Merge branch 'master' into notification-sound

Fixed grids saving to subdirectory when the setting is unchecked but "save images to subdirectory" was checked.

.gitignore

@@ -19,4 +19,6 @@ __pycache__
 /webui-user.sh
 /interrogate
 /user.css
-/.idea
+/.idea
+notification.mp3
+/SwinIR

README.md

@@ -1,7 +1,7 @@
 # Stable Diffusion web UI
 A browser interface based on Gradio library for Stable Diffusion.
 
-![](screenshot.png)
+![](txt2img_Screenshot.png)
 
 ## Features
 [Detailed feature showcase with images](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features):

javascript/dragdrop.js

@@ -68,13 +68,19 @@ window.addEventListener('paste', e => {
     if ( ! isValidImageList( files ) ) {
         return;
     }
-    [...gradioApp().querySelectorAll('input[type=file][accept="image/x-png,image/gif,image/jpeg"]')]
-        .filter(input => !input.matches('.\\!hidden input[type=file]'))
-        .forEach(input => {
-            input.files = files;
-            input.dispatchEvent(new Event('change'))
-        });
-    [...gradioApp().querySelectorAll('[data-testid="image"]')]
-        .filter(imgWrap => !imgWrap.closest('.\\!hidden'))
-        .forEach(imgWrap => dropReplaceImage( imgWrap, files ));
+
+    const visibleImageFields = [...gradioApp().querySelectorAll('[data-testid="image"]')]
+        .filter(el => uiElementIsVisible(el));
+    if ( ! visibleImageFields.length ) {
+        return;
+    }
+    
+    const firstFreeImageField = visibleImageFields
+        .filter(el => el.querySelector('input[type=file]'))?.[0];
+
+    dropReplaceImage(
+        firstFreeImageField ?
+        firstFreeImageField :
+        visibleImageFields[visibleImageFields.length - 1]
+    , files );
 });

javascript/hints.js

@@ -57,14 +57,13 @@ titles = {
 
     "Interrogate": "Reconstruct prompt from existing image and put it into the prompt field.",
 
-    "Images filename pattern": "Use following tags to define how filenames for images are chosen: [steps], [cfg], [prompt], [prompt_spaces], [width], [height], [sampler], [seed], [model_hash], [prompt_words], [date]; leave empty for default.",
-    "Directory name pattern": "Use following tags to define how subdirectories for images and grids are chosen: [steps], [cfg], [prompt], [prompt_spaces], [width], [height], [sampler], [seed], [model_hash], [prompt_words], [date]; leave empty for default.",
+    "Images filename pattern": "Use following tags to define how filenames for images are chosen: [steps], [cfg], [prompt], [prompt_spaces], [width], [height], [styles], [sampler], [seed], [model_hash], [prompt_words], [date], [datetime], [job_timestamp]; leave empty for default.",
+    "Directory name pattern": "Use following tags to define how subdirectories for images and grids are chosen: [steps], [cfg], [prompt], [prompt_spaces], [width], [height], [styles], [sampler], [seed], [model_hash], [prompt_words], [date], [datetime], [job_timestamp]; leave empty for default.",
     "Max prompt words": "Set the maximum number of words to be used in the [prompt_words] option; ATTENTION: If the words are too long, they may exceed the maximum length of the file path that the system can handle",
 
     "Loopback": "Process an image, use it as an input, repeat.",
     "Loops": "How many times to repeat processing an image and using it as input for the next iteration",
 
-
     "Style 1": "Style to apply; styles have components for both positive and negative prompts and apply to both",
     "Style 2": "Style to apply; styles have components for both positive and negative prompts and apply to both",
     "Apply style": "Insert selected styles into prompt fields",

javascript/notification.js

@@ -25,6 +25,9 @@ onUiUpdate(function(){
 
     lastHeadImg = headImg;
 
+    // play notification sound if available
+    gradioApp().querySelector('#audio_notification audio')?.play();
+
     if (document.hasFocus()) return;
 
     // Multiple copies of the images are in the DOM when one is selected. Dedup with a Set to get the real number generated.

javascript/ui.js

@@ -1,9 +1,8 @@
 // various functions for interation with ui.py not large enough to warrant putting them in separate files
 
 function selected_gallery_index(){
-    var gr = gradioApp()
-    var buttons = gradioApp().querySelectorAll(".gallery-item")
-    var button = gr.querySelector(".gallery-item.\\!ring-2")
+    var buttons = gradioApp().querySelectorAll('[style="display: block;"].tabitem .gallery-item')
+    var button = gradioApp().querySelector('[style="display: block;"].tabitem .gallery-item.\\!ring-2')
 
     var result = -1
     buttons.forEach(function(v, i){ if(v==button) { result = i } })

modules/generation_parameters_copypaste.py

@@ -1,9 +1,11 @@
-from collections import namedtuple
 import re
 import gradio as gr
 
