merge dev

extensions-builtin/Lora/networks.py

@@ -260,11 +260,11 @@ def load_networks(names, te_multipliers=None, unet_multipliers=None, dyn_dims=No
 
     loaded_networks.clear()
 
-    networks_on_disk = [available_network_aliases.get(name, None) for name in names]
+    networks_on_disk = [available_networks.get(name, None) if name.lower() in forbidden_network_aliases else available_network_aliases.get(name, None) for name in names]
     if any(x is None for x in networks_on_disk):
         list_available_networks()
 
-        networks_on_disk = [available_network_aliases.get(name, None) for name in names]
+        networks_on_disk = [available_networks.get(name, None) if name.lower() in forbidden_network_aliases else available_network_aliases.get(name, None) for name in names]
 
     failed_to_load_networks = []
 

extensions-builtin/canvas-zoom-and-pan/javascript/zoom.js

@@ -218,6 +218,8 @@ onUiLoaded(async() => {
         canvas_hotkey_fullscreen: "KeyS",
         canvas_hotkey_move: "KeyF",
         canvas_hotkey_overlap: "KeyO",
+        canvas_hotkey_shrink_brush: "KeyQ",
+        canvas_hotkey_grow_brush: "KeyW",
         canvas_disabled_functions: [],
         canvas_show_tooltip: true,
         canvas_auto_expand: true,
@@ -227,6 +229,8 @@ onUiLoaded(async() => {
     const functionMap = {
         "Zoom": "canvas_hotkey_zoom",
         "Adjust brush size": "canvas_hotkey_adjust",
+        "Hotkey shrink brush": "canvas_hotkey_shrink_brush",
+        "Hotkey enlarge brush": "canvas_hotkey_grow_brush",
         "Moving canvas": "canvas_hotkey_move",
         "Fullscreen": "canvas_hotkey_fullscreen",
         "Reset Zoom": "canvas_hotkey_reset",
@@ -686,7 +690,9 @@ onUiLoaded(async() => {
             const hotkeyActions = {
                 [hotkeysConfig.canvas_hotkey_reset]: resetZoom,
                 [hotkeysConfig.canvas_hotkey_overlap]: toggleOverlap,
-                [hotkeysConfig.canvas_hotkey_fullscreen]: fitToScreen
+                [hotkeysConfig.canvas_hotkey_fullscreen]: fitToScreen,
+                [hotkeysConfig.canvas_hotkey_shrink_brush]: () => adjustBrushSize(elemId, 10),
+                [hotkeysConfig.canvas_hotkey_grow_brush]: () => adjustBrushSize(elemId, -10)
             };
 
             const action = hotkeyActions[event.code];

extensions-builtin/canvas-zoom-and-pan/scripts/hotkey_config.py

@@ -4,6 +4,8 @@ from modules import shared
 shared.options_templates.update(shared.options_section(('canvas_hotkey', "Canvas Hotkeys"), {
     "canvas_hotkey_zoom": shared.OptionInfo("Alt", "Zoom canvas", gr.Radio, {"choices": ["Shift","Ctrl", "Alt"]}).info("If you choose 'Shift' you cannot scroll horizontally, 'Alt' can cause a little trouble in firefox"),
     "canvas_hotkey_adjust": shared.OptionInfo("Ctrl", "Adjust brush size", gr.Radio, {"choices": ["Shift","Ctrl", "Alt"]}).info("If you choose 'Shift' you cannot scroll horizontally, 'Alt' can cause a little trouble in firefox"),
+    "canvas_hotkey_shrink_brush": shared.OptionInfo("Q", "Shrink the brush size"),
+    "canvas_hotkey_grow_brush": shared.OptionInfo("W", "Enlarge the brush size"),
     "canvas_hotkey_move": shared.OptionInfo("F", "Moving the canvas").info("To work correctly in firefox, turn off 'Automatically search the page text when typing' in the browser settings"),
     "canvas_hotkey_fullscreen": shared.OptionInfo("S", "Fullscreen Mode, maximizes the picture so that it fits into the screen and stretches it to its full width "),
     "canvas_hotkey_reset": shared.OptionInfo("R", "Reset zoom and canvas positon"),
@@ -11,5 +13,5 @@ shared.options_templates.update(shared.options_section(('canvas_hotkey', "Canvas
     "canvas_show_tooltip": shared.OptionInfo(True, "Enable tooltip on the canvas"),
     "canvas_auto_expand": shared.OptionInfo(True, "Automatically expands an image that does not fit completely in the canvas area, similar to manually pressing the S and R buttons"),
     "canvas_blur_prompt": shared.OptionInfo(False, "Take the focus off the prompt when working with a canvas"),
-    "canvas_disabled_functions": shared.OptionInfo(["Overlap"], "Disable function that you don't use", gr.CheckboxGroup, {"choices": ["Zoom","Adjust brush size", "Moving canvas","Fullscreen","Reset Zoom","Overlap"]}),
+    "canvas_disabled_functions": shared.OptionInfo(["Overlap"], "Disable function that you don't use", gr.CheckboxGroup, {"choices": ["Zoom","Adjust brush size","Hotkey enlarge brush","Hotkey shrink brush","Moving canvas","Fullscreen","Reset Zoom","Overlap"]}),
 }))

