diff options
32 files changed, 358 insertions, 122 deletions
diff --git a/extensions-builtin/Lora/extra_networks_lora.py b/extensions-builtin/Lora/extra_networks_lora.py index 6be6ef73..45f899fc 100644 --- a/extensions-builtin/Lora/extra_networks_lora.py +++ b/extensions-builtin/Lora/extra_networks_lora.py @@ -8,7 +8,7 @@ class ExtraNetworkLora(extra_networks.ExtraNetwork): def activate(self, p, params_list):
additional = shared.opts.sd_lora
- if additional != "" and additional in lora.available_loras and len([x for x in params_list if x.items[0] == additional]) == 0:
+ if additional != "None" and additional in lora.available_loras and len([x for x in params_list if x.items[0] == additional]) == 0:
p.all_prompts = [x + f"<lora:{additional}:{shared.opts.extra_networks_default_multiplier}>" for x in p.all_prompts]
params_list.append(extra_networks.ExtraNetworkParams(items=[additional, shared.opts.extra_networks_default_multiplier]))
diff --git a/extensions-builtin/Lora/scripts/lora_script.py b/extensions-builtin/Lora/scripts/lora_script.py index 0adab225..3fc38ab9 100644 --- a/extensions-builtin/Lora/scripts/lora_script.py +++ b/extensions-builtin/Lora/scripts/lora_script.py @@ -52,5 +52,5 @@ script_callbacks.on_before_ui(before_ui) shared.options_templates.update(shared.options_section(('extra_networks', "Extra Networks"), {
- "sd_lora": shared.OptionInfo("None", "Add Lora to prompt", gr.Dropdown, lambda: {"choices": [""] + [x for x in lora.available_loras]}, refresh=lora.list_available_loras),
+ "sd_lora": shared.OptionInfo("None", "Add Lora to prompt", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in lora.available_loras]}, refresh=lora.list_available_loras),
}))
diff --git a/javascript/edit-attention.js b/javascript/edit-attention.js index 20a5aadf..588c7b77 100644 --- a/javascript/edit-attention.js +++ b/javascript/edit-attention.js @@ -17,7 +17,7 @@ function keyupEditAttention(event){ // Find opening parenthesis around current cursor
const before = text.substring(0, selectionStart);
let beforeParen = before.lastIndexOf(OPEN);
- if (beforeParen == -1) return false;
+ if (beforeParen == -1) return false;
let beforeParenClose = before.lastIndexOf(CLOSE);
while (beforeParenClose !== -1 && beforeParenClose > beforeParen) {
beforeParen = before.lastIndexOf(OPEN, beforeParen - 1);
@@ -27,7 +27,7 @@ function keyupEditAttention(event){ // Find closing parenthesis around current cursor
const after = text.substring(selectionStart);
let afterParen = after.indexOf(CLOSE);
- if (afterParen == -1) return false;
+ if (afterParen == -1) return false;
let afterParenOpen = after.indexOf(OPEN);
while (afterParenOpen !== -1 && afterParen > afterParenOpen) {
afterParen = after.indexOf(CLOSE, afterParen + 1);
@@ -43,10 +43,28 @@ function keyupEditAttention(event){ target.setSelectionRange(selectionStart, selectionEnd);
return true;
}
+
+ function selectCurrentWord(){
+ if (selectionStart !== selectionEnd) return false;
+ const delimiters = opts.keyedit_delimiters + " \r\n\t";
+
+ // seek backward until to find beggining
+ while (!delimiters.includes(text[selectionStart - 1]) && selectionStart > 0) {
+ selectionStart--;
+ }
+
+ // seek forward to find end
+ while (!delimiters.includes(text[selectionEnd]) && selectionEnd < text.length) {
+ selectionEnd++;
+ }
- // If the user hasn't selected anything, let's select their current parenthesis block
- if(! selectCurrentParenthesisBlock('<', '>')){
- selectCurrentParenthesisBlock('(', ')')
+ target.setSelectionRange(selectionStart, selectionEnd);
+ return true;
+ }
+
+ // If the user hasn't selected anything, let's select their current parenthesis block or word
+ if (!selectCurrentParenthesisBlock('<', '>') && !selectCurrentParenthesisBlock('(', ')')) {
+ selectCurrentWord();
}
event.preventDefault();
@@ -81,7 +99,13 @@ function keyupEditAttention(event){ weight = parseFloat(weight.toPrecision(12));
if(String(weight).length == 1) weight += ".0"
- text = text.slice(0, selectionEnd + 1) + weight + text.slice(selectionEnd + 1 + end - 1);
+ if (closeCharacter == ')' && weight == 1) {
+ text = text.slice(0, selectionStart - 1) + text.slice(selectionStart, selectionEnd) + text.slice(selectionEnd + 5);
+ selectionStart--;
+ selectionEnd--;
+ } else {
+ text = text.slice(0, selectionEnd + 1) + weight + text.slice(selectionEnd + 1 + end - 1);
+ }
target.focus();
target.value = text;
@@ -93,4 +117,4 @@ function keyupEditAttention(event){ addEventListener('keydown', (event) => {
keyupEditAttention(event);
-});
\ No newline at end of file +});
diff --git a/javascript/extensions.js b/javascript/extensions.js index c593cd2e..72924a28 100644 --- a/javascript/extensions.js +++ b/javascript/extensions.js @@ -1,5 +1,5 @@ -function extensions_apply(_, _){
+function extensions_apply(_, _, disable_all){
var disable = []
var update = []
@@ -13,10 +13,10 @@ function extensions_apply(_, _){ restart_reload()
- return [JSON.stringify(disable), JSON.stringify(update)]
+ return [JSON.stringify(disable), JSON.stringify(update), disable_all]
}
-function extensions_check(){
+function extensions_check(_, _){
var disable = []
gradioApp().querySelectorAll('#extensions input[type="checkbox"]').forEach(function(x){
diff --git a/javascript/progressbar.js b/javascript/progressbar.js index 4ac9b8db..8df3f569 100644 --- a/javascript/progressbar.js +++ b/javascript/progressbar.js @@ -138,7 +138,7 @@ function requestProgress(id_task, progressbarContainer, gallery, atEnd, onProgre return } - if(elapsedFromStart > 5 && !res.queued && !res.active){ + if(elapsedFromStart > 40 && !res.queued && !res.active){ removeProgressBar() return } @@ -206,6 +206,10 @@ def list_extensions(settings_file): print(e, file=sys.stderr)
disabled_extensions = set(settings.get('disabled_extensions', []))
+ disable_all_extensions = settings.get('disable_all_extensions', 'none')
+
+ if disable_all_extensions != 'none':
+ return []
return [x for x in os.listdir(extensions_dir) if x not in disabled_extensions]
@@ -235,7 +239,7 @@ def prepare_environment(): codeformer_repo = os.environ.get('CODEFORMER_REPO', 'https://github.com/sczhou/CodeFormer.git')
blip_repo = os.environ.get('BLIP_REPO', 'https://github.com/salesforce/BLIP.git')
- stable_diffusion_commit_hash = os.environ.get('STABLE_DIFFUSION_COMMIT_HASH', "47b6b607fdd31875c9279cd2f4f16b92e4ea958e")
+ stable_diffusion_commit_hash = os.environ.get('STABLE_DIFFUSION_COMMIT_HASH', "cf1d67a6fd5ea1aa600c4df58e5b47da45f6bdbf")
taming_transformers_commit_hash = os.environ.get('TAMING_TRANSFORMERS_COMMIT_HASH', "24268930bf1dce879235a7fddd0b2355b84d7ea6")
k_diffusion_commit_hash = os.environ.get('K_DIFFUSION_COMMIT_HASH', "5b3af030dd83e0297272d861c19477735d0317ec")
codeformer_commit_hash = os.environ.get('CODEFORMER_COMMIT_HASH', "c5b4593074ba6214284d6acd5f1719b6c5d739af")