-re_param = re.compile(r"\s*([\w ]+):\s*([^,]+)(?:,|$)")
+re_param_code = r"\s*([\w ]+):\s*([^,]+)(?:,|$)"
+re_param = re.compile(re_param_code)
+re_params = re.compile(r"^(?:" + re_param_code + "){3,}$")
 re_imagesize = re.compile(r"^(\d+)x(\d+)$")
+type_of_gr_update = type(gr.update())
 
 
 def parse_generation_parameters(x: str):
@@ -25,6 +27,10 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
     done_with_prompt = False
 
     *lines, lastline = x.strip().split("\n")
+    if not re_params.match(lastline):
+        lines.append(lastline)
+        lastline = ''
+
     for i, line in enumerate(lines):
         line = line.strip()
         if line.startswith("Negative prompt:"):
@@ -32,9 +38,9 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
             line = line[16:].strip()
 
         if done_with_prompt:
-            negative_prompt += line
+            negative_prompt += ("" if negative_prompt == "" else "\n") + line
         else:
-            prompt += line
+            prompt += ("" if prompt == "" else "\n") + line
 
     if len(prompt) > 0:
         res["Prompt"] = prompt
@@ -53,19 +59,21 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
     return res
 
 
-def connect_paste(button, d, input_comp, js=None):
-    items = []
-    outputs = []
-
+def connect_paste(button, paste_fields, input_comp, js=None):
     def paste_func(prompt):
         params = parse_generation_parameters(prompt)
         res = []
 
-        for key, output in zip(items, outputs):
-            v = params.get(key, None)
+        for output, key in paste_fields:
+            if callable(key):
+                v = key(params)
+            else:
+                v = params.get(key, None)
 
             if v is None:
                 res.append(gr.update())
+            elif isinstance(v, type_of_gr_update):
+                res.append(v)
             else:
                 try:
                     valtype = type(output.value)
@@ -76,13 +84,9 @@ def connect_paste(button, d, input_comp, js=None):
 
         return res
 
-    for k, v in d.items():
-        items.append(k)
-        outputs.append(v)
-
     button.click(
         fn=paste_func,
         _js=js,
         inputs=[input_comp],
-        outputs=outputs,
+        outputs=[x[0] for x in paste_fields],
     )

modules/images.py

@@ -290,10 +290,13 @@ def apply_filename_pattern(x, p, seed, prompt):
         x = x.replace("[cfg]", str(p.cfg_scale))
         x = x.replace("[width]", str(p.width))
         x = x.replace("[height]", str(p.height))
+        x = x.replace("[styles]", sanitize_filename_part(", ".join(p.styles), replace_spaces=False))
         x = x.replace("[sampler]", sanitize_filename_part(sd_samplers.samplers[p.sampler_index].name, replace_spaces=False))
 
     x = x.replace("[model_hash]", shared.sd_model.sd_model_hash)
     x = x.replace("[date]", datetime.date.today().isoformat())
+    x = x.replace("[datetime]", datetime.datetime.now().strftime("%Y%m%d%H%M%S"))
+    x = x.replace("[job_timestamp]", shared.state.job_timestamp)
 
     if cmd_opts.hide_ui_dir_config:
         x = re.sub(r'^[\\/]+|\.{2,}[\\/]+|[\\/]+\.{2,}', '', x)

modules/img2img.py

@@ -108,6 +108,8 @@ def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, pro
     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"
+
         process_batch(p, img2img_batch_input_dir, img2img_batch_output_dir, args)
 
         processed = Processed(p, [], p.seed, "")

modules/processing.py

@@ -406,7 +406,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
                 index_of_first_image = 1
 
             if opts.grid_save:
-                images.save_image(grid, p.outpath_grids, "grid", all_seeds[0], all_prompts[0], opts.grid_format, info=infotext(), short_filename=not opts.grid_extended_filename, p=p)
+                images.save_image(grid, p.outpath_grids, "grid", all_seeds[0], all_prompts[0], opts.grid_format, info=infotext(), short_filename=not opts.grid_extended_filename, p=p, grid=True)
 
