Merge branch 'master' into img2img-enhance

20 files changed, 391 insertions, 141 deletions

diff --git a/README.md b/README.md
index 24f8e799..b67e2296 100644
--- a/README.md
+++ b/README.md
@@ -13,9 +13,9 @@ A browser interface based on Gradio library for Stable Diffusion.
 - Prompt Matrix

 - Stable Diffusion Upscale

 - Attention, specify parts of text that the model should pay more attention to

-    - a man in a ((tuxedo)) - will pay more attention to tuxedo

-    - a man in a (tuxedo:1.21) - alternative syntax

-    - select text and press ctrl+up or ctrl+down to automatically adjust attention to selected text (code contributed by anonymous user)

+    - a man in a `((tuxedo))` - will pay more attention to tuxedo

+    - a man in a `(tuxedo:1.21)` - alternative syntax

+    - select text and press `Ctrl+Up` or `Ctrl+Down` to automatically adjust attention to selected text (code contributed by anonymous user)

 - Loopback, run img2img processing multiple times

 - X/Y/Z plot, a way to draw a 3 dimensional plot of images with different parameters

 - Textual Inversion

@@ -28,7 +28,7 @@ A browser interface based on Gradio library for Stable Diffusion.
     - CodeFormer, face restoration tool as an alternative to GFPGAN

     - RealESRGAN, neural network upscaler

     - ESRGAN, neural network upscaler with a lot of third party models

-    - SwinIR and Swin2SR([see here](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/2092)), neural network upscalers

+    - SwinIR and Swin2SR ([see here](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/2092)), neural network upscalers

     - LDSR, Latent diffusion super resolution upscaling

 - Resizing aspect ratio options

 - Sampling method selection

@@ -46,7 +46,7 @@ A browser interface based on Gradio library for Stable Diffusion.
      - drag and drop an image/text-parameters to promptbox

 - Read Generation Parameters Button, loads parameters in promptbox to UI

 - Settings page

-- Running arbitrary python code from UI (must run with --allow-code to enable)

+- Running arbitrary python code from UI (must run with `--allow-code` to enable)

 - Mouseover hints for most UI elements

 - Possible to change defaults/mix/max/step values for UI elements via text config

 - Tiling support, a checkbox to create images that can be tiled like textures

@@ -69,7 +69,7 @@ A browser interface based on Gradio library for Stable Diffusion.
      - also supports weights for prompts: `a cat :1.2 AND a dog AND a penguin :2.2`

 - No token limit for prompts (original stable diffusion lets you use up to 75 tokens)

 - DeepDanbooru integration, creates danbooru style tags for anime prompts

-- [xformers](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Xformers), major speed increase for select cards: (add --xformers to commandline args)

+- [xformers](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Xformers), major speed increase for select cards: (add `--xformers` to commandline args)

 - via extension: [History tab](https://github.com/yfszzx/stable-diffusion-webui-images-browser): view, direct and delete images conveniently within the UI

 - Generate forever option

 - Training tab

@@ -78,11 +78,11 @@ A browser interface based on Gradio library for Stable Diffusion.
 - Clip skip

 - Hypernetworks

 - Loras (same as Hypernetworks but more pretty)

-- A sparate UI where you can choose, with preview, which embeddings, hypernetworks or Loras to add to your prompt. 

+- A sparate UI where you can choose, with preview, which embeddings, hypernetworks or Loras to add to your prompt 

 - Can select to load a different VAE from settings screen

 - Estimated completion time in progress bar

 - API

-- Support for dedicated [inpainting model](https://github.com/runwayml/stable-diffusion#inpainting-with-stable-diffusion) by RunwayML.

+- Support for dedicated [inpainting model](https://github.com/runwayml/stable-diffusion#inpainting-with-stable-diffusion) by RunwayML

 - via extension: [Aesthetic Gradients](https://github.com/AUTOMATIC1111/stable-diffusion-webui-aesthetic-gradients), a way to generate images with a specific aesthetic by using clip images embeds (implementation of [https://github.com/vicgalle/stable-diffusion-aesthetic-gradients](https://github.com/vicgalle/stable-diffusion-aesthetic-gradients))

 - [Stable Diffusion 2.0](https://github.com/Stability-AI/stablediffusion) support - see [wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#stable-diffusion-20) for instructions

 - [Alt-Diffusion](https://arxiv.org/abs/2211.06679) support - see [wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#alt-diffusion) for instructions

@@ -91,7 +91,6 @@ A browser interface based on Gradio library for Stable Diffusion.
 - Eased resolution restriction: generated image's domension must be a multiple of 8 rather than 64

 - Now with a license!

 - Reorder elements in the UI from settings screen

-- 

 

 ## Installation and Running

 Make sure the required [dependencies](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies) are met and follow the instructions available for both [NVidia](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-NVidia-GPUs) (recommended) and [AMD](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs) GPUs.

@@ -101,7 +100,7 @@ Alternatively, use online services (like Google Colab):
 - [List of Online Services](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Online-Services)

 

 ### Automatic Installation on Windows

-1. Install [Python 3.10.6](https://www.python.org/downloads/windows/), checking "Add Python to PATH"

+1. Install [Python 3.10.6](https://www.python.org/downloads/windows/), checking "Add Python to PATH".

 2. Install [git](https://git-scm.com/download/win).

 3. Download the stable-diffusion-webui repository, for example by running `git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui.git`.

 4. Run `webui-user.bat` from Windows Explorer as normal, non-administrator, user.

@@ -159,4 +158,4 @@ Licenses for borrowed code can be found in `Settings -> Licenses` screen, and al
 - Security advice - RyotaK

 - UniPC sampler - Wenliang Zhao - https://github.com/wl-zhao/UniPC

 - Initial Gradio script - posted on 4chan by an Anonymous user. Thank you Anonymous user.