diff --git a/models/karlo/ViT-L-14_stats.th b/models/karlo/ViT-L-14_stats.th Binary files differnew file mode 100644 index 00000000..a6a06e94 --- /dev/null +++ b/models/karlo/ViT-L-14_stats.th diff --git a/modules/api/api.py b/modules/api/api.py index 518b2a61..5ed670e9 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -6,7 +6,6 @@ import uvicorn import gradio as gr from threading import Lock from io import BytesIO -from gradio.processing_utils import decode_base64_to_file from fastapi import APIRouter, Depends, FastAPI, Request, Response from fastapi.security import HTTPBasic, HTTPBasicCredentials from fastapi.exceptions import HTTPException @@ -395,16 +394,11 @@ class Api: def extras_batch_images_api(self, req: ExtrasBatchImagesRequest): reqDict = setUpscalers(req) - def prepareFiles(file): - file = decode_base64_to_file(file.data, file_path=file.name) - file.orig_name = file.name - return file - - reqDict['image_folder'] = list(map(prepareFiles, reqDict['imageList'])) - reqDict.pop('imageList') + image_list = reqDict.pop('imageList', []) + image_folder = [decode_base64_to_image(x.data) for x in image_list] with self.queue_lock: - result = postprocessing.run_extras(extras_mode=1, image="", input_dir="", output_dir="", save_output=False, **reqDict) + result = postprocessing.run_extras(extras_mode=1, image_folder=image_folder, image="", input_dir="", output_dir="", save_output=False, **reqDict) return ExtrasBatchImagesResponse(images=list(map(encode_pil_to_base64, result[0])), html_info=result[1]) diff --git a/modules/extensions.py b/modules/extensions.py index 0d34b89a..3a7a0372 100644 --- a/modules/extensions.py +++ b/modules/extensions.py @@ -15,7 +15,12 @@ if not os.path.exists(extensions_dir): def active():
- return [x for x in extensions if x.enabled]
+ if shared.opts.disable_all_extensions == "all":
+ return []
+ elif shared.opts.disable_all_extensions == "extra":
+ return [x for x in extensions if x.enabled and x.is_builtin]
+ else:
+ return [x for x in extensions if x.enabled]
class Extension:
@@ -97,6 +102,11 @@ def list_extensions(): if not os.path.isdir(extensions_dir):
return
+ if shared.opts.disable_all_extensions == "all":
+ print("*** \"Disable all extensions\" option was set, will not load any extensions ***")
+ elif shared.opts.disable_all_extensions == "extra":
+ print("*** \"Disable all extensions\" option was set, will only load built-in extensions ***")
+
extension_paths = []
for dirname in [extensions_dir, extensions_builtin_dir]:
if not os.path.isdir(dirname):
@@ -112,4 +122,3 @@ def list_extensions(): for dirname, path, is_builtin in extension_paths:
extension = Extension(name=dirname, path=path, enabled=dirname not in shared.opts.disabled_extensions, is_builtin=is_builtin)
extensions.append(extension)
-
diff --git a/modules/extra_networks_hypernet.py b/modules/extra_networks_hypernet.py index d3a4d7ad..33d100dd 100644 --- a/modules/extra_networks_hypernet.py +++ b/modules/extra_networks_hypernet.py @@ -9,7 +9,7 @@ class ExtraNetworkHypernet(extra_networks.ExtraNetwork): def activate(self, p, params_list):
additional = shared.opts.sd_hypernetwork
- if additional != "" and additional in shared.hypernetworks and len([x for x in params_list if x.items[0] == additional]) == 0:
+ if additional != "None" and additional in shared.hypernetworks and len([x for x in params_list if x.items[0] == additional]) == 0:
p.all_prompts = [x + f"<hypernet:{additional}:{shared.opts.extra_networks_default_multiplier}>" for x in p.all_prompts]
params_list.append(extra_networks.ExtraNetworkParams(items=[additional, shared.opts.extra_networks_default_multiplier]))
diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index f6ef42d5..1fc49537 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -312,7 +312,7 @@ class Hypernetwork: def list_hypernetworks(path):
res = {}
- for filename in sorted(glob.iglob(os.path.join(path, '**/*.pt'), recursive=True)):
+ for filename in sorted(glob.iglob(os.path.join(path, '**/*.pt'), recursive=True), key=str.lower):
name = os.path.splitext(os.path.basename(filename))[0]
# Prevent a hypothetical "None.pt" from being listed.
if name != "None":
diff --git a/modules/images.py b/modules/images.py index b3535070..1a118a69 100644 --- a/modules/images.py +++ b/modules/images.py @@ -352,6 +352,7 @@ class FilenameGenerator: 'prompt_no_styles': lambda self: self.prompt_no_style(),
'prompt_spaces': lambda self: sanitize_filename_part(self.prompt, replace_spaces=False),
'prompt_words': lambda self: self.prompt_words(),
+ 'clip_skip': lambda self: opts.data["CLIP_stop_at_last_layers"],
}
default_time_format = '%Y%m%d%H%M%S'
diff --git a/modules/img2img.py b/modules/img2img.py index c973b770..d22d9a49 100644 --- a/modules/img2img.py +++ b/modules/img2img.py @@ -151,13 +151,14 @@ def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_s override_settings=override_settings,
)
- p.scripts = modules.scripts.scripts_txt2img
+ p.scripts = modules.scripts.scripts_img2img
p.script_args = args
if shared.cmd_opts.enable_console_prompts:
print(f"\nimg2img: {prompt}", file=shared.progress_print_out)
- p.extra_generation_params["Mask blur"] = mask_blur
+ if mask:
+ p.extra_generation_params["Mask blur"] = mask_blur
if is_batch:
assert not shared.cmd_opts.hide_ui_dir_config, "Launched with --hide-ui-dir-config, batch img2img disabled"
diff --git a/modules/interrogate.py b/modules/interrogate.py index cbb80683..e1665708 100644 --- a/modules/interrogate.py +++ b/modules/interrogate.py @@ -32,7 +32,7 @@ def download_default_clip_interrogate_categories(content_dir): category_types = ["artists", "flavors", "mediums", "movements"]
try:
- os.makedirs(tmpdir)
+ os.makedirs(tmpdir, exist_ok=True)
for category_type in category_types:
torch.hub.download_url_to_file(f"https://raw.githubusercontent.com/pharmapsychotic/clip-interrogator/main/clip_interrogator/data/{category_type}.txt", os.path.join(tmpdir, f"{category_type}.txt"))
os.rename(tmpdir, content_dir)
@@ -41,7 +41,7 @@ def download_default_clip_interrogate_categories(content_dir): errors.display(e, "downloading default CLIP interrogate categories")
finally:
if os.path.exists(tmpdir):
- os.remove(tmpdir)
+ os.removedirs(tmpdir)
class InterrogateModels:
diff --git a/modules/lowvram.py b/modules/lowvram.py index 042a0254..e254cc13 100644 --- a/modules/lowvram.py +++ b/modules/lowvram.py @@ -55,12 +55,12 @@ def setup_for_low_vram(sd_model, use_medvram): if hasattr(sd_model.cond_stage_model, 'model'):
sd_model.cond_stage_model.transformer = sd_model.cond_stage_model.model
- # remove four big modules, cond, first_stage, depth (if applicable), and unet from the model and then
+ # remove several big modules: cond, first_stage, depth/embedder (if applicable), and unet from the model and then