     devices.torch_gc()
     return Processed(p, output_images, all_seeds[0], infotext(), subseed=all_subseeds[0], all_prompts=all_prompts, all_seeds=all_seeds, all_subseeds=all_subseeds, index_of_first_image=index_of_first_image)
@@ -488,6 +488,11 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
 
         self.sampler = samplers[self.sampler_index].constructor(self.sd_model)
         noise = create_random_tensors(samples.shape[1:], seeds=seeds, subseeds=subseeds, subseed_strength=subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self)
+
+        # GC now before running the next img2img to prevent running out of memory
+        x = None
+        devices.torch_gc()
+        
         samples = self.sampler.sample_img2img(self, samples, noise, conditioning, unconditional_conditioning, steps=self.steps)
 
         return samples

modules/scripts.py

@@ -119,6 +119,7 @@ class ScriptRunner:
                 continue
 
             for control in controls:
+                control.custom_script_source = os.path.basename(script.filename)
                 control.visible = False
 
             inputs += controls

modules/sd_hijack.py

@@ -201,7 +201,7 @@ class StableDiffusionModelHijack:
         def process_file(path, filename):
             name = os.path.splitext(filename)[0]
 
-            data = torch.load(path)
+            data = torch.load(path, map_location="cpu")
 
             # textual inversion embeddings
             if 'string_to_param' in data:
@@ -217,7 +217,7 @@ class StableDiffusionModelHijack:
                 if len(emb.shape) == 1:
                     emb = emb.unsqueeze(0)
 
-            self.word_embeddings[name] = emb.detach()
+            self.word_embeddings[name] = emb.detach().to(device)
             self.word_embeddings_checksums[name] = f'{const_hash(emb.reshape(-1)*100)&0xffff:04x}'
 
             ids = tokenizer([name], add_special_tokens=False)['input_ids'][0]
@@ -300,7 +300,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
         remade_batch_tokens = []
         id_start = self.wrapped.tokenizer.bos_token_id
         id_end = self.wrapped.tokenizer.eos_token_id
-        maxlen = self.wrapped.max_length - 2
+        maxlen = self.wrapped.max_length
         used_custom_terms = []
 
         cache = {}

modules/shared.py

@@ -4,6 +4,7 @@ import json
 import os
 import gradio as gr
 import tqdm
+import datetime
 
 import modules.artists
 from modules.paths import script_path, sd_path
@@ -65,6 +66,7 @@ class State:
     job = ""
     job_no = 0
     job_count = 0
+    job_timestamp = '0'
     sampling_step = 0
     sampling_steps = 0
     current_latent = None
@@ -78,6 +80,9 @@ class State:
         self.job_no += 1
         self.sampling_step = 0
         self.current_image_sampling_step = 0
+        
+    def get_job_timestamp(self):
+        return datetime.datetime.now().strftime("%Y%m%d%H%M%S")
 
 
 state = State()
@@ -116,7 +121,7 @@ def options_section(section_identifer, options_dict):
     return options_dict
 
 
-hide_dirs = {"visible": False} if cmd_opts.hide_ui_dir_config else None
+hide_dirs = {"visible": not cmd_opts.hide_ui_dir_config}
 
 options_templates = {}
 
@@ -307,6 +312,13 @@ class TotalTQDM:
             self.reset()
         self._tqdm.update()
 
+    def updateTotal(self, new_total):
+        if not opts.multiple_tqdm:
+            return
+        if self._tqdm is None:
+            self.reset()
+        self._tqdm.total=new_total
+
     def clear(self):
         if self._tqdm is not None:
             self._tqdm.close()

modules/ui.py

@@ -49,7 +49,6 @@ 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..." }
 .progress-bar { display:none!important; }
 .meta-text { display:none!important; }
 """
@@ -198,7 +197,7 @@ def check_progress_call(id_part):
 
         image = shared.state.current_image
 
-        if image is None or progress >= 1:
+        if image is None:
             image = gr.update(value=None)
         else:
             preview_visibility = gr_show(True)
@@ -413,6 +412,10 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
                 steps = gr.Slider(minimum=1, maximum=150, step=1, label="Sampling Steps", value=20)
                 sampler_index = gr.Radio(label='Sampling method', elem_id="txt2img_sampling", choices=[x.name for x in samplers], value=samplers[0].name, type="index")
 
+                with gr.Group():
+                    width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512)
+                    height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512)
+
                 with gr.Row():
                     restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1)
                     tiling = gr.Checkbox(label='Tiling', value=False)
@@ -428,10 +431,6 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
 
                 cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0)
 