-- (You)

+- (You)
\ No newline at end of file
diff --git a/extensions-builtin/Lora/lora.py b/extensions-builtin/Lora/lora.py
index 7c371deb..d3eb0d3b 100644
--- a/extensions-builtin/Lora/lora.py
+++ b/extensions-builtin/Lora/lora.py
@@ -2,20 +2,34 @@ import glob
 import os

 import re

 import torch

+from typing import Union

 

 from modules import shared, devices, sd_models, errors

 

 metadata_tags_order = {"ss_sd_model_name": 1, "ss_resolution": 2, "ss_clip_skip": 3, "ss_num_train_images": 10, "ss_tag_frequency": 20}

 

 re_digits = re.compile(r"\d+")

-re_unet_down_blocks = re.compile(r"lora_unet_down_blocks_(\d+)_attentions_(\d+)_(.+)")

-re_unet_mid_blocks = re.compile(r"lora_unet_mid_block_attentions_(\d+)_(.+)")

-re_unet_up_blocks = re.compile(r"lora_unet_up_blocks_(\d+)_attentions_(\d+)_(.+)")

-re_text_block = re.compile(r"lora_te_text_model_encoder_layers_(\d+)_(.+)")

+re_x_proj = re.compile(r"(.*)_([qkv]_proj)$")

+re_compiled = {}

+

+suffix_conversion = {

+    "attentions": {},

+    "resnets": {

+        "conv1": "in_layers_2",

+        "conv2": "out_layers_3",

+        "time_emb_proj": "emb_layers_1",

+        "conv_shortcut": "skip_connection",

+    }

+}

+

+

+def convert_diffusers_name_to_compvis(key, is_sd2):

+    def match(match_list, regex_text):

+        regex = re_compiled.get(regex_text)

+        if regex is None:

+            regex = re.compile(regex_text)

+            re_compiled[regex_text] = regex

 

-

-def convert_diffusers_name_to_compvis(key):

-    def match(match_list, regex):

         r = re.match(regex, key)

         if not r:

             return False

@@ -26,16 +40,33 @@ def convert_diffusers_name_to_compvis(key):
 

     m = []

 

-    if match(m, re_unet_down_blocks):

-        return f"diffusion_model_input_blocks_{1 + m[0] * 3 + m[1]}_1_{m[2]}"

+    if match(m, r"lora_unet_down_blocks_(\d+)_(attentions|resnets)_(\d+)_(.+)"):

+        suffix = suffix_conversion.get(m[1], {}).get(m[3], m[3])

+        return f"diffusion_model_input_blocks_{1 + m[0] * 3 + m[2]}_{1 if m[1] == 'attentions' else 0}_{suffix}"

+

+    if match(m, r"lora_unet_mid_block_(attentions|resnets)_(\d+)_(.+)"):

+        suffix = suffix_conversion.get(m[0], {}).get(m[2], m[2])

+        return f"diffusion_model_middle_block_{1 if m[0] == 'attentions' else m[1] * 2}_{suffix}"

+

+    if match(m, r"lora_unet_up_blocks_(\d+)_(attentions|resnets)_(\d+)_(.+)"):

+        suffix = suffix_conversion.get(m[1], {}).get(m[3], m[3])

+        return f"diffusion_model_output_blocks_{m[0] * 3 + m[2]}_{1 if m[1] == 'attentions' else 0}_{suffix}"

 

-    if match(m, re_unet_mid_blocks):

-        return f"diffusion_model_middle_block_1_{m[1]}"

+    if match(m, r"lora_unet_down_blocks_(\d+)_downsamplers_0_conv"):

+        return f"diffusion_model_input_blocks_{3 + m[0] * 3}_0_op"

 

-    if match(m, re_unet_up_blocks):

-        return f"diffusion_model_output_blocks_{m[0] * 3 + m[1]}_1_{m[2]}"

+    if match(m, r"lora_unet_up_blocks_(\d+)_upsamplers_0_conv"):

+        return f"diffusion_model_output_blocks_{2 + m[0] * 3}_{2 if m[0]>0 else 1}_conv"

+

+    if match(m, r"lora_te_text_model_encoder_layers_(\d+)_(.+)"):

+        if is_sd2:

+            if 'mlp_fc1' in m[1]:

+                return f"model_transformer_resblocks_{m[0]}_{m[1].replace('mlp_fc1', 'mlp_c_fc')}"

+            elif 'mlp_fc2' in m[1]:

+                return f"model_transformer_resblocks_{m[0]}_{m[1].replace('mlp_fc2', 'mlp_c_proj')}"

+            else:

+                return f"model_transformer_resblocks_{m[0]}_{m[1].replace('self_attn', 'attn')}"

 

-    if match(m, re_text_block):

         return f"transformer_text_model_encoder_layers_{m[0]}_{m[1]}"

 

     return key

@@ -101,15 +132,22 @@ def load_lora(name, filename):
 

     sd = sd_models.read_state_dict(filename)

 

-    keys_failed_to_match = []

+    keys_failed_to_match = {}

+    is_sd2 = 'model_transformer_resblocks' in shared.sd_model.lora_layer_mapping

 

     for key_diffusers, weight in sd.items():

-        fullkey = convert_diffusers_name_to_compvis(key_diffusers)

-        key, lora_key = fullkey.split(".", 1)

+        key_diffusers_without_lora_parts, lora_key = key_diffusers.split(".", 1)

+        key = convert_diffusers_name_to_compvis(key_diffusers_without_lora_parts, is_sd2)

 

         sd_module = shared.sd_model.lora_layer_mapping.get(key, None)

+

         if sd_module is None:

-            keys_failed_to_match.append(key_diffusers)

+            m = re_x_proj.match(key)

+            if m:

+                sd_module = shared.sd_model.lora_layer_mapping.get(m.group(1), None)

+

+        if sd_module is None:

+            keys_failed_to_match[key_diffusers] = key

             continue

 

         lora_module = lora.modules.get(key, None)

@@ -123,15 +161,21 @@ def load_lora(name, filename):
 

         if type(sd_module) == torch.nn.Linear:

             module = torch.nn.Linear(weight.shape[1], weight.shape[0], bias=False)

+        elif type(sd_module) == torch.nn.modules.linear.NonDynamicallyQuantizableLinear:

+            module = torch.nn.Linear(weight.shape[1], weight.shape[0], bias=False)

+        elif type(sd_module) == torch.nn.MultiheadAttention:

+            module = torch.nn.Linear(weight.shape[1], weight.shape[0], bias=False)

         elif type(sd_module) == torch.nn.Conv2d:

             module = torch.nn.Conv2d(weight.shape[1], weight.shape[0], (1, 1), bias=False)

         else:

+            print(f'Lora layer {key_diffusers} matched a layer with unsupported type: {type(sd_module).__name__}')

+            continue

             assert False, f'Lora layer {key_diffusers} matched a layer with unsupported type: {type(sd_module).__name__}'

 

         with torch.no_grad():

             module.weight.copy_(weight)

 

-        module.to(device=devices.device, dtype=devices.dtype)

+        module.to(device=devices.cpu, dtype=devices.dtype)

 

         if lora_key == "lora_up.weight":

             lora_module.up = module

@@ -177,29 +221,120 @@ def load_loras(names, multipliers=None):
         loaded_loras.append(lora)

 

 

-def lora_forward(module, input, res):

-    input = devices.cond_cast_unet(input)

-    if len(loaded_loras) == 0:

-        return res

+def lora_calc_updown(lora, module, target):

+    with torch.no_grad():

+        up = module.up.weight.to(target.device, dtype=target.dtype)

+        down = module.down.weight.to(target.device, dtype=target.dtype)

 

-    lora_layer_name = getattr(module, 'lora_layer_name', None)

-    for lora in loaded_loras:

-        module = lora.modules.get(lora_layer_name, None)

-        if module is not None:

-            if shared.opts.lora_apply_to_outputs and res.shape == input.shape:

-                res = res + module.up(module.down(res)) * lora.multiplier * (module.alpha / module.up.weight.shape[1] if module.alpha else 1.0)

+        if up.shape[2:] == (1, 1) and down.shape[2:] == (1, 1):

+            updown = (up.squeeze(2).squeeze(2) @ down.squeeze(2).squeeze(2)).unsqueeze(2).unsqueeze(3)

+        else:

+            updown = up @ down

+

+        updown = updown * lora.multiplier * (module.alpha / module.up.weight.shape[1] if module.alpha else 1.0)

+

+        return updown

+

+

+def lora_apply_weights(self: Union[torch.nn.Conv2d, torch.nn.Linear, torch.nn.MultiheadAttention]):

+    """

+    Applies the currently selected set of Loras to the weights of torch layer self.

+    If weights already have this particular set of loras applied, does nothing.

+    If not, restores orginal weights from backup and alters weights according to loras.

+    """

+

+    lora_layer_name = getattr(self, 'lora_layer_name', None)

+    if lora_layer_name is None:

+        return

+

+    current_names = getattr(self, "lora_current_names", ())

+    wanted_names = tuple((x.name, x.multiplier) for x in loaded_loras)

+

+    weights_backup = getattr(self, "lora_weights_backup", None)

+    if weights_backup is None:

+        if isinstance(self, torch.nn.MultiheadAttention):

+            weights_backup = (self.in_proj_weight.to(devices.cpu, copy=True), self.out_proj.weight.to(devices.cpu, copy=True))

+        else:

+            weights_backup = self.weight.to(devices.cpu, copy=True)

+

+        self.lora_weights_backup = weights_backup

+

+    if current_names != wanted_names:

+        if weights_backup is not None:

+            if isinstance(self, torch.nn.MultiheadAttention):

+                self.in_proj_weight.copy_(weights_backup[0])

+                self.out_proj.weight.copy_(weights_backup[1])

             else:

-                res = res + module.up(module.down(input)) * lora.multiplier * (module.alpha / module.up.weight.shape[1] if module.alpha else 1.0)

+                self.weight.copy_(weights_backup)

 

-    return res

+        for lora in loaded_loras:

+            module = lora.modules.get(lora_layer_name, None)

+            if module is not None and hasattr(self, 'weight'):

+                self.weight += lora_calc_updown(lora, module, self.weight)

+                continue

+

+            module_q = lora.modules.get(lora_layer_name + "_q_proj", None)

+            module_k = lora.modules.get(lora_layer_name + "_k_proj", None)

+            module_v = lora.modules.get(lora_layer_name + "_v_proj", None)

+            module_out = lora.modules.get(lora_layer_name + "_out_proj", None)

+

+            if isinstance(self, torch.nn.MultiheadAttention) and module_q and module_k and module_v and module_out:

+                updown_q = lora_calc_updown(lora, module_q, self.in_proj_weight)

+                updown_k = lora_calc_updown(lora, module_k, self.in_proj_weight)

+                updown_v = lora_calc_updown(lora, module_v, self.in_proj_weight)

+                updown_qkv = torch.vstack([updown_q, updown_k, updown_v])

+

+                self.in_proj_weight += updown_qkv

+                self.out_proj.weight += lora_calc_updown(lora, module_out, self.out_proj.weight)

+                continue

+

+            if module is None:

+                continue

+

+            print(f'failed to calculate lora weights for layer {lora_layer_name}')

+

+        setattr(self, "lora_current_names", wanted_names)

+

+

+def lora_reset_cached_weight(self: Union[torch.nn.Conv2d, torch.nn.Linear]):

+    setattr(self, "lora_current_names", ())

+    setattr(self, "lora_weights_backup", None)

 

 

 def lora_Linear_forward(self, input):

-    return lora_forward(self, input, torch.nn.Linear_forward_before_lora(self, input))

+    lora_apply_weights(self)

+

+    return torch.nn.Linear_forward_before_lora(self, input)

+

+

+def lora_Linear_load_state_dict(self, *args, **kwargs):

+    lora_reset_cached_weight(self)

+

+    return torch.nn.Linear_load_state_dict_before_lora(self, *args, **kwargs)

 

 

 def lora_Conv2d_forward(self, input):

-    return lora_forward(self, input, torch.nn.Conv2d_forward_before_lora(self, input))

+    lora_apply_weights(self)

+

+    return torch.nn.Conv2d_forward_before_lora(self, input)

+

+

+def lora_Conv2d_load_state_dict(self, *args, **kwargs):

+    lora_reset_cached_weight(self)

+

+    return torch.nn.Conv2d_load_state_dict_before_lora(self, *args, **kwargs)

+

+

+def lora_MultiheadAttention_forward(self, *args, **kwargs):

+    lora_apply_weights(self)