# send the model to GPU. Then put modules back. the modules will be in CPU.
- stored = sd_model.cond_stage_model.transformer, sd_model.first_stage_model, getattr(sd_model, 'depth_model', None), sd_model.model
- sd_model.cond_stage_model.transformer, sd_model.first_stage_model, sd_model.depth_model, sd_model.model = None, None, None, None
+ stored = sd_model.cond_stage_model.transformer, sd_model.first_stage_model, getattr(sd_model, 'depth_model', None), getattr(sd_model, 'embedder', None), sd_model.model
+ sd_model.cond_stage_model.transformer, sd_model.first_stage_model, sd_model.depth_model, sd_model.embedder, sd_model.model = None, None, None, None, None
sd_model.to(devices.device)
- sd_model.cond_stage_model.transformer, sd_model.first_stage_model, sd_model.depth_model, sd_model.model = stored
+ sd_model.cond_stage_model.transformer, sd_model.first_stage_model, sd_model.depth_model, sd_model.embedder, sd_model.model = stored
# register hooks for those the first three models
sd_model.cond_stage_model.transformer.register_forward_pre_hook(send_me_to_gpu)
@@ -69,6 +69,8 @@ def setup_for_low_vram(sd_model, use_medvram): sd_model.first_stage_model.decode = first_stage_model_decode_wrap
if sd_model.depth_model:
sd_model.depth_model.register_forward_pre_hook(send_me_to_gpu)
+ if sd_model.embedder:
+ sd_model.embedder.register_forward_pre_hook(send_me_to_gpu)
parents[sd_model.cond_stage_model.transformer] = sd_model.cond_stage_model
if hasattr(sd_model.cond_stage_model, 'model'):
diff --git a/modules/postprocessing.py b/modules/postprocessing.py index 09d8e605..4dc1a2ab 100644 --- a/modules/postprocessing.py +++ b/modules/postprocessing.py @@ -18,9 +18,15 @@ def run_postprocessing(extras_mode, image, image_folder, input_dir, output_dir, if extras_mode == 1:
for img in image_folder:
- image = Image.open(img)
+ if isinstance(img, Image.Image):
+ image = img
+ fn = ''
+ else:
+ image = Image.open(os.path.abspath(img.name))
+ fn = os.path.splitext(img.orig_name)[0]
+
image_data.append(image)
- image_names.append(os.path.splitext(img.orig_name)[0])
+ image_names.append(fn)
elif extras_mode == 2:
assert not shared.cmd_opts.hide_ui_dir_config, '--hide-ui-dir-config option must be disabled'
assert input_dir, 'input directory not selected'
diff --git a/modules/processing.py b/modules/processing.py index 2e5a363f..5556afc5 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -3,6 +3,7 @@ import math import os
import sys
import warnings
+import hashlib
import torch
import numpy as np
@@ -78,21 +79,27 @@ def apply_overlay(image, paste_loc, index, overlays): def txt2img_image_conditioning(sd_model, x, width, height):
- if sd_model.model.conditioning_key not in {'hybrid', 'concat'}:
- # Dummy zero conditioning if we're not using inpainting model.
- # Still takes up a bit of memory, but no encoder call.
- # Pretty sure we can just make this a 1x1 image since its not going to be used besides its batch size.
- return x.new_zeros(x.shape[0], 5, 1, 1, dtype=x.dtype, device=x.device)
+ if sd_model.model.conditioning_key in {'hybrid', 'concat'}: # Inpainting models
+
+ # The "masked-image" in this case will just be all zeros since the entire image is masked.
+ image_conditioning = torch.zeros(x.shape[0], 3, height, width, device=x.device)
+ image_conditioning = sd_model.get_first_stage_encoding(sd_model.encode_first_stage(image_conditioning))
- # The "masked-image" in this case will just be all zeros since the entire image is masked.
- image_conditioning = torch.zeros(x.shape[0], 3, height, width, device=x.device)
- image_conditioning = sd_model.get_first_stage_encoding(sd_model.encode_first_stage(image_conditioning))
+ # Add the fake full 1s mask to the first dimension.
+ image_conditioning = torch.nn.functional.pad(image_conditioning, (0, 0, 0, 0, 1, 0), value=1.0)
+ image_conditioning = image_conditioning.to(x.dtype)
- # Add the fake full 1s mask to the first dimension.
- image_conditioning = torch.nn.functional.pad(image_conditioning, (0, 0, 0, 0, 1, 0), value=1.0)
- image_conditioning = image_conditioning.to(x.dtype)
+ return image_conditioning
- return image_conditioning
+ elif sd_model.model.conditioning_key == "crossattn-adm": # UnCLIP models
+
+ return x.new_zeros(x.shape[0], 2*sd_model.noise_augmentor.time_embed.dim, dtype=x.dtype, device=x.device)
+
+ else:
+ # Dummy zero conditioning if we're not using inpainting or unclip models.
+ # Still takes up a bit of memory, but no encoder call.
+ # Pretty sure we can just make this a 1x1 image since its not going to be used besides its batch size.
+ return x.new_zeros(x.shape[0], 5, 1, 1, dtype=x.dtype, device=x.device)
class StableDiffusionProcessing:
@@ -190,6 +197,14 @@ class StableDiffusionProcessing: return conditioning_image
+ def unclip_image_conditioning(self, source_image):
+ c_adm = self.sd_model.embedder(source_image)
+ if self.sd_model.noise_augmentor is not None:
+ noise_level = 0 # TODO: Allow other noise levels?