-                with gr.Group():
-                    width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512)
-                    height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512)
-
                 seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs()
 
                 with gr.Group():
@@ -522,23 +521,25 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
                 ]
             )
 
-            txt2img_paste_fields = {
-                "Prompt": txt2img_prompt,
-                "Negative prompt": txt2img_negative_prompt,
-                "Steps": steps,
-                "Sampler": sampler_index,
-                "Face restoration": restore_faces,
-                "CFG scale": cfg_scale,
-                "Seed": seed,
-                "Size-1": width,
-                "Size-2": height,
-                "Batch size": batch_size,
-                "Variation seed": subseed,
-                "Variation seed strength": subseed_strength,
-                "Seed resize from-1": seed_resize_from_w,
-                "Seed resize from-2": seed_resize_from_h,
-                "Denoising strength": denoising_strength,
-            }
+            txt2img_paste_fields = [
+                (txt2img_prompt, "Prompt"),
+                (txt2img_negative_prompt, "Negative prompt"),
+                (steps, "Steps"),
+                (sampler_index, "Sampler"),
+                (restore_faces, "Face restoration"),
+                (cfg_scale, "CFG scale"),
+                (seed, "Seed"),
+                (width, "Size-1"),
+                (height, "Size-2"),
+                (batch_size, "Batch size"),
+                (subseed, "Variation seed"),
+                (subseed_strength, "Variation seed strength"),
+                (seed_resize_from_w, "Seed resize from-1"),
+                (seed_resize_from_h, "Seed resize from-2"),
+                (denoising_strength, "Denoising strength"),
+                (enable_hr, lambda d: "Denoising strength" in d),
+                (hr_options, lambda d: gr.Row.update(visible="Denoising strength" in d)),
+            ]
             modules.generation_parameters_copypaste.connect_paste(paste, txt2img_paste_fields, txt2img_prompt)
 
     with gr.Blocks(analytics_enabled=False) as img2img_interface:
@@ -563,13 +564,13 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
                     with gr.TabItem('Inpaint', id='inpaint'):
                         init_img_with_mask = gr.Image(label="Image for inpainting with mask",  show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool="sketch", image_mode="RGBA")
 
-                        init_img_inpaint = gr.Image(label="Image for img2img", show_label=False, source="upload", interactive=True, type="pil", visible=False)
-                        init_mask_inpaint = gr.Image(label="Mask", source="upload", interactive=True, type="pil", visible=False)
+                        init_img_inpaint = gr.Image(label="Image for img2img", show_label=False, source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_base")
+                        init_mask_inpaint = gr.Image(label="Mask", source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_mask")
 
                         mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4)
 
                         with gr.Row():
-                            mask_mode = gr.Radio(label="Mask mode", show_label=False, choices=["Draw mask", "Upload mask"], type="index", value="Draw mask")
+                            mask_mode = gr.Radio(label="Mask mode", show_label=False, choices=["Draw mask", "Upload mask"], type="index", value="Draw mask", elem_id="mask_mode")
                             inpainting_mask_invert = gr.Radio(label='Masking mode', show_label=False, choices=['Inpaint masked', 'Inpaint not masked'], value='Inpaint masked', type="index")
 
                         inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='fill', type="index")
@@ -579,9 +580,10 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
                             inpaint_full_res_padding = gr.Slider(label='Inpaint at full resolution padding, pixels', minimum=0, maximum=256, step=4, value=32)
 
                     with gr.TabItem('Batch img2img', id='batch'):
-                        gr.HTML("<p class=\"text-gray-500\">Process images in a directory on the same machine where the server is running.</p>")
-                        img2img_batch_input_dir = gr.Textbox(label="Input directory")
-                        img2img_batch_output_dir = gr.Textbox(label="Output directory")
+                        hidden = '<br>Disabled when launched with --hide-ui-dir-config.' if shared.cmd_opts.hide_ui_dir_config else ''
+                        gr.HTML(f"<p class=\"text-gray-500\">Process images in a directory on the same machine where the server is running.{hidden}</p>")
+                        img2img_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs)
+                        img2img_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs)
 
                 with gr.Row():
                     resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", show_label=False, choices=["Just resize", "Crop and resize", "Resize and fill"], type="index", value="Just resize")
@@ -589,6 +591,10 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
                 steps = gr.Slider(minimum=1, maximum=150, step=1, label="Sampling Steps", value=20)
                 sampler_index = gr.Radio(label='Sampling method', choices=[x.name for x in samplers_for_img2img], value=samplers_for_img2img[0].name, type="index")
 