modules/dat_model.py

+import os
+
+from modules import modelloader, errors
+from modules.shared import cmd_opts, opts
+from modules.upscaler import Upscaler, UpscalerData
+from modules.upscaler_utils import upscale_with_model
+
+
+class UpscalerDAT(Upscaler):
+    def __init__(self, user_path):
+        self.name = "DAT"
+        self.user_path = user_path
+        self.scalers = []
+        super().__init__()
+
+        for file in self.find_models(ext_filter=[".pt", ".pth"]):
+            name = modelloader.friendly_name(file)
+            scaler_data = UpscalerData(name, file, upscaler=self, scale=None)
+            self.scalers.append(scaler_data)
+
+        for model in get_dat_models(self):
+            if model.name in opts.dat_enabled_models:
+                self.scalers.append(model)
+
+    def do_upscale(self, img, path):
+        try:
+            info = self.load_model(path)
+        except Exception:
+            errors.report(f"Unable to load DAT model {path}", exc_info=True)
+            return img
+
+        model_descriptor = modelloader.load_spandrel_model(
+            info.local_data_path,
+            device=self.device,
+            prefer_half=(not cmd_opts.no_half and not cmd_opts.upcast_sampling),
+            expected_architecture="DAT",
+        )
+        return upscale_with_model(
+            model_descriptor,
+            img,
+            tile_size=opts.DAT_tile,
+            tile_overlap=opts.DAT_tile_overlap,
+        )
+
+    def load_model(self, path):
+        for scaler in self.scalers:
+            if scaler.data_path == path:
+                if scaler.local_data_path.startswith("http"):
+                    scaler.local_data_path = modelloader.load_file_from_url(
+                        scaler.data_path,
+                        model_dir=self.model_download_path,
+                    )
+                if not os.path.exists(scaler.local_data_path):
+                    raise FileNotFoundError(f"DAT data missing: {scaler.local_data_path}")
+                return scaler
+        raise ValueError(f"Unable to find model info: {path}")
+
+
+def get_dat_models(scaler):
+    return [
+        UpscalerData(
+            name="DAT x2",
+            path="https://github.com/n0kovo/dat_upscaler_models/raw/main/DAT/DAT_x2.pth",
+            scale=2,
+            upscaler=scaler,
+        ),
+        UpscalerData(
+            name="DAT x3",
+            path="https://github.com/n0kovo/dat_upscaler_models/raw/main/DAT/DAT_x3.pth",
+            scale=3,
+            upscaler=scaler,
+        ),
+        UpscalerData(
+            name="DAT x4",
+            path="https://github.com/n0kovo/dat_upscaler_models/raw/main/DAT/DAT_x4.pth",
+            scale=4,
+            upscaler=scaler,
+        ),
+    ]

modules/devices.py

@@ -164,7 +164,11 @@ def manual_cast_forward(target_dtype):
 