+

+    return torch.nn.MultiheadAttention_forward_before_lora(self, *args, **kwargs)

+

+

+def lora_MultiheadAttention_load_state_dict(self, *args, **kwargs):

+    lora_reset_cached_weight(self)

+

+    return torch.nn.MultiheadAttention_load_state_dict_before_lora(self, *args, **kwargs)

 

 

 def list_available_loras():

@@ -212,7 +347,7 @@ def list_available_loras():
         glob.glob(os.path.join(shared.cmd_opts.lora_dir, '**/*.safetensors'), recursive=True) + \

         glob.glob(os.path.join(shared.cmd_opts.lora_dir, '**/*.ckpt'), recursive=True)

 

-    for filename in sorted(candidates):

+    for filename in sorted(candidates, key=str.lower):

         if os.path.isdir(filename):

             continue

 

diff --git a/extensions-builtin/Lora/scripts/lora_script.py b/extensions-builtin/Lora/scripts/lora_script.py
index 2e860160..0adab225 100644
--- a/extensions-builtin/Lora/scripts/lora_script.py
+++ b/extensions-builtin/Lora/scripts/lora_script.py
@@ -9,7 +9,11 @@ from modules import script_callbacks, ui_extra_networks, extra_networks, shared
 

 def unload():

     torch.nn.Linear.forward = torch.nn.Linear_forward_before_lora

+    torch.nn.Linear._load_from_state_dict = torch.nn.Linear_load_state_dict_before_lora

     torch.nn.Conv2d.forward = torch.nn.Conv2d_forward_before_lora

+    torch.nn.Conv2d._load_from_state_dict = torch.nn.Conv2d_load_state_dict_before_lora

+    torch.nn.MultiheadAttention.forward = torch.nn.MultiheadAttention_forward_before_lora

+    torch.nn.MultiheadAttention._load_from_state_dict = torch.nn.MultiheadAttention_load_state_dict_before_lora

 

 

 def before_ui():

@@ -20,11 +24,27 @@ def before_ui():
 if not hasattr(torch.nn, 'Linear_forward_before_lora'):

     torch.nn.Linear_forward_before_lora = torch.nn.Linear.forward

 

+if not hasattr(torch.nn, 'Linear_load_state_dict_before_lora'):

+    torch.nn.Linear_load_state_dict_before_lora = torch.nn.Linear._load_from_state_dict

+

 if not hasattr(torch.nn, 'Conv2d_forward_before_lora'):

     torch.nn.Conv2d_forward_before_lora = torch.nn.Conv2d.forward

 

+if not hasattr(torch.nn, 'Conv2d_load_state_dict_before_lora'):

+    torch.nn.Conv2d_load_state_dict_before_lora = torch.nn.Conv2d._load_from_state_dict

+

+if not hasattr(torch.nn, 'MultiheadAttention_forward_before_lora'):

+    torch.nn.MultiheadAttention_forward_before_lora = torch.nn.MultiheadAttention.forward

+

+if not hasattr(torch.nn, 'MultiheadAttention_load_state_dict_before_lora'):

+    torch.nn.MultiheadAttention_load_state_dict_before_lora = torch.nn.MultiheadAttention._load_from_state_dict

+

 torch.nn.Linear.forward = lora.lora_Linear_forward

+torch.nn.Linear._load_from_state_dict = lora.lora_Linear_load_state_dict

 torch.nn.Conv2d.forward = lora.lora_Conv2d_forward

+torch.nn.Conv2d._load_from_state_dict = lora.lora_Conv2d_load_state_dict

+torch.nn.MultiheadAttention.forward = lora.lora_MultiheadAttention_forward

+torch.nn.MultiheadAttention._load_from_state_dict = lora.lora_MultiheadAttention_load_state_dict

 

 script_callbacks.on_model_loaded(lora.assign_lora_names_to_compvis_modules)

 script_callbacks.on_script_unloaded(unload)

@@ -33,6 +53,4 @@ 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),

-    "lora_apply_to_outputs": shared.OptionInfo(False, "Apply Lora to outputs rather than inputs when possible (experimental)"),

-

 }))

diff --git a/javascript/aspectRatioOverlay.js b/javascript/aspectRatioOverlay.js
index 0f164b82..a8278cca 100644
--- a/javascript/aspectRatioOverlay.js
+++ b/javascript/aspectRatioOverlay.js
@@ -12,7 +12,7 @@ function dimensionChange(e, is_width, is_height){
 		currentHeight = e.target.value*1.0

 	}

 

-	var inImg2img   = Boolean(gradioApp().querySelector("button.rounded-t-lg.border-gray-200"))

+	var inImg2img = gradioApp().querySelector("#tab_img2img").style.display == "block";

 

 	if(!inImg2img){

 		return;

@@ -22,7 +22,7 @@ function dimensionChange(e, is_width, is_height){
 

     var tabIndex = get_tab_index('mode_img2img')

 	if(tabIndex == 0){ // img2img

-		targetElement = gradioApp().querySelector('div[data-testid=image] img');

+		targetElement = gradioApp().querySelector('#img2img_image div[data-testid=image] img');

 	} else if(tabIndex == 1){ //Sketch

 		targetElement = gradioApp().querySelector('#img2img_sketch div[data-testid=image] img');

 	} else if(tabIndex == 2){ // Inpaint

@@ -30,7 +30,7 @@ function dimensionChange(e, is_width, is_height){
 	} else if(tabIndex == 3){ // Inpaint sketch

 		targetElement = gradioApp().querySelector('#inpaint_sketch div[data-testid=image] img');

 	}

-	

+

 

 	if(targetElement){

 

@@ -38,7 +38,7 @@ function dimensionChange(e, is_width, is_height){
 		if(!arPreviewRect){

 		    arPreviewRect = document.createElement('div')

 		    arPreviewRect.id = "imageARPreview";

-		    gradioApp().getRootNode().appendChild(arPreviewRect)

+		    gradioApp().appendChild(arPreviewRect)

 		}

 

 

@@ -91,23 +91,26 @@ onUiUpdate(function(){
 	if(arPreviewRect){

 		arPreviewRect.style.display = 'none';

 	}

-	var inImg2img   = Boolean(gradioApp().querySelector("button.rounded-t-lg.border-gray-200"))