+                with gr.Group():
+                    width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512)
+                    height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512)
+
                 with gr.Row():
                     restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1)
                     tiling = gr.Checkbox(label='Tiling', value=False)
@@ -601,10 +607,6 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
                     cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0)
                     denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.75)
 
-                with gr.Group():
-                    width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512)
-                    height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512)
-
                 seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs()
 
                 with gr.Group():
@@ -741,23 +743,23 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
                     outputs=[prompt, negative_prompt, style1, style2],
                 )
 
-            img2img_paste_fields = {
-                "Prompt": img2img_prompt,
-                "Negative prompt": img2img_negative_prompt,
-                "Steps": steps,
-                "Sampler": sampler_index,
-                "Face restoration": restore_faces,
-                "CFG scale": cfg_scale,
-                "Seed": seed,
-                "Size-1": width,
-                "Size-2": height,
-                "Batch size": batch_size,
-                "Variation seed": subseed,
-                "Variation seed strength": subseed_strength,
-                "Seed resize from-1": seed_resize_from_w,
-                "Seed resize from-2": seed_resize_from_h,
-                "Denoising strength": denoising_strength,
-            }
+            img2img_paste_fields = [
+                (img2img_prompt, "Prompt"),
+                (img2img_negative_prompt, "Negative prompt"),
+                (steps, "Steps"),
+                (sampler_index, "Sampler"),
+                (restore_faces, "Face restoration"),
+                (cfg_scale, "CFG scale"),
+                (seed, "Seed"),
+                (width, "Size-1"),
+                (height, "Size-2"),
+                (batch_size, "Batch size"),
+                (subseed, "Variation seed"),
+                (subseed_strength, "Variation seed strength"),
+                (seed_resize_from_w, "Seed resize from-1"),
+                (seed_resize_from_h, "Seed resize from-2"),
+                (denoising_strength, "Denoising strength"),
+            ]
             modules.generation_parameters_copypaste.connect_paste(paste, img2img_paste_fields, img2img_prompt)
 
     with gr.Blocks(analytics_enabled=False) as extras_interface:
@@ -968,6 +970,9 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
             for interface, label, ifid in interfaces:
                 with gr.TabItem(label, id=ifid):
                     interface.render()
+        
+        if os.path.exists(os.path.join(script_path, "notification.mp3")):
+            audio_notification = gr.Audio(interactive=False, value=os.path.join(script_path, "notification.mp3"), elem_id="audio_notification", visible=False)
 
         text_settings = gr.Textbox(elem_id="settings_json", value=lambda: opts.dumpjson(), visible=False)
         settings_submit.click(
@@ -976,18 +981,21 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
             outputs=[result, text_settings],
         )
 
+        paste_field_names = ['Prompt', 'Negative prompt', 'Steps', 'Face restoration', 'Seed', 'Size-1', 'Size-2']
+        txt2img_fields = [field for field,name in txt2img_paste_fields if name in paste_field_names]
+        img2img_fields = [field for field,name in img2img_paste_fields if name in paste_field_names]
         send_to_img2img.click(
-            fn=lambda x: (image_from_url_text(x)),
-            _js="extract_image_from_gallery_img2img",
-            inputs=[txt2img_gallery],
-            outputs=[init_img],
+            fn=lambda img, *args: (image_from_url_text(img),*args),
+            _js="(gallery, ...args) => [extract_image_from_gallery_img2img(gallery), ...args]",
+            inputs=[txt2img_gallery] + txt2img_fields,
+            outputs=[init_img] + img2img_fields,
         )
 
         send_to_inpaint.click(
-            fn=lambda x: (image_from_url_text(x)),
-            _js="extract_image_from_gallery_inpaint",
-            inputs=[txt2img_gallery],
-            outputs=[init_img_with_mask],
+            fn=lambda x, *args: (image_from_url_text(x), *args),
+            _js="(gallery, ...args) => [extract_image_from_gallery_inpaint(gallery), ...args]",
+            inputs=[txt2img_gallery] + txt2img_fields,
+            outputs=[init_img_with_mask] + img2img_fields,
         )
 
         img2img_send_to_img2img.click(
@@ -1039,12 +1047,21 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
         def apply_field(obj, field, condition=None):
             key = path + "/" + field
 
+            if getattr(obj,'custom_script_source',None) is not None:
+              key = 'customscript/' + obj.custom_script_source + '/' + key
+            
+            if getattr(obj, 'do_not_save_to_config', False):
+                return
+            
             saved_value = ui_settings.get(key, None)
             if saved_value is None:
                 ui_settings[key] = getattr(obj, field)
             elif condition is None or condition(saved_value):
                 setattr(obj, field, saved_value)
 
