt = f"{prefix} {name} {suffix}" - print(p.prompt) - processed = processing.process_images(p) - for img in processed.images: - i = 0 - filename = os.path.join(artist_path, format(0, "03d") + ".jpg") - while os.path.exists(filename): - i += 1 - filename = os.path.join(artist_path, format(i, "03d") + ".jpg") - img.save(filename, quality=80) - return processed -- cgit v1.2.3 From 3be6b29d81408d2adb741bff5b11c80214aa621e Mon Sep 17 00:00:00 2001 From: w-e-w <40751091+w-e-w@users.noreply.github.com> Date: Mon, 24 Oct 2022 15:14:34 +0900 Subject: indent=4 config.json --- modules/shared.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index 6541e679..d6ddfe59 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -348,7 +348,7 @@ class Options: def save(self, filename): with open(filename, "w", encoding="utf8") as file: - json.dump(self.data, file) + json.dump(self.data, file, indent=4) def same_type(self, x, y): if x is None or y is None: -- cgit v1.2.3 From 8da1bd48bf9d0411cd9ba87b8d9220743cb5807e Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Mon, 24 Oct 2022 14:03:58 +0300 Subject: add an option to skip adding number to filenames when saving. rework filename pattern function go through the pattern once and not calculate any of replacements until they are actually encountered in the pattern. --- modules/images.py | 250 ++++++++++++++++++++++++++++-------------------------- modules/shared.py | 8 +- 2 files changed, 135 insertions(+), 123 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/images.py b/modules/images.py index a9b1330d..848ede75 100644 --- a/modules/images.py +++ b/modules/images.py @@ -1,4 +1,7 @@ import datetime +import sys +import traceback + import pytz import io import math @@ -274,10 +277,15 @@ invalid_filename_chars = '<>:"/\\|?*\n' invalid_filename_prefix = ' ' invalid_filename_postfix = ' .' re_nonletters = re.compile(r'[\s' + string.punctuation + ']+') +re_pattern = re.compile(r"([^\[\]]+|\[([^]]+)]|[\[\]]*)") +re_pattern_arg = re.compile(r"(.*)<([^>]*)>$") max_filename_part_length = 128 def sanitize_filename_part(text, replace_spaces=True): + if text is None: + return None + if replace_spaces: text = text.replace(' ', '_') @@ -287,49 +295,103 @@ def sanitize_filename_part(text, replace_spaces=True): return text -def apply_filename_pattern(x, p, seed, prompt): - max_prompt_words = opts.directories_max_prompt_words - - if seed is not None: - x = re.sub(r'\[seed]', str(seed), x, flags=re.IGNORECASE) - - if p is not None: - x = re.sub(r'\[steps]', str(p.steps), x, flags=re.IGNORECASE) - x = re.sub(r'\[cfg]', str(p.cfg_scale), x, flags=re.IGNORECASE) - x = re.sub(r'\[width]', str(p.width), x, flags=re.IGNORECASE) - x = re.sub(r'\[height]', str(p.height), x, flags=re.IGNORECASE) - x = re.sub(r'\[styles]', sanitize_filename_part(", ".join([x for x in p.styles if not x == "None"]) or "None", replace_spaces=False), x, flags=re.IGNORECASE) - x = re.sub(r'\[sampler]', sanitize_filename_part(sd_samplers.samplers[p.sampler_index].name, replace_spaces=False), x, flags=re.IGNORECASE) - - x = re.sub(r'\[model_hash]', getattr(p, "sd_model_hash", shared.sd_model.sd_model_hash), x, flags=re.IGNORECASE) - current_time = datetime.datetime.now() - x = re.sub(r'\[date]', current_time.strftime('%Y-%m-%d'), x, flags=re.IGNORECASE) - x = replace_datetime(x, current_time) # replace [datetime], [datetime], [datetime