-	if(inImg2img){

-		let inputs = gradioApp().querySelectorAll('input');

-		inputs.forEach(function(e){

-		    var is_width = e.parentElement.id == "img2img_width"

-		    var is_height = e.parentElement.id == "img2img_height"

-

-			if((is_width || is_height) && !e.classList.contains('scrollwatch')){

-				e.addEventListener('input', function(e){dimensionChange(e, is_width, is_height)} )

-				e.classList.add('scrollwatch')

-			}

-			if(is_width){

-				currentWidth = e.value*1.0

-			}

-			if(is_height){

-				currentHeight = e.value*1.0

-			}

-		})

-	}

+    var tabImg2img = gradioApp().querySelector("#tab_img2img");

+    if (tabImg2img) {

+        var inImg2img = tabImg2img.style.display == "block";

+        if(inImg2img){

+            let inputs = gradioApp().querySelectorAll('input');

+            inputs.forEach(function(e){

+                var is_width = e.parentElement.id == "img2img_width"

+                var is_height = e.parentElement.id == "img2img_height"

+

+                if((is_width || is_height) && !e.classList.contains('scrollwatch')){

+                    e.addEventListener('input', function(e){dimensionChange(e, is_width, is_height)} )

+                    e.classList.add('scrollwatch')

+                }

+                if(is_width){

+                    currentWidth = e.value*1.0

+                }

+                if(is_height){

+                    currentHeight = e.value*1.0

+                }

+            })

+        }

+    }

 });

diff --git a/javascript/hints.js b/javascript/hints.js
index b3f3d08d..f48a0eb6 100644
--- a/javascript/hints.js
+++ b/javascript/hints.js
@@ -21,8 +21,7 @@ titles = {
     "\u{1f5d1}\ufe0f": "Clear prompt",
     "\u{1f4cb}": "Apply selected styles to current prompt",
     "\u{1f4d2}": "Paste available values into the field",
-    "\u{1f3b4}": "Show extra networks",
-
+    "\u{1f3b4}": "Show/hide extra networks",
 
     "Inpaint a part of image": "Draw a mask over an image, and the script will regenerate the masked area with content according to prompt",
     "SD upscale": "Upscale image normally, split result into tiles, improve each tile using img2img, merge whole image back",
diff --git a/javascript/imageviewer.js b/javascript/imageviewer.js
index 7547e771..d6483562 100644
--- a/javascript/imageviewer.js
+++ b/javascript/imageviewer.js
@@ -32,13 +32,7 @@ function negmod(n, m) {
 function updateOnBackgroundChange() {
     const modalImage = gradioApp().getElementById("modalImage")
     if (modalImage && modalImage.offsetParent) {
-        let allcurrentButtons = gradioApp().querySelectorAll(".gallery-item.transition-all.\\!ring-2")
-        let currentButton = null
-        allcurrentButtons.forEach(function(elem) {
-            if (elem.parentElement.offsetParent) {
-                currentButton = elem;
-            }
-        })
+        let currentButton = selected_gallery_button();
 
         if (currentButton?.children?.length > 0 && modalImage.src != currentButton.children[0].src) {
             modalImage.src = currentButton.children[0].src;
@@ -50,22 +44,10 @@ function updateOnBackgroundChange() {
 }
 
 function modalImageSwitch(offset) {
-    var allgalleryButtons = gradioApp().querySelectorAll(".gradio-gallery .thumbnail-item")
-    var galleryButtons = []
-    allgalleryButtons.forEach(function(elem) {
-        if (elem.parentElement.offsetParent) {
-            galleryButtons.push(elem);
-        }
-    })
+    var galleryButtons = all_gallery_buttons();
 
     if (galleryButtons.length > 1) {
-        var allcurrentButtons = gradioApp().querySelectorAll(".gradio-gallery .thumbnail-item.selected")
-        var currentButton = null
-        allcurrentButtons.forEach(function(elem) {
-            if (elem.parentElement.offsetParent) {
-                currentButton = elem;
-            }
-        })
+        var currentButton = selected_gallery_button();
 
         var result = -1
         galleryButtons.forEach(function(v, i) {
diff --git a/javascript/notification.js b/javascript/notification.js
index 5ae6df24..8ddd4c5d 100644
--- a/javascript/notification.js
+++ b/javascript/notification.js
@@ -15,7 +15,7 @@ onUiUpdate(function(){
         }
     }
 
-    const galleryPreviews = gradioApp().querySelectorAll('div[id^="tab_"][style*="display: block"] div[id$="_results"] img.h-full.w-full.overflow-hidden');
+    const galleryPreviews = gradioApp().querySelectorAll('div[id^="tab_"][style*="display: block"] div[id$="_results"] .thumbnail-item > img');
 
     if (galleryPreviews == null) return;
 
diff --git a/javascript/ui.js b/javascript/ui.js
index 7aa30dc1..a73eeaa2 100644
--- a/javascript/ui.js
+++ b/javascript/ui.js
@@ -7,9 +7,31 @@ function set_theme(theme){
     }
 }
 
+function all_gallery_buttons() {
+    var allGalleryButtons = gradioApp().querySelectorAll('[style="display: block;"].tabitem div[id$=_gallery].gradio-gallery .thumbnails > .thumbnail-item.thumbnail-small');
+    var visibleGalleryButtons = [];
+    allGalleryButtons.forEach(function(elem) {
+        if (elem.parentElement.offsetParent) {
+            visibleGalleryButtons.push(elem);
+        }
+    })
+    return visibleGalleryButtons;
+}
+
+function selected_gallery_button() {
+    var allCurrentButtons = gradioApp().querySelectorAll('[style="display: block;"].tabitem div[id$=_gallery].gradio-gallery .thumbnail-item.thumbnail-small.selected');
+    var visibleCurrentButton = null;
+    allCurrentButtons.forEach(function(elem) {
+        if (elem.parentElement.offsetParent) {
+            visibleCurrentButton = elem;
+        }
+    })
+    return visibleCurrentButton;
+}
+
 function selected_gallery_index(){
-    var buttons = gradioApp().querySelectorAll('[style="display: block;"].tabitem div[id$=_gallery] .thumbnails > .thumbnail-item')
-    var button = gradioApp().querySelector('[style="display: block;"].tabitem div[id$=_gallery] .thumbnails > .thumbnail-item.selected')
+    var buttons = all_gallery_buttons();
+    var button = selected_gallery_button();
 