+        if type(x) in [gr.Slider, gr.Radio, gr.Checkbox, gr.Textbox, gr.Number] and x.visible:
+            apply_field(x, 'visible')
+
         if type(x) == gr.Slider:
             apply_field(x, 'value')
             apply_field(x, 'minimum')
@@ -1054,6 +1071,15 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
         if type(x) == gr.Radio:
             apply_field(x, 'value', lambda val: val in x.choices)
 
+        if type(x) == gr.Checkbox:
+            apply_field(x, 'value')
+
+        if type(x) == gr.Textbox:
+            apply_field(x, 'value')
+        
+        if type(x) == gr.Number:
+            apply_field(x, 'value')
+        
     visit(txt2img_interface, loadsave, "txt2img")
     visit(img2img_interface, loadsave, "img2img")
     visit(extras_interface, loadsave, "extras")

requirements.txt

@@ -1,22 +1,20 @@
-transformers
-diffusers
 basicsr
-gfpgan
-gradio
-numpy
-Pillow
-realesrgan
-torch
-transformers
-omegaconf
-pytorch_lightning
 diffusers
-invisible-watermark
-scikit-image>=0.19
+fairscale==0.4.4
 fonts
 font-roboto
+gfpgan
+gradio
+invisible-watermark
 git+https://github.com/crowsonkb/k-diffusion.git
+numpy
+omegaconf
+piexif
+Pillow
+pytorch_lightning
+realesrgan
+scikit-image>=0.19
 git+https://github.com/TencentARC/GFPGAN.git@8d2447a2d918f8eba5a4a01463fd48e45126a379
 timm==0.4.12
-fairscale==0.4.4
-piexif
+transformers
+torch

script.js

@@ -2,24 +2,61 @@ function gradioApp(){
     return document.getElementsByTagName('gradio-app')[0].shadowRoot;
 }
 
+function get_uiCurrentTab() {
+    return gradioApp().querySelector('.tabs button:not(.border-transparent)')
+}
+
 uiUpdateCallbacks = []
+uiTabChangeCallbacks = []
+let uiCurrentTab = null
+
 function onUiUpdate(callback){
     uiUpdateCallbacks.push(callback)
 }
+function onUiTabChange(callback){
+    uiTabChangeCallbacks.push(callback)
+}
 
-function uiUpdate(root){
-	uiUpdateCallbacks.forEach(function(x){
-        try {
-            x()
-        } catch (e) {
-            (console.error || console.log).call(console, e.message, e);
-        }
-	})
+function runCallback(x){
+    try {
+        x()
+    } catch (e) {
+        (console.error || console.log).call(console, e.message, e);
+    }
+}
+function executeCallbacks(queue) {
+    queue.forEach(runCallback)
 }
 
 document.addEventListener("DOMContentLoaded", function() {
     var mutationObserver = new MutationObserver(function(m){
-        uiUpdate(gradioApp());
+        executeCallbacks(uiUpdateCallbacks);
+        const newTab = get_uiCurrentTab();
+        if ( newTab && ( newTab !== uiCurrentTab ) ) {
+            uiCurrentTab = newTab;
+            executeCallbacks(uiTabChangeCallbacks);
+        }
     });
     mutationObserver.observe( gradioApp(), { childList:true, subtree:true })
 });
+
+/**
+ * checks that a UI element is not in another hidden element or tab content
+ */
+function uiElementIsVisible(el) {
+    let isVisible = !el.closest('.\\!hidden');
+    if ( ! isVisible ) {
+        return false;
+    }
+
+    while( isVisible = el.closest('.tabitem')?.style.display !== 'none' ) {
+        if ( ! isVisible ) {
+            return false;
+        } else if ( el.parentElement ) {
+            el = el.parentElement
+        } else {
+            break;
+        }
+    }
+    return isVisible;
+}

scripts/img2imgalt.py

@@ -59,7 +59,55 @@ def find_noise_for_image(p, cond, uncond, cfg_scale, steps):
     return x / x.std()
 