 @contextlib.contextmanager
 def manual_cast(target_dtype):
+    applied = False
     for module_type in patch_module_list:
+        if hasattr(module_type, "org_forward"):
+            continue
+        applied = True
         org_forward = module_type.forward
         if module_type == torch.nn.MultiheadAttention and has_xpu():
             module_type.forward = manual_cast_forward(torch.float32)
@@ -174,8 +178,11 @@ def manual_cast(target_dtype):
     try:
         yield None
     finally:
+        if applied:
             for module_type in patch_module_list:
+                if hasattr(module_type, "org_forward"):
                     module_type.forward = module_type.org_forward
+                    delattr(module_type, "org_forward")
 
 
 def autocast(disable=False):

modules/extensions.py

@@ -224,13 +224,16 @@ def list_extensions():
 
     # check for requirements
     for extension in extensions:
+        if not extension.enabled:
+            continue
+
         for req in extension.metadata.requires:
             required_extension = loaded_extensions.get(req)
             if required_extension is None:
                 errors.report(f'Extension "{extension.name}" requires "{req}" which is not installed.', exc_info=False)
                 continue
 
-            if not extension.enabled:
+            if not required_extension.enabled:
                 errors.report(f'Extension "{extension.name}" requires "{required_extension.name}" which is disabled.', exc_info=False)
                 continue
 

modules/images.py

@@ -321,7 +321,7 @@ def resize_image(resize_mode, im, width, height, upscaler_name=None):
     return res
 
 
-invalid_filename_chars = '<>:"/\\|?*\n\r\t'
+invalid_filename_chars = '#<>:"/\\|?*\n\r\t'
 invalid_filename_prefix = ' '
 invalid_filename_postfix = ' .'
 re_nonletters = re.compile(r'[\s' + string.punctuation + ']+')

modules/infotext_utils.py

@@ -230,7 +230,7 @@ def restore_old_hires_fix_params(res):
     res['Hires resize-2'] = height
 