     var result = -1
     buttons.forEach(function(v, i){ if(v==button) { result = i } })
@@ -18,14 +40,18 @@ function selected_gallery_index(){
 }
 
 function extract_image_from_gallery(gallery){
-    if(gallery.length == 1){
-        return [gallery[0]]
+    if (gallery.length == 0){
+        return [null];
+    }
+    if (gallery.length == 1){
+        return [gallery[0]];
     }
 
     index = selected_gallery_index()
 
     if (index < 0 || index >= gallery.length){
-        return [null]
+        // Use the first image in the gallery as the default
+        index = 0;
     }
 
     return [gallery[index]];
diff --git a/modules/api/api.py b/modules/api/api.py
index 13af9ed6..518b2a61 100644
--- a/modules/api/api.py
+++ b/modules/api/api.py
@@ -3,6 +3,7 @@ import io
 import time
 import datetime
 import uvicorn
+import gradio as gr
 from threading import Lock
 from io import BytesIO
 from gradio.processing_utils import decode_base64_to_file
@@ -197,6 +198,9 @@ class Api:
         self.add_api_route("/sdapi/v1/reload-checkpoint", self.reloadapi, methods=["POST"])
         self.add_api_route("/sdapi/v1/scripts", self.get_scripts_list, methods=["GET"], response_model=ScriptsList)
 
+        self.default_script_arg_txt2img = []
+        self.default_script_arg_img2img = []
+
     def add_api_route(self, path: str, endpoint, **kwargs):
         if shared.cmd_opts.api_auth:
             return self.app.add_api_route(path, endpoint, dependencies=[Depends(self.auth)], **kwargs)
@@ -230,7 +234,7 @@ class Api:
         script_idx = script_name_to_index(script_name, script_runner.scripts)
         return script_runner.scripts[script_idx]
 
-    def init_script_args(self, request, selectable_scripts, selectable_idx, script_runner):
+    def init_default_script_args(self, script_runner):
         #find max idx from the scripts in runner and generate a none array to init script_args
         last_arg_index = 1
         for script in script_runner.scripts:
@@ -238,13 +242,24 @@ class Api:
                 last_arg_index = script.args_to
         # None everywhere except position 0 to initialize script args
         script_args = [None]*last_arg_index
+        script_args[0] = 0
+
+        # get default values
+        with gr.Blocks(): # will throw errors calling ui function without this
+            for script in script_runner.scripts:
+                if script.ui(script.is_img2img):
+                    ui_default_values = []
+                    for elem in script.ui(script.is_img2img):
+                        ui_default_values.append(elem.value)
+                    script_args[script.args_from:script.args_to] = ui_default_values
+        return script_args
+
+    def init_script_args(self, request, default_script_args, selectable_scripts, selectable_idx, script_runner):
+        script_args = default_script_args.copy()
         # position 0 in script_arg is the idx+1 of the selectable script that is going to be run when using scripts.scripts_*2img.run()
         if selectable_scripts:
             script_args[selectable_scripts.args_from:selectable_scripts.args_to] = request.script_args
             script_args[0] = selectable_idx + 1
-        else:
-            # when [0] = 0 no selectable script to run
-            script_args[0] = 0
 
         # Now check for always on scripts
         if request.alwayson_scripts and (len(request.alwayson_scripts) > 0):
@@ -265,6 +280,8 @@ class Api:
         if not script_runner.scripts:
             script_runner.initialize_scripts(False)
             ui.create_ui()
+        if not self.default_script_arg_txt2img:
+            self.default_script_arg_txt2img = self.init_default_script_args(script_runner)
         selectable_scripts, selectable_script_idx = self.get_selectable_script(txt2imgreq.script_name, script_runner)
 
         populate = txt2imgreq.copy(update={  # Override __init__ params
@@ -280,7 +297,7 @@ class Api:
         args.pop('script_args', None) # will refeed them to the pipeline directly after initializing them
         args.pop('alwayson_scripts', None)
 
-        script_args = self.init_script_args(txt2imgreq, selectable_scripts, selectable_script_idx, script_runner)
+        script_args = self.init_script_args(txt2imgreq, self.default_script_arg_txt2img, selectable_scripts, selectable_script_idx, script_runner)
 
         send_images = args.pop('send_images', True)
         args.pop('save_images', None)
@@ -317,6 +334,8 @@ class Api:
         if not script_runner.scripts:
             script_runner.initialize_scripts(True)
             ui.create_ui()
+        if not self.default_script_arg_img2img:
+            self.default_script_arg_img2img = self.init_default_script_args(script_runner)
         selectable_scripts, selectable_script_idx = self.get_selectable_script(img2imgreq.script_name, script_runner)
 
         populate = img2imgreq.copy(update={  # Override __init__ params
@@ -334,7 +353,7 @@ class Api:
         args.pop('script_args', None)  # will refeed them to the pipeline directly after initializing them
         args.pop('alwayson_scripts', None)
 
-        script_args = self.init_script_args(img2imgreq, selectable_scripts, selectable_script_idx, script_runner)
+        script_args = self.init_script_args(img2imgreq, self.default_script_arg_img2img, selectable_scripts, selectable_script_idx, script_runner)
 
         send_images = args.pop('send_images', True)
         args.pop('save_images', None)
diff --git a/modules/cmd_args.py b/modules/cmd_args.py
index 0af87251..81c0b82a 100644
--- a/modules/cmd_args.py
+++ b/modules/cmd_args.py
@@ -4,6 +4,7 @@ from modules.paths_internal import models_path, script_path, data_path, extensio
 

 parser = argparse.ArgumentParser()

 