 
-Cached = namedtuple("Cached", ["noise", "cfg_scale", "steps", "latent", "original_prompt", "original_negative_prompt"])
+Cached = namedtuple("Cached", ["noise", "cfg_scale", "steps", "latent", "original_prompt", "original_negative_prompt", "sigma_adjustment"])
+
+
+# Based on changes suggested by briansemrau in https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/736
+def find_noise_for_image_sigma_adjustment(p, cond, uncond, cfg_scale, steps):
+    x = p.init_latent
+
+    s_in = x.new_ones([x.shape[0]])
+    dnw = K.external.CompVisDenoiser(shared.sd_model)
+    sigmas = dnw.get_sigmas(steps).flip(0)
+
+    shared.state.sampling_steps = steps
+
+    for i in trange(1, len(sigmas)):
+        shared.state.sampling_step += 1
+
+        x_in = torch.cat([x] * 2)
+        sigma_in = torch.cat([sigmas[i - 1] * s_in] * 2)
+        cond_in = torch.cat([uncond, cond])
+
+        c_out, c_in = [K.utils.append_dims(k, x_in.ndim) for k in dnw.get_scalings(sigma_in)]
+
+        if i == 1:
+            t = dnw.sigma_to_t(torch.cat([sigmas[i] * s_in] * 2))
+        else:
+            t = dnw.sigma_to_t(sigma_in)
+
+        eps = shared.sd_model.apply_model(x_in * c_in, t, cond=cond_in)
+        denoised_uncond, denoised_cond = (x_in + eps * c_out).chunk(2)
+
+        denoised = denoised_uncond + (denoised_cond - denoised_uncond) * cfg_scale
+
+        if i == 1:
+            d = (x - denoised) / (2 * sigmas[i])
+        else:
+            d = (x - denoised) / sigmas[i - 1]
+
+        dt = sigmas[i] - sigmas[i - 1]
+        x = x + d * dt
+
+        sd_samplers.store_latent(x)
+
+        # This shouldn't be necessary, but solved some VRAM issues
+        del x_in, sigma_in, cond_in, c_out, c_in, t,
+        del eps, denoised_uncond, denoised_cond, denoised, d, dt
+
+    shared.state.nextjob()
+
+    return x / sigmas[-1]
 
 
 class Script(scripts.Script):
@@ -78,9 +126,10 @@ class Script(scripts.Script):
         cfg = gr.Slider(label="Decode CFG scale", minimum=0.0, maximum=15.0, step=0.1, value=1.0)
         st = gr.Slider(label="Decode steps", minimum=1, maximum=150, step=1, value=50)
         randomness = gr.Slider(label="Randomness", minimum=0.0, maximum=1.0, step=0.01, value=0.0)
-        return [original_prompt, original_negative_prompt, cfg, st, randomness]
+        sigma_adjustment = gr.Checkbox(label="Sigma adjustment for finding noise for image", value=False)
+        return [original_prompt, original_negative_prompt, cfg, st, randomness, sigma_adjustment]
 
-    def run(self, p, original_prompt, original_negative_prompt, cfg, st, randomness):
+    def run(self, p, original_prompt, original_negative_prompt, cfg, st, randomness, sigma_adjustment):
         p.batch_size = 1
         p.batch_count = 1
 
@@ -88,7 +137,10 @@ class Script(scripts.Script):
         def sample_extra(conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength):
             lat = (p.init_latent.cpu().numpy() * 10).astype(int)
 
-            same_params = self.cache is not None and self.cache.cfg_scale == cfg and self.cache.steps == st and self.cache.original_prompt == original_prompt and self.cache.original_negative_prompt == original_negative_prompt
+            same_params = self.cache is not None and self.cache.cfg_scale == cfg and self.cache.steps == st \
+                                and self.cache.original_prompt == original_prompt \
+                                and self.cache.original_negative_prompt == original_negative_prompt \
+                                and self.cache.sigma_adjustment == sigma_adjustment
             same_everything = same_params and self.cache.latent.shape == lat.shape and np.abs(self.cache.latent-lat).sum() < 100
 
             if same_everything:
@@ -97,8 +149,11 @@ class Script(scripts.Script):
                 shared.state.job_count += 1
                 cond = p.sd_model.get_learned_conditioning(p.batch_size * [original_prompt])
                 uncond = p.sd_model.get_learned_conditioning(p.batch_size * [original_negative_prompt])
-                rec_noise = find_noise_for_image(p, cond, uncond, cfg, st)
-                self.cache = Cached(rec_noise, cfg, st, lat, original_prompt, original_negative_prompt)
+                if sigma_adjustment:
+                    rec_noise = find_noise_for_image_sigma_adjustment(p, cond, uncond, cfg, st)
+                else:
+                    rec_noise = find_noise_for_image(p, cond, uncond, cfg, st)
+                self.cache = Cached(rec_noise, cfg, st, lat, original_prompt, original_negative_prompt, sigma_adjustment)
 
             rand_noise = processing.create_random_tensors(p.init_latent.shape[1:], [p.seed + x + 1 for x in range(p.init_latent.shape[0])])
             