+ c_adm, noise_level_emb = self.sd_model.noise_augmentor(c_adm, noise_level=repeat(torch.tensor([noise_level]).to(c_adm.device), '1 -> b', b=c_adm.shape[0]))
+ c_adm = torch.cat((c_adm, noise_level_emb), 1)
+ return c_adm
+
def inpainting_image_conditioning(self, source_image, latent_image, image_mask=None):
self.is_using_inpainting_conditioning = True
@@ -241,6 +256,9 @@ class StableDiffusionProcessing: if self.sampler.conditioning_key in {'hybrid', 'concat'}:
return self.inpainting_image_conditioning(source_image, latent_image, image_mask=image_mask)
+ if self.sampler.conditioning_key == "crossattn-adm":
+ return self.unclip_image_conditioning(source_image)
+
# Dummy zero conditioning if we're not using inpainting or depth model.
return latent_image.new_zeros(latent_image.shape[0], 5, 1, 1)
@@ -459,6 +477,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter "Conditional mask weight": getattr(p, "inpainting_mask_weight", shared.opts.inpainting_mask_weight) if p.is_using_inpainting_conditioning else None,
"Clip skip": None if clip_skip <= 1 else clip_skip,
"ENSD": None if opts.eta_noise_seed_delta == 0 else opts.eta_noise_seed_delta,
+ "Init image hash": getattr(p, 'init_img_hash', None)
}
generation_params.update(p.extra_generation_params)
@@ -990,6 +1009,12 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): self.color_corrections = []
imgs = []
for img in self.init_images:
+
+ # Save init image
+ if opts.save_init_img:
+ self.init_img_hash = hashlib.md5(img.tobytes()).hexdigest()
+ images.save_image(img, path=opts.outdir_init_images, basename=None, forced_filename=self.init_img_hash, save_to_dirs=False)
+
image = images.flatten(img, opts.img2img_background_color)
if crop_region is None and self.resize_mode != 3:
diff --git a/modules/sd_models.py b/modules/sd_models.py index 86218c08..6ea874df 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -122,7 +122,7 @@ def list_models(): elif cmd_ckpt is not None and cmd_ckpt != shared.default_sd_model_file:
print(f"Checkpoint in --ckpt argument not found (Possible it was moved to {model_path}: {cmd_ckpt}", file=sys.stderr)
- for filename in model_list:
+ for filename in sorted(model_list, key=str.lower):
checkpoint_info = CheckpointInfo(filename)
checkpoint_info.register()
@@ -383,6 +383,14 @@ def repair_config(sd_config): elif shared.cmd_opts.upcast_sampling:
sd_config.model.params.unet_config.params.use_fp16 = True
+ if getattr(sd_config.model.params.first_stage_config.params.ddconfig, "attn_type", None) == "vanilla-xformers" and not shared.xformers_available:
+ sd_config.model.params.first_stage_config.params.ddconfig.attn_type = "vanilla"
+
+ # For UnCLIP-L, override the hardcoded karlo directory
+ if hasattr(sd_config.model.params, "noise_aug_config") and hasattr(sd_config.model.params.noise_aug_config.params, "clip_stats_path"):
+ karlo_path = os.path.join(paths.models_path, 'karlo')
+ sd_config.model.params.noise_aug_config.params.clip_stats_path = sd_config.model.params.noise_aug_config.params.clip_stats_path.replace("checkpoints/karlo_models", karlo_path)
+
sd1_clip_weight = 'cond_stage_model.transformer.text_model.embeddings.token_embedding.weight'
sd2_clip_weight = 'cond_stage_model.model.transformer.resblocks.0.attn.in_proj_weight'
diff --git a/modules/sd_models_config.py b/modules/sd_models_config.py index 91c21700..9398f528 100644 --- a/modules/sd_models_config.py +++ b/modules/sd_models_config.py @@ -14,6 +14,8 @@ config_sd2 = os.path.join(sd_repo_configs_path, "v2-inference.yaml") config_sd2v = os.path.join(sd_repo_configs_path, "v2-inference-v.yaml")
config_sd2_inpainting = os.path.join(sd_repo_configs_path, "v2-inpainting-inference.yaml")
config_depth_model = os.path.join(sd_repo_configs_path, "v2-midas-inference.yaml")
+config_unclip = os.path.join(sd_repo_configs_path, "v2-1-stable-unclip-l-inference.yaml")
+config_unopenclip = os.path.join(sd_repo_configs_path, "v2-1-stable-unclip-h-inference.yaml")
config_inpainting = os.path.join(sd_configs_path, "v1-inpainting-inference.yaml")
config_instruct_pix2pix = os.path.join(sd_configs_path, "instruct-pix2pix.yaml")
config_alt_diffusion = os.path.join(sd_configs_path, "alt-diffusion-inference.yaml")
@@ -65,9 +67,14 @@ def is_using_v_parameterization_for_sd2(state_dict): def guess_model_config_from_state_dict(sd, filename):
sd2_cond_proj_weight = sd.get('cond_stage_model.model.transformer.resblocks.0.attn.in_proj_weight', None)
diffusion_model_input = sd.get('model.diffusion_model.input_blocks.0.0.weight', None)
+ sd2_variations_weight = sd.get('embedder.model.ln_final.weight', None)
if sd.get('depth_model.model.pretrained.act_postprocess3.0.project.0.bias', None) is not None:
return config_depth_model
+ elif sd2_variations_weight is not None and sd2_variations_weight.shape[0] == 768:
+ return config_unclip
+ elif sd2_variations_weight is not None and sd2_variations_weight.shape[0] == 1024:
+ return config_unopenclip
if sd2_cond_proj_weight is not None and sd2_cond_proj_weight.shape[1] == 1024:
if diffusion_model_input.shape[1] == 9:
diff --git a/modules/sd_samplers_compvis.py b/modules/sd_samplers_compvis.py index 083da18c..bfcc5574 100644 --- a/modules/sd_samplers_compvis.py +++ b/modules/sd_samplers_compvis.py @@ -70,8 +70,13 @@ class VanillaStableDiffusionSampler: # Have to unwrap the inpainting conditioning here to perform pre-processing
image_conditioning = None
+ uc_image_conditioning = None
if isinstance(cond, dict):
- image_conditioning = cond["c_concat"][0]
+ if self.conditioning_key == "crossattn-adm":
+ image_conditioning = cond["c_adm"]
+ uc_image_conditioning = unconditional_conditioning["c_adm"]
+ else:
+ image_conditioning = cond["c_concat"][0]
cond = cond["c_crossattn"][0]
unconditional_conditioning = unconditional_conditioning["c_crossattn"][0]
@@ -98,8 +103,12 @@ class VanillaStableDiffusionSampler: # Wrap the image conditioning back up since the DDIM code can accept the dict directly.