+parser.add_argument("-f", action='store_true', help=argparse.SUPPRESS)  # allows running as root; implemented outside of webui

 parser.add_argument("--update-all-extensions", action='store_true', help="launch.py argument: download updates for all extensions when starting the program")

 parser.add_argument("--skip-python-version-check", action='store_true', help="launch.py argument: do not check python version")

 parser.add_argument("--skip-torch-cuda-test", action='store_true', help="launch.py argument: do not check if CUDA is able to work properly")

diff --git a/modules/extensions.py b/modules/extensions.py
index a14ffbf0..0d34b89a 100644
--- a/modules/extensions.py
+++ b/modules/extensions.py
@@ -5,13 +5,14 @@ import traceback
 import time

 import git

 

-from modules import paths, shared

+from modules import shared

 from modules.paths_internal import extensions_dir, extensions_builtin_dir

 

 extensions = []

 

-if not os.path.exists(paths.extensions_dir):

-    os.makedirs(paths.extensions_dir)

+if not os.path.exists(extensions_dir):

+    os.makedirs(extensions_dir)

+

 

 def active():

     return [x for x in extensions if x.enabled]

@@ -26,21 +27,29 @@ class Extension:
         self.can_update = False

         self.is_builtin = is_builtin

         self.version = ''

+        self.remote = None

+        self.have_info_from_repo = False

+

+    def read_info_from_repo(self):

+        if self.have_info_from_repo:

+            return

+

+        self.have_info_from_repo = True

 

         repo = None

         try:

-            if os.path.exists(os.path.join(path, ".git")):

-                repo = git.Repo(path)

+            if os.path.exists(os.path.join(self.path, ".git")):

+                repo = git.Repo(self.path)

         except Exception:

-            print(f"Error reading github repository info from {path}:", file=sys.stderr)

+            print(f"Error reading github repository info from {self.path}:", file=sys.stderr)

             print(traceback.format_exc(), file=sys.stderr)

 

         if repo is None or repo.bare:

             self.remote = None

         else:

             try:

-                self.remote = next(repo.remote().urls, None)

                 self.status = 'unknown'

+                self.remote = next(repo.remote().urls, None)

                 head = repo.head.commit

                 ts = time.asctime(time.gmtime(repo.head.commit.committed_date))

                 self.version = f'{head.hexsha[:8]} ({ts})'

@@ -85,11 +94,11 @@ class Extension:
 def list_extensions():

     extensions.clear()

 

-    if not os.path.isdir(paths.extensions_dir):

+    if not os.path.isdir(extensions_dir):

         return

 

     extension_paths = []

-    for dirname in [paths.extensions_dir, paths.extensions_builtin_dir]:

+    for dirname in [extensions_dir, extensions_builtin_dir]:

         if not os.path.isdir(dirname):

             return

 

@@ -98,7 +107,7 @@ def list_extensions():
             if not os.path.isdir(path):

                 continue

 

-            extension_paths.append((extension_dirname, path, dirname == paths.extensions_builtin_dir))

+            extension_paths.append((extension_dirname, path, dirname == extensions_builtin_dir))

 

     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)

diff --git a/modules/images.py b/modules/images.py
index 7030aaaa..b3535070 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -261,9 +261,12 @@ def resize_image(resize_mode, im, width, height, upscaler_name=None):
 

         if scale > 1.0:

             upscalers = [x for x in shared.sd_upscalers if x.name == upscaler_name]

-            assert len(upscalers) > 0, f"could not find upscaler named {upscaler_name}"

+            if len(upscalers) == 0:

+                upscaler = shared.sd_upscalers[0]

+                print(f"could not find upscaler named {upscaler_name or '<empty string>'}, using {upscaler.name} as a fallback")

+            else:

+                upscaler = upscalers[0]

 

-            upscaler = upscalers[0]

             im = upscaler.scaler.upscale(im, scale, upscaler.data_path)

 

         if im.width != w or im.height != h:

diff --git a/modules/scripts.py b/modules/scripts.py
index d661be4f..4d0bbd66 100644
--- a/modules/scripts.py
+++ b/modules/scripts.py
@@ -553,3 +553,15 @@ def IOComponent_init(self, *args, **kwargs):
 

 original_IOComponent_init = gr.components.IOComponent.__init__

 gr.components.IOComponent.__init__ = IOComponent_init

+

+

+def BlockContext_init(self, *args, **kwargs):

+    res = original_BlockContext_init(self, *args, **kwargs)

+

+    add_classes_to_gradio_component(self)

+

+    return res

+

+

+original_BlockContext_init = gr.blocks.BlockContext.__init__

+gr.blocks.BlockContext.__init__ = BlockContext_init

diff --git a/modules/shared.py b/modules/shared.py
index 11be3985..3ad0862b 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -640,7 +640,7 @@ mem_mon.start()
 

 

 def listfiles(dirname):

-    filenames = [os.path.join(dirname, x) for x in sorted(os.listdir(dirname)) if not x.startswith(".")]

+    filenames = [os.path.join(dirname, x) for x in sorted(os.listdir(dirname), key=str.lower) if not x.startswith(".")]

     return [file for file in filenames if os.path.isfile(file)]

 

 

diff --git a/modules/ui_common.py b/modules/ui_common.py
index 0f3427c8..3b11dcc8 100644
--- a/modules/ui_common.py
+++ b/modules/ui_common.py
@@ -145,8 +145,7 @@ Requested path was: {f}
             )

 

             if tabname != "extras":

-                with gr.Row():

-                    download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False, elem_id=f'download_files_{tabname}')

+                download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False, elem_id=f'download_files_{tabname}')

 

                 with gr.Group():

                     html_info = gr.HTML(elem_id=f'html_info_{tabname}', elem_classes="infotext")

diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py
index da7e79f0..b4a0d6ec 100644
--- a/modules/ui_extensions.py
+++ b/modules/ui_extensions.py
@@ -63,6 +63,9 @@ def check_updates(id_task, disable_list):
 

         try:

             ext.check_updates()

+        except FileNotFoundError as e:

+            if 'FETCH_HEAD' not in str(e):

+                raise

         except Exception:

             print(f"Error checking updates for {ext.name}:", file=sys.stderr)

             print(traceback.format_exc(), file=sys.stderr)

@@ -87,6 +90,8 @@ def extension_table():
     """

 

     for ext in extensions.extensions:

+        ext.read_info_from_repo()

+

         remote = f"""<a href="{html.escape(ext.remote or '')}" target="_blank">{html.escape("built-in" if ext.is_builtin else ext.remote or '')}</a>"""