@@ -121,6 +176,7 @@ class Script(scripts.Script):
         p.extra_generation_params["Decode CFG scale"] = cfg
         p.extra_generation_params["Decode steps"] = st
         p.extra_generation_params["Randomness"] = randomness
+        p.extra_generation_params["Sigma Adjustment"] = sigma_adjustment
 
         processed = processing.process_images(p)
 

scripts/xy_grid.py

@@ -141,10 +141,11 @@ class Script(scripts.Script):
             y_values = gr.Textbox(label="Y values", visible=False, lines=1)
         
         draw_legend = gr.Checkbox(label='Draw legend', value=True)
-            
-        return [x_type, x_values, y_type, y_values, draw_legend]
+        no_fixed_seeds = gr.Checkbox(label='Keep -1 for seeds', value=False)
 
-    def run(self, p, x_type, x_values, y_type, y_values, draw_legend):
+        return [x_type, x_values, y_type, y_values, draw_legend, no_fixed_seeds]
+
+    def run(self, p, x_type, x_values, y_type, y_values, draw_legend, no_fixed_seeds):
         modules.processing.fix_seed(p)
         p.batch_size = 1
 
@@ -169,7 +170,7 @@ class Script(scripts.Script):
                         end   = int(mc.group(2))
                         num   = int(mc.group(3)) if mc.group(3) is not None else 1
                         
-                        valslist_ext += [int(x) for x in np.linspace(start = start, stop = end, num = num).tolist()]
+                        valslist_ext += [int(x) for x in np.linspace(start=start, stop=end, num=num).tolist()]
                     else:
                         valslist_ext.append(val)
 
@@ -191,7 +192,7 @@ class Script(scripts.Script):
                         end   = float(mc.group(2))
                         num   = int(mc.group(3)) if mc.group(3) is not None else 1
                         
-                        valslist_ext += np.linspace(start = start, stop = end, num = num).tolist()
+                        valslist_ext += np.linspace(start=start, stop=end, num=num).tolist()
                     else:
                         valslist_ext.append(val)
 
@@ -207,6 +208,26 @@ class Script(scripts.Script):
         y_opt = axis_options[y_type]
         ys = process_axis(y_opt, y_values)
 
+        def fix_axis_seeds(axis_opt, axis_list):
+            if axis_opt.label == 'Seed':
+                return [int(random.randrange(4294967294)) if val is None or val == '' or val == -1 else val for val in axis_list]
+            else:
+                return axis_list
+
+        if not no_fixed_seeds:
+            xs = fix_axis_seeds(x_opt, xs)
+            ys = fix_axis_seeds(y_opt, ys)
+
+        if x_opt.label == 'Steps':
+            total_steps = sum(xs) * len(ys)
+        elif y_opt.label == 'Steps':
+            total_steps = sum(ys) * len(xs)
+        else:
+            total_steps = p.steps * len(xs) * len(ys)
+
+        print(f"X/Y plot will create {len(xs) * len(ys) * p.n_iter} images on a {len(xs)}x{len(ys)} grid. (Total steps to process: {total_steps * p.n_iter})")
+        shared.total_tqdm.updateTotal(total_steps * p.n_iter)
+
         def cell(x, y):
             pc = copy(p)
             x_opt.apply(pc, x, xs)

webui.bat

@@ -3,6 +3,8 @@
 if not defined PYTHON (set PYTHON=python)
 if not defined VENV_DIR (set VENV_DIR=venv)
 
+set ERROR_REPORTING=FALSE
+
 mkdir tmp 2>NUL
 
 %PYTHON% -c "" >tmp/stdout.txt 2>tmp/stderr.txt

webui.py

@@ -50,6 +50,7 @@ def wrap_gradio_gpu_call(func):
         shared.state.sampling_step = 0
         shared.state.job_count = -1
         shared.state.job_no = 0
+        shared.state.job_timestamp = shared.state.get_job_timestamp()
         shared.state.current_latent = None
         shared.state.current_image = None
         shared.state.current_image_sampling_step = 0

webui.sh

@@ -41,6 +41,9 @@ then
     venv_dir="venv"
 fi
 
+# Disable sentry logging
+export ERROR_REPORTING=FALSE
+
 # Do not reinstall existing pip packages on Debian/Ubuntu
 export PIP_IGNORE_INSTALLED=0