# Note that they need to be lists because it just concatenates them later.
if image_conditioning is not None:
- cond = {"c_concat": [image_conditioning], "c_crossattn": [cond]}
- unconditional_conditioning = {"c_concat": [image_conditioning], "c_crossattn": [unconditional_conditioning]}
+ if self.conditioning_key == "crossattn-adm":
+ cond = {"c_adm": image_conditioning, "c_crossattn": [cond]}
+ unconditional_conditioning = {"c_adm": uc_image_conditioning, "c_crossattn": [unconditional_conditioning]}
+ else:
+ cond = {"c_concat": [image_conditioning], "c_crossattn": [cond]}
+ unconditional_conditioning = {"c_concat": [image_conditioning], "c_crossattn": [unconditional_conditioning]}
return x, ts, cond, unconditional_conditioning
@@ -176,8 +185,12 @@ class VanillaStableDiffusionSampler: # Wrap the conditioning models with additional image conditioning for inpainting model
if image_conditioning is not None:
- conditioning = {"c_concat": [image_conditioning], "c_crossattn": [conditioning]}
- unconditional_conditioning = {"c_concat": [image_conditioning], "c_crossattn": [unconditional_conditioning]}
+ if self.conditioning_key == "crossattn-adm":
+ conditioning = {"c_adm": image_conditioning, "c_crossattn": [conditioning]}
+ unconditional_conditioning = {"c_adm": torch.zeros_like(image_conditioning), "c_crossattn": [unconditional_conditioning]}
+ else:
+ conditioning = {"c_concat": [image_conditioning], "c_crossattn": [conditioning]}
+ unconditional_conditioning = {"c_concat": [image_conditioning], "c_crossattn": [unconditional_conditioning]}
samples = self.launch_sampling(t_enc + 1, lambda: self.sampler.decode(x1, conditioning, t_enc, unconditional_guidance_scale=p.cfg_scale, unconditional_conditioning=unconditional_conditioning))
@@ -195,8 +208,12 @@ class VanillaStableDiffusionSampler: # Wrap the conditioning models with additional image conditioning for inpainting model
# dummy_for_plms is needed because PLMS code checks the first item in the dict to have the right shape
if image_conditioning is not None:
- conditioning = {"dummy_for_plms": np.zeros((conditioning.shape[0],)), "c_crossattn": [conditioning], "c_concat": [image_conditioning]}
- unconditional_conditioning = {"c_crossattn": [unconditional_conditioning], "c_concat": [image_conditioning]}
+ if self.conditioning_key == "crossattn-adm":
+ conditioning = {"dummy_for_plms": np.zeros((conditioning.shape[0],)), "c_crossattn": [conditioning], "c_adm": image_conditioning}
+ unconditional_conditioning = {"c_crossattn": [unconditional_conditioning], "c_adm": torch.zeros_like(image_conditioning)}
+ else:
+ conditioning = {"dummy_for_plms": np.zeros((conditioning.shape[0],)), "c_crossattn": [conditioning], "c_concat": [image_conditioning]}
+ unconditional_conditioning = {"c_crossattn": [unconditional_conditioning], "c_concat": [image_conditioning]}
samples_ddim = self.launch_sampling(steps, lambda: self.sampler.sample(S=steps, conditioning=conditioning, batch_size=int(x.shape[0]), shape=x[0].shape, verbose=False, unconditional_guidance_scale=p.cfg_scale, unconditional_conditioning=unconditional_conditioning, x_T=x, eta=self.eta)[0])
diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index 93f0e55a..e9f08518 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -92,14 +92,21 @@ class CFGDenoiser(torch.nn.Module): batch_size = len(conds_list)
repeats = [len(conds_list[i]) for i in range(batch_size)]
+ if shared.sd_model.model.conditioning_key == "crossattn-adm":
+ image_uncond = torch.zeros_like(image_cond)
+ make_condition_dict = lambda c_crossattn, c_adm: {"c_crossattn": c_crossattn, "c_adm": c_adm}
+ else:
+ image_uncond = image_cond
+ make_condition_dict = lambda c_crossattn, c_concat: {"c_crossattn": c_crossattn, "c_concat": [c_concat]}
+
if not is_edit_model:
x_in = torch.cat([torch.stack([x[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [x])
sigma_in = torch.cat([torch.stack([sigma[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [sigma])
- image_cond_in = torch.cat([torch.stack([image_cond[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [image_cond])
+ image_cond_in = torch.cat([torch.stack([image_cond[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [image_uncond])
else:
x_in = torch.cat([torch.stack([x[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [x] + [x])
sigma_in = torch.cat([torch.stack([sigma[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [sigma] + [sigma])
- image_cond_in = torch.cat([torch.stack([image_cond[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [image_cond] + [torch.zeros_like(self.init_latent)])
+ image_cond_in = torch.cat([torch.stack([image_cond[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [image_uncond] + [torch.zeros_like(self.init_latent)])
denoiser_params = CFGDenoiserParams(x_in, image_cond_in, sigma_in, state.sampling_step, state.sampling_steps, tensor, uncond)
cfg_denoiser_callback(denoiser_params)
@@ -116,13 +123,13 @@ class CFGDenoiser(torch.nn.Module): cond_in = torch.cat([tensor, uncond, uncond])
if shared.batch_cond_uncond:
- x_out = self.inner_model(x_in, sigma_in, cond={"c_crossattn": [cond_in], "c_concat": [image_cond_in]})
+ x_out = self.inner_model(x_in, sigma_in, cond=make_condition_dict([cond_in], image_cond_in))
else:
x_out = torch.zeros_like(x_in)
for batch_offset in range(0, x_out.shape[0], batch_size):
a = batch_offset
b = a + batch_size
- x_out[a:b] = self.inner_model(x_in[a:b], sigma_in[a:b], cond={"c_crossattn": [cond_in[a:b]], "c_concat": [image_cond_in[a:b]]})
+ x_out[a:b] = self.inner_model(x_in[a:b], sigma_in[a:b], cond=make_condition_dict([cond_in[a:b]], image_cond_in[a:b]))
else:
x_out = torch.zeros_like(x_in)
batch_size = batch_size*2 if shared.batch_cond_uncond else batch_size
@@ -135,9 +142,9 @@ class CFGDenoiser(torch.nn.Module): else:
c_crossattn = torch.cat([tensor[a:b]], uncond)
- x_out[a:b] = self.inner_model(x_in[a:b], sigma_in[a:b], cond={"c_crossattn": c_crossattn, "c_concat": [image_cond_in[a:b]]})
+ x_out[a:b] = self.inner_model(x_in[a:b], sigma_in[a:b], cond=make_condition_dict(c_crossattn, image_cond_in[a:b]))
- x_out[-uncond.shape[0]:] = self.inner_model(x_in[-uncond.shape[0]:], sigma_in[-uncond.shape[0]:], cond={"c_crossattn": [uncond], "c_concat": [image_cond_in[-uncond.shape[0]:]]})
+ x_out[-uncond.shape[0]:] = self.inner_model(x_in[-uncond.shape[0]:], sigma_in[-uncond.shape[0]:], cond=make_condition_dict([uncond], image_cond_in[-uncond.shape[0]:]))
denoised_params = CFGDenoisedParams(x_out, state.sampling_step, state.sampling_steps)
cfg_denoised_callback(denoised_params)
diff --git a/modules/shared.py b/modules/shared.py index 3ad0862b..725f58d1 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -39,6 +39,7 @@ restricted_opts = { "outdir_grids",
"outdir_txt2img_grids",
"outdir_save",
+ "outdir_init_images"
}
ui_reorder_categories = [