 

         if ext.can_update:

diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py
index daea03d6..25eb464b 100644
--- a/modules/ui_extra_networks.py
+++ b/modules/ui_extra_networks.py
@@ -2,8 +2,10 @@ import glob
 import os.path

 import urllib.parse

 from pathlib import Path

+from PIL import PngImagePlugin

 

 from modules import shared

+from modules.images import read_info_from_image

 import gradio as gr

 import json

 import html

@@ -252,10 +254,10 @@ def create_ui(container, button, tabname):
 

     def toggle_visibility(is_visible):

         is_visible = not is_visible

-        return is_visible, gr.update(visible=is_visible)

+        return is_visible, gr.update(visible=is_visible), gr.update(variant=("secondary-down" if is_visible else "secondary"))

 

     state_visible = gr.State(value=False)

-    button.click(fn=toggle_visibility, inputs=[state_visible], outputs=[state_visible, container])

+    button.click(fn=toggle_visibility, inputs=[state_visible], outputs=[state_visible, container, button])

 

     def refresh():

         res = []

@@ -290,6 +292,7 @@ def setup_ui(ui, gallery):
 

         img_info = images[index if index >= 0 else 0]

         image = image_from_url_text(img_info)

+        geninfo, items = read_info_from_image(image)

 

         is_allowed = False

         for extra_page in ui.stored_extra_pages:

@@ -299,7 +302,12 @@ def setup_ui(ui, gallery):
 

         assert is_allowed, f'writing to {filename} is not allowed'

 

-        image.save(filename)

+        if geninfo:

+            pnginfo_data = PngImagePlugin.PngInfo()

+            pnginfo_data.add_text('parameters', geninfo)

+            image.save(filename, pnginfo=pnginfo_data)

+        else:

+            image.save(filename)

 

         return [page.create_html(ui.tabname) for page in ui.stored_extra_pages]

 

diff --git a/scripts/loopback.py b/scripts/loopback.py
index 9c388aa8..d3065fe6 100644
--- a/scripts/loopback.py
+++ b/scripts/loopback.py
@@ -54,15 +54,12 @@ class Script(scripts.Script):
                 return strength

 

             progress = loop / (loops - 1)

-            match denoising_curve:

-                case "Aggressive":

-                    strength = math.sin((progress) * math.pi * 0.5)

-

-                case "Lazy":

-                    strength = 1 - math.cos((progress) * math.pi * 0.5)

-

-                case _:

-                    strength = progress

+            if denoising_curve == "Aggressive":

+                strength = math.sin((progress) * math.pi * 0.5)

+            elif denoising_curve == "Lazy":

+                strength = 1 - math.cos((progress) * math.pi * 0.5)

+            else:

+                strength = progress

 

             change = (final_denoising_strength - initial_denoising_strength) * strength

             return initial_denoising_strength + change

diff --git a/style.css b/style.css
index 84405622..75c26b40 100644
--- a/style.css
+++ b/style.css
@@ -7,7 +7,7 @@
     --block-background-fill: transparent;

 }

 

-.block.padded{

+.block.padded:not(.gradio-accordion) {

     padding: 0 !important;

 }

 

@@ -54,10 +54,6 @@ div.compact{
     gap: 1em;

 }

 

-.gradio-dropdown ul.options{

-    z-index: 3000;

-}

-

 .gradio-dropdown label span:not(.has-info),

 .gradio-textbox label span:not(.has-info),

 .gradio-number label span:not(.has-info)

@@ -65,11 +61,30 @@ div.compact{
     margin-bottom: 0;

 }

 

+.gradio-dropdown ul.options{

+    z-index: 3000;

+    min-width: fit-content;

+    max-width: inherit;

+    white-space: nowrap;

+}

+

+.gradio-dropdown ul.options li.item {

+    padding: 0.05em 0;

+}

+

+.gradio-dropdown ul.options li.item.selected {

+    background-color: var(--neutral-100);

+}

+

+.dark .gradio-dropdown ul.options li.item.selected {

+    background-color: var(--neutral-900);

+}

+

 .gradio-dropdown div.wrap.wrap.wrap.wrap{

     box-shadow: 0 1px 2px 0 rgba(0, 0, 0, 0.05);

 }

 

-.gradio-dropdown .wrap-inner.wrap-inner.wrap-inner{

+.gradio-dropdown:not(.multiselect) .wrap-inner.wrap-inner.wrap-inner{

     flex-wrap: unset;

 }

 

@@ -123,6 +138,18 @@ div.gradio-html.min{
     border-radius: 0.5em;

 }

 

+.gradio-button.secondary-down{

+    background: var(--button-secondary-background-fill);

+    color: var(--button-secondary-text-color);

+}

+.gradio-button.secondary-down, .gradio-button.secondary-down:hover{

+    box-shadow: 1px 1px 1px rgba(0,0,0,0.25) inset, 0px 0px 3px rgba(0,0,0,0.15) inset;

+}

+.gradio-button.secondary-down:hover{

+    background: var(--button-secondary-background-fill-hover);

+    color: var(--button-secondary-text-color-hover);

+}

+

 .checkboxes-row{

     margin-bottom: 0.5em;

     margin-left: 0em;

@@ -507,6 +534,17 @@ div.dimensions-tools{
   background-color: rgba(0, 0, 0, 0.8);

 }

 

+#imageARPreview {

+    position: absolute;

+    top: 0px;

+    left: 0px;

+    border: 2px solid red;

+    background: rgba(255, 0, 0, 0.3);

+    z-index: 900;

+    pointer-events: none;

+    display: none;

+}

+

 /* context menu (ie for the generate button) */

 

 #context-menu{

diff --git a/webui.py b/webui.py
index 30f3e4a1..b570895f 100644
--- a/webui.py
+++ b/webui.py
@@ -265,9 +265,6 @@ def webui():
             inbrowser=cmd_opts.autolaunch,

             prevent_thread_lock=True

         )

-        for dep in shared.demo.dependencies:

-            dep['show_progress'] = False  # disable gradio css animation on component update

-

         # after initial launch, disable --autolaunch for subsequent restarts

         cmd_opts.autolaunch = False