@@ -253,6 +254,7 @@ options_templates.update(options_section(('saving-images', "Saving images/grids" "use_upscaler_name_as_suffix": OptionInfo(False, "Use upscaler name as filename suffix in the extras tab"),
"save_selected_only": OptionInfo(True, "When using 'Save' button, only save a single selected image"),
"do_not_add_watermark": OptionInfo(False, "Do not add watermark to images"),
+ "save_init_img": OptionInfo(False, "Save init images when using img2img"),
"temp_dir": OptionInfo("", "Directory for temporary images; leave empty for default"),
"clean_temp_dir_at_start": OptionInfo(False, "Cleanup non-default temporary directory when starting webui"),
@@ -268,6 +270,7 @@ options_templates.update(options_section(('saving-paths', "Paths for saving"), { "outdir_txt2img_grids": OptionInfo("outputs/txt2img-grids", 'Output directory for txt2img grids', component_args=hide_dirs),
"outdir_img2img_grids": OptionInfo("outputs/img2img-grids", 'Output directory for img2img grids', component_args=hide_dirs),
"outdir_save": OptionInfo("log/images", "Directory for saving images using the Save button", component_args=hide_dirs),
+ "outdir_init_images": OptionInfo("outputs/init-images", "Directory for saving init images when using img2img", component_args=hide_dirs),
}))
options_templates.update(options_section(('saving-to-dirs', "Saving to a directory"), {
@@ -361,7 +364,7 @@ options_templates.update(options_section(('extra_networks', "Extra Networks"), { "extra_networks_card_width": OptionInfo(0, "Card width for Extra Networks (px)"),
"extra_networks_card_height": OptionInfo(0, "Card height for Extra Networks (px)"),
"extra_networks_add_text_separator": OptionInfo(" ", "Extra text to add before <...> when adding extra network to prompt"),
- "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": [""] + [x for x in hypernetworks.keys()]}, refresh=reload_hypernetworks),
+ "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}, refresh=reload_hypernetworks),
}))
options_templates.update(options_section(('ui', "User interface"), {
@@ -382,6 +385,7 @@ options_templates.update(options_section(('ui', "User interface"), { "dimensions_and_batch_together": OptionInfo(True, "Show Width/Height and Batch sliders in same row"),
"keyedit_precision_attention": OptionInfo(0.1, "Ctrl+up/down precision when editing (attention:1.1)", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}),
"keyedit_precision_extra": OptionInfo(0.05, "Ctrl+up/down precision when editing <extra networks:0.9>", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}),
+ "keyedit_delimiters": OptionInfo(".,\/!?%^*;:{}=`~()", "Ctrl+up/down word delimiters"),
"quicksettings": OptionInfo("sd_model_checkpoint", "Quicksettings list"),
"hidden_tabs": OptionInfo([], "Hidden UI tabs (requires restart)", ui_components.DropdownMulti, lambda: {"choices": [x for x in tab_names]}),
"ui_reorder": OptionInfo(", ".join(ui_reorder_categories), "txt2img/img2img UI item order"),
@@ -422,7 +426,8 @@ options_templates.update(options_section(('postprocessing', "Postprocessing"), { }))
options_templates.update(options_section((None, "Hidden options"), {
- "disabled_extensions": OptionInfo([], "Disable those extensions"),
+ "disabled_extensions": OptionInfo([], "Disable these extensions"),
+ "disable_all_extensions": OptionInfo("none", "Disable all extensions (preserves the list of disabled extensions)", gr.Radio, {"choices": ["none", "extra", "all"]}),
"sd_checkpoint_hash": OptionInfo("", "SHA256 hash of the current checkpoint"),
}))
diff --git a/modules/ui.py b/modules/ui.py index af8546c2..dd28bdbb 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -70,17 +70,6 @@ def gr_show(visible=True): sample_img2img = "assets/stable-samples/img2img/sketch-mountains-input.jpg"
sample_img2img = sample_img2img if os.path.exists(sample_img2img) else None
-css_hide_progressbar = """
-.wrap .m-12 svg { display:none!important; }
-.wrap .m-12::before { content:"Loading..." }
-.wrap .z-20 svg { display:none!important; }
-.wrap .z-20::before { content:"Loading..." }
-.wrap.cover-bg .z-20::before { content:"" }
-.progress-bar { display:none!important; }
-.meta-text { display:none!important; }
-.meta-text-center { display:none!important; }
-"""
-
# Using constants for these since the variation selector isn't visible.
# Important that they exactly match script.js for tooltip to work.
random_symbol = '\U0001f3b2\ufe0f' # 🎲️
@@ -1215,7 +1204,7 @@ def create_ui(): with gr.Column(elem_id='ti_gallery_container'):
ti_output = gr.Text(elem_id="ti_output", value="", show_label=False)
- ti_gallery = gr.Gallery(label='Output', show_label=False, elem_id='ti_gallery').style(grid=4)
+ ti_gallery = gr.Gallery(label='Output', show_label=False, elem_id='ti_gallery').style(columns=4)
ti_progress = gr.HTML(elem_id="ti_progress", value="")
ti_outcome = gr.HTML(elem_id="ti_error", value="")
@@ -1566,22 +1555,6 @@ def create_ui(): (train_interface, "Train", "ti"),
]
- css = ""
-
- for cssfile in modules.scripts.list_files_with_name("style.css"):
- if not os.path.isfile(cssfile):
- continue
-
- with open(cssfile, "r", encoding="utf8") as file:
- css += file.read() + "\n"
-
- if os.path.exists(os.path.join(data_path, "user.css")):
- with open(os.path.join(data_path, "user.css"), "r", encoding="utf8") as file:
- css += file.read() + "\n"
-
- if not cmd_opts.no_progressbar_hiding:
- css += css_hide_progressbar
-
interfaces += script_callbacks.ui_tabs_callback()
interfaces += [(settings_interface, "Settings", "settings")]
@@ -1592,7 +1565,7 @@ def create_ui(): for _interface, label, _ifid in interfaces:
shared.tab_names.append(label)
- with gr.Blocks(css=css, analytics_enabled=False, title="Stable Diffusion") as demo:
+ with gr.Blocks(analytics_enabled=False, title="Stable Diffusion") as demo:
with gr.Row(elem_id="quicksettings", variant="compact"):
for i, k, item in sorted(quicksettings_list, key=lambda x: quicksettings_names.get(x[1], x[0])):
component = create_setting_component(k, is_quicksettings=True)
@@ -1655,6 +1628,7 @@ def create_ui(): fn=get_settings_values,
inputs=[],
outputs=[component_dict[k] for k in component_keys],
+ queue=False,
)
def modelmerger(*args):
@@ -1777,25 +1751,60 @@ def create_ui(): return demo
-def reload_javascript():
+def webpath(fn):
+ if fn.startswith(script_path):
+ web_path = os.path.relpath(fn, script_path).replace('\\', '/')
+ else:
+ web_path = os.path.abspath(fn)
+
+ return f'file={web_path}?{os.path.getmtime(fn)}'
+
+
+def javascript_html():
script_js = os.path.join(script_path, "script.js")
- head = f'<script type="text/javascript" src="file={os.path.abspath(script_js)}?{os.path.getmtime(script_js)}"></script>\n'
+ head = f'<script type="text/javascript" src="{webpath(script_js)}"></script>\n'
inline = f"{localization.localization_js(shared.opts.localization)};"
if cmd_opts.theme is not None:
inline += f"set_theme('{cmd_opts.theme}');"
for script in modules.scripts.list_scripts("javascript", ".js"):
- head += f'<script type="text/javascript" src="file={script.path}?{os.path.getmtime(script.path)}"></script>\n'
+ head += f'<script type="text/javascript" src="{webpath(script.path)}"></script>\n'
for script in modules.scripts.list_scripts("javascript", ".mjs"):
- head += f'<script type="module" src="file={script.path}?{os.path.getmtime(script.path)}"></script>\n'
+ head += f'<script type="module" src="{webpath(script.path)}"></script>\n'
head += f'<script type="text/javascript">{inline}</script>\n'
+ return head
+
+
+def css_html():
+ head = ""
+
+ def stylesheet(fn):
+ return f'<link rel="stylesheet" property="stylesheet" href="{webpath(fn)}">'
+
+ for cssfile in modules.scripts.list_files_with_name("style.css"):
+ if not os.path.isfile(cssfile):
+ continue
+
+ head += stylesheet(cssfile)
+
+ if os.path.exists(os.path.join(data_path, "user.css")):
+ head += stylesheet(os.path.join(data_path, "user.css"))
+
+ return head
+
+
+def reload_javascript():
+ js = javascript_html()
+ css = css_html()
+
def template_response(*args, **kwargs):
res = shared.GradioTemplateResponseOriginal(*args, **kwargs)
- res.body = res.body.replace(b'</head>', f'{head}</head>'.encode("utf8"))
+ res.body = res.body.replace(b'</head>', f'{js}</head>'.encode("utf8"))
+ res.body = res.body.replace(b'</body>', f'{css}</body>'.encode("utf8"))
res.init_headers()
return res
diff --git a/modules/ui_common.py b/modules/ui_common.py index 3b11dcc8..27ab3ebb 100644 --- a/modules/ui_common.py +++ b/modules/ui_common.py @@ -125,7 +125,7 @@ Requested path was: {f} with gr.Column(variant='panel', elem_id=f"{tabname}_results"):
with gr.Group(elem_id=f"{tabname}_gallery_container"):
- result_gallery = gr.Gallery(label='Output', show_label=False, elem_id=f"{tabname}_gallery").style(grid=4)
+ result_gallery = gr.Gallery(label='Output', show_label=False, elem_id=f"{tabname}_gallery").style(columns=4)
generation_info = None
with gr.Column():
diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py index b4a0d6ec..efd6cda2 100644 --- a/modules/ui_extensions.py +++ b/modules/ui_extensions.py @@ -21,7 +21,7 @@ def check_access(): assert not shared.cmd_opts.disable_extension_access, "extension access disabled because of command line flags"
-def apply_and_restart(disable_list, update_list):
+def apply_and_restart(disable_list, update_list, disable_all):
check_access()
disabled = json.loads(disable_list)
@@ -43,6 +43,7 @@ def apply_and_restart(disable_list, update_list): print(traceback.format_exc(), file=sys.stderr)
shared.opts.disabled_extensions = disabled
+ shared.opts.disable_all_extensions = disable_all
shared.opts.save(shared.config_filename)
shared.state.interrupt()
@@ -99,9 +100,13 @@ def extension_table(): else:
ext_status = ext.status
+ style = ""
+ if shared.opts.disable_all_extensions == "extra" and not ext.is_builtin or shared.opts.disable_all_extensions == "all":
+ style = ' style="color: var(--primary-400)"'
+
code += f"""
<tr>
- <td><label><input class="gr-check-radio gr-checkbox" name="enable_{html.escape(ext.name)}" type="checkbox" {'checked="checked"' if ext.enabled else ''}>{html.escape(ext.name)}</label></td>
+ <td><label{style}><input class="gr-check-radio gr-checkbox" name="enable_{html.escape(ext.name)}" type="checkbox" {'checked="checked"' if ext.enabled else ''}>{html.escape(ext.name)}</label></td>
<td>{remote}</td>
<td>{ext.version}</td>
<td{' class="extension_status"' if ext.remote is not None else ''}>{ext_status}</td>
@@ -294,16 +299,24 @@ def create_ui(): with gr.Row(elem_id="extensions_installed_top"):
apply = gr.Button(value="Apply and restart UI", variant="primary")
check = gr.Button(value="Check for updates")
+ extensions_disable_all = gr.Radio(label="Disable all extensions", choices=["none", "extra", "all"], value=shared.opts.disable_all_extensions, elem_id="extensions_disable_all")
extensions_disabled_list = gr.Text(elem_id="extensions_disabled_list", visible=False).style(container=False)
extensions_update_list = gr.Text(elem_id="extensions_update_list", visible=False).style(container=False)
- info = gr.HTML()
+ html = ""
+ if shared.opts.disable_all_extensions != "none":
+ html = """
+<span style="color: var(--primary-400);">
+ "Disable all extensions" was set, change it to "none" to load all extensions again
+</span>
+ """
+ info = gr.HTML(html)
extensions_table = gr.HTML(lambda: extension_table())
apply.click(
fn=apply_and_restart,
_js="extensions_apply",
- inputs=[extensions_disabled_list, extensions_update_list],
+ inputs=[extensions_disabled_list, extensions_update_list, extensions_disable_all],
outputs=[],
)
diff --git a/modules/ui_postprocessing.py b/modules/ui_postprocessing.py index b418d955..d278e1b6 100644 --- a/modules/ui_postprocessing.py +++ b/modules/ui_postprocessing.py @@ -13,7 +13,7 @@ def create_ui(): extras_image = gr.Image(label="Source", source="upload", interactive=True, type="pil", elem_id="extras_image")
with gr.TabItem('Batch Process', elem_id="extras_batch_process_tab") as tab_batch:
- image_batch = gr.File(label="Batch Process", file_count="multiple", interactive=True, type="file", elem_id="extras_image_batch")
+ image_batch = gr.Files(label="Batch Process", interactive=True, elem_id="extras_image_batch")
with gr.TabItem('Batch from Directory', elem_id="extras_batch_directory_tab") as tab_batch_dir:
extras_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, placeholder="A directory on the same machine where the server is running.", elem_id="extras_batch_input_dir")
diff --git a/requirements.txt b/requirements.txt index c72b2927..77954b8d 100644 --- a/requirements.txt +++ b/requirements.txt @@ -4,7 +4,7 @@ basicsr fonts
font-roboto
gfpgan
-gradio==3.23
+gradio==3.27
invisible-watermark
numpy
omegaconf
diff --git a/requirements_versions.txt b/requirements_versions.txt index df65431a..0a62c6de 100644 --- a/requirements_versions.txt +++ b/requirements_versions.txt @@ -3,7 +3,7 @@ transformers==4.25.1 accelerate==0.12.0
basicsr==1.4.2
gfpgan==1.3.8
-gradio==3.23
+gradio==3.27
numpy==1.23.3
Pillow==9.4.0
realesrgan==0.3.0
diff --git a/scripts/custom_code.py b/scripts/custom_code.py index d29113e6..4071d86d 100644 --- a/scripts/custom_code.py +++ b/scripts/custom_code.py @@ -1,9 +1,40 @@ import modules.scripts as scripts
import gradio as gr
+import ast
+import copy
from modules.processing import Processed
from modules.shared import opts, cmd_opts, state
+
+def convertExpr2Expression(expr):
+ expr.lineno = 0
+ expr.col_offset = 0
+ result = ast.Expression(expr.value, lineno=0, col_offset = 0)
+
+ return result
+
+
+def exec_with_return(code, module):
+ """
+ like exec() but can return values
+ https://stackoverflow.com/a/52361938/5862977
+ """
+ code_ast = ast.parse(code)
+
+ init_ast = copy.deepcopy(code_ast)
+ init_ast.body = code_ast.body[:-1]
+
+ last_ast = copy.deepcopy(code_ast)
+ last_ast.body = code_ast.body[-1:]
+
+ exec(compile(init_ast, "<ast>", "exec"), module.__dict__)
+ if type(last_ast.body[0]) == ast.Expr:
+ return eval(compile(convertExpr2Expression(last_ast.body[0]), "<ast>", "eval"), module.__dict__)
+ else:
+ exec(compile(last_ast, "<ast>", "exec"), module.__dict__)
+
+
class Script(scripts.Script):
def title(self):
@@ -13,12 +44,23 @@ class Script(scripts.Script): return cmd_opts.allow_code
def ui(self, is_img2img):
- code = gr.Textbox(label="Python code", lines=1, elem_id=self.elem_id("code"))
+ example = """from modules.processing import process_images
+
+p.width = 768
+p.height = 768
+p.batch_size = 2
+p.steps = 10
+
+return process_images(p)
+"""
+
- return [code]
+ code = gr.Code(value=example, language="python", label="Python code", elem_id=self.elem_id("code"))
+ indent_level = gr.Number(label='Indent level', value=2, precision=0, elem_id=self.elem_id("indent_level"))
+ return [code, indent_level]
- def run(self, p, code):
+ def run(self, p, code, indent_level):
assert cmd_opts.allow_code, '--allow-code option must be enabled'
display_result_data = [[], -1, ""]
@@ -29,13 +71,20 @@ class Script(scripts.Script): display_result_data[2] = i
from types import ModuleType
- compiled = compile(code, '', 'exec')
module = ModuleType("testmodule")
module.__dict__.update(globals())
module.p = p
module.display = display
- exec(compiled, module.__dict__)
+
+ indent = " " * indent_level
+ indented = code.replace('\n', '\n' + indent)
+ body = f"""def __webuitemp__():
+{indent}{indented}
+__webuitemp__()"""
+
+ result = exec_with_return(body, module)
+
+ if isinstance(result, Processed):
+ return result
return Processed(p, *display_result_data)
-
-
\ No newline at end of file diff --git a/scripts/postprocessing_upscale.py b/scripts/postprocessing_upscale.py index 11eab31a..ef1186ac 100644 --- a/scripts/postprocessing_upscale.py +++ b/scripts/postprocessing_upscale.py @@ -4,8 +4,8 @@ import numpy as np from modules import scripts_postprocessing, shared
import gradio as gr
-from modules.ui_components import FormRow
-
+from modules.ui_components import FormRow, ToolButton
+from modules.ui import switch_values_symbol
upscale_cache = {}
@@ -25,9 +25,12 @@ class ScriptPostprocessingUpscale(scripts_postprocessing.ScriptPostprocessing): with gr.TabItem('Scale to', elem_id="extras_scale_to_tab") as tab_scale_to:
with FormRow():
- upscaling_resize_w = gr.Number(label="Width", value=512, precision=0, elem_id="extras_upscaling_resize_w")
- upscaling_resize_h = gr.Number(label="Height", value=512, precision=0, elem_id="extras_upscaling_resize_h")
- upscaling_crop = gr.Checkbox(label='Crop to fit', value=True, elem_id="extras_upscaling_crop")
+ with gr.Column(elem_id="upscaling_column_size", scale=4):
+ upscaling_resize_w = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="extras_upscaling_resize_w")
+ upscaling_resize_h = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="extras_upscaling_resize_h")
+ with gr.Column(elem_id="upscaling_dimensions_row", scale=1, elem_classes="dimensions-tools"):
+ upscaling_res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="upscaling_res_switch_btn")
+ upscaling_crop = gr.Checkbox(label='Crop to fit', value=True, elem_id="extras_upscaling_crop")
with FormRow():
extras_upscaler_1 = gr.Dropdown(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name)
@@ -36,6 +39,7 @@ class ScriptPostprocessingUpscale(scripts_postprocessing.ScriptPostprocessing): extras_upscaler_2 = gr.Dropdown(label='Upscaler 2', elem_id="extras_upscaler_2", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name)
extras_upscaler_2_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Upscaler 2 visibility", value=0.0, elem_id="extras_upscaler_2_visibility")
+ upscaling_res_switch_btn.click(lambda w, h: (h, w), inputs=[upscaling_resize_w, upscaling_resize_h], outputs=[upscaling_resize_w, upscaling_resize_h], show_progress=False)
tab_scale_by.select(fn=lambda: 0, inputs=[], outputs=[selected_tab])
tab_scale_to.select(fn=lambda: 1, inputs=[], outputs=[selected_tab])
@@ -312,12 +312,23 @@ div.dimensions-tools{ align-content: center;
}
+div#extras_scale_to_tab div.form{
+ flex-direction: row;
+}
+
#mode_img2img .gradio-image > div.fixed-height, #mode_img2img .gradio-image > div.fixed-height img{
height: 480px !important;
max-height: 480px !important;
min-height: 480px !important;
}
+#img2img_sketch, #img2maskimg, #inpaint_sketch {
+ overflow: overlay !important;
+ resize: auto;
+ background: var(--panel-background-fill);
+ z-index: 5;
+}
+
.image-buttons button{
min-width: auto;
}
@@ -329,6 +340,7 @@ div.dimensions-tools{ /* settings */
#quicksettings {
width: fit-content;
+ align-items: end;
}
#quicksettings > div, #quicksettings > fieldset{
@@ -67,6 +67,46 @@ else: server_name = "0.0.0.0" if cmd_opts.listen else None
+def fix_asyncio_event_loop_policy():
+ """
+ The default `asyncio` event loop policy only automatically creates
+ event loops in the main threads. Other threads must create event
+ loops explicitly or `asyncio.get_event_loop` (and therefore
+ `.IOLoop.current`) will fail. Installing this policy allows event
+ loops to be created automatically on any thread, matching the
+ behavior of Tornado versions prior to 5.0 (or 5.0 on Python 2).
+ """
+
+ import asyncio
+
+ if sys.platform == "win32" and hasattr(asyncio, "WindowsSelectorEventLoopPolicy"):
+ # "Any thread" and "selector" should be orthogonal, but there's not a clean
+ # interface for composing policies so pick the right base.
+ _BasePolicy = asyncio.WindowsSelectorEventLoopPolicy # type: ignore
+ else:
+ _BasePolicy = asyncio.DefaultEventLoopPolicy
+
+ class AnyThreadEventLoopPolicy(_BasePolicy): # type: ignore
+ """Event loop policy that allows loop creation on any thread.
+ Usage::
+
+ asyncio.set_event_loop_policy(AnyThreadEventLoopPolicy())
+ """
+
+ def get_event_loop(self) -> asyncio.AbstractEventLoop:
+ try:
+ return super().get_event_loop()
+ except (RuntimeError, AssertionError):
+ # This was an AssertionError in python 3.4.2 (which ships with debian jessie)
+ # and changed to a RuntimeError in 3.4.3.
+ # "There is no current event loop in thread %r"
+ loop = self.new_event_loop()
+ self.set_event_loop(loop)
+ return loop
+
+ asyncio.set_event_loop_policy(AnyThreadEventLoopPolicy())
+
+
def check_versions():
if shared.cmd_opts.skip_version_check:
return
@@ -99,6 +139,8 @@ Use --skip-version-check commandline argument to disable this check. def initialize():
+ fix_asyncio_event_loop_policy()
+
check_versions()
extensions.list_extensions()
@@ -126,9 +168,6 @@ def initialize(): modules.scripts.load_scripts()
startup_timer.record("load scripts")
- modelloader.load_upscalers()
- startup_timer.record("load upscalers")
-
modules.sd_vae.refresh_vae_list()
startup_timer.record("refresh VAE")
|