 
-def parse_generation_parameters(x: str):
+def parse_generation_parameters(x: str, skip_fields: list[str] | None = None):
     """parses generation parameters string, the one you see in text field under the picture in UI:
 ```
 girl with an artist's beret, determined, blue eyes, desert scene, computer monitors, heavy makeup, by Alphonse Mucha and Charlie Bowater, ((eyeshadow)), (coquettish), detailed, intricate
@@ -240,6 +240,8 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
 
     returns a dict with field values
     """
+    if skip_fields is None:
+        skip_fields = shared.opts.infotext_skip_pasting
 
     res = {}
 
@@ -356,8 +358,8 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
 
     infotext_versions.backcompat(res)
 
-    skip = set(shared.opts.infotext_skip_pasting)
-    res = {k: v for k, v in res.items() if k not in skip}
+    for key in skip_fields:
+        res.pop(key, None)
 
     return res
 

modules/postprocessing.py

@@ -62,8 +62,6 @@ def run_postprocessing(extras_mode, image, image_folder, input_dir, output_dir,
         else:
             image_data = image_placeholder
 
-        shared.state.assign_current_image(image_data)
-
         parameters, existing_pnginfo = images.read_info_from_image(image_data)
         if parameters:
             existing_pnginfo["parameters"] = parameters
@@ -92,6 +90,8 @@ def run_postprocessing(extras_mode, image, image_folder, input_dir, output_dir,
                 pp.image.info = existing_pnginfo
                 pp.image.info["postprocessing"] = infotext
 
+            shared.state.assign_current_image(pp.image)
+
             if save_output:
                 fullfn, _ = images.save_image(pp.image, path=outpath, basename=basename, extension=opts.samples_format, info=infotext, short_filename=True, no_prompt=True, grid=False, pnginfo_section_name="extras", existing_info=existing_pnginfo, forced_filename=forced_filename, suffix=suffix)
 

modules/processing.py

@@ -1029,6 +1029,11 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
 
                 image = apply_overlay(image, p.paste_to, overlay_image)
 
+                if p.scripts is not None:
+                    pp = scripts.PostprocessImageArgs(image)
+                    p.scripts.postprocess_image_after_composite(p, pp)
+                    image = pp.image
+
                 if save_samples:
                     images.save_image(image, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p)
 
@@ -1227,8 +1232,11 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
             if not state.processing_has_refined_job_count:
                 if state.job_count == -1:
                     state.job_count = self.n_iter
-
-                shared.total_tqdm.updateTotal((self.steps + (self.hr_second_pass_steps or self.steps)) * state.job_count)
+                if getattr(self, 'txt2img_upscale', False):
+                    total_steps = (self.hr_second_pass_steps or self.steps) * state.job_count
+                else:
+                    total_steps = (self.steps + (self.hr_second_pass_steps or self.steps)) * state.job_count
+                shared.total_tqdm.updateTotal(total_steps)
                 state.job_count = state.job_count * 2
                 state.processing_has_refined_job_count = True
 

modules/processing_scripts/seed.py

@@ -6,6 +6,7 @@ from modules import scripts, ui, errors
 from modules.infotext_utils import PasteField
 from modules.shared import cmd_opts
 from modules.ui_components import ToolButton
+from modules import infotext_utils
 
 
 class ScriptSeed(scripts.ScriptBuiltinUI):
@@ -77,7 +78,6 @@ class ScriptSeed(scripts.ScriptBuiltinUI):
             p.seed_resize_from_h = seed_resize_from_h
 
 
-
 def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info: gr.Textbox, is_subseed):
     """ Connects a 'reuse (sub)seed' button's click event so that it copies last used
         (sub)seed value from generation info the to the seed field. If copying subseed and subseed strength
@@ -85,21 +85,14 @@ def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info:
 
     def copy_seed(gen_info_string: str, index):
         res = -1
-
         try:
             gen_info = json.loads(gen_info_string)
-            index -= gen_info.get('index_of_first_image', 0)
-
-            if is_subseed and gen_info.get('subseed_strength', 0) > 0:
-                all_subseeds = gen_info.get('all_subseeds', [-1])
-                res = all_subseeds[index if 0 <= index < len(all_subseeds) else 0]
-            else:
-                all_seeds = gen_info.get('all_seeds', [-1])
-                res = all_seeds[index if 0 <= index < len(all_seeds) else 0]
-
-        except json.decoder.JSONDecodeError:
+            infotext = gen_info.get('infotexts')[index]
+            gen_parameters = infotext_utils.parse_generation_parameters(infotext, [])
+            res = int(gen_parameters.get('Variation seed' if is_subseed else 'Seed', -1))
+        except Exception:
             if gen_info_string:
-                errors.report(f"Error parsing JSON generation info: {gen_info_string}")
+                errors.report(f"Error retrieving seed from generation info: {gen_info_string}", exc_info=True)
 
         return [res, gr.update()]
 

modules/scripts.py

@@ -262,6 +262,15 @@ class Script:
 
         pass
 
+    def postprocess_image_after_composite(self, p, pp: PostprocessImageArgs, *args):
+        """
+        Called for every image after it has been generated.
+        Same as postprocess_image but after inpaint_full_res composite
+        So that it operates on the full image instead of the inpaint_full_res crop region.
+        """
+
+        pass
+
     def postprocess(self, p, processed, *args):
         """
         This function is called after processing ends for AlwaysVisible scripts.
@@ -856,6 +865,14 @@ class ScriptRunner:
             except Exception:
                 errors.report(f"Error running postprocess_image: {script.filename}", exc_info=True)
 
+    def postprocess_image_after_composite(self, p, pp: PostprocessImageArgs):
+        for script in self.alwayson_scripts:
+            try:
+                script_args = p.script_args[script.args_from:script.args_to]
+                script.postprocess_image_after_composite(p, pp, *script_args)
+            except Exception:
+                errors.report(f"Error running postprocess_image_after_composite: {script.filename}", exc_info=True)
+
     def before_component(self, component, **kwargs):
         for callback, script in self.on_before_component_elem_id.get(kwargs.get("elem_id"), []):
             try:

modules/shared_items.py

@@ -8,6 +8,11 @@ def realesrgan_models_names():
     return [x.name for x in modules.realesrgan_model.get_realesrgan_models(None)]
 
 
+def dat_models_names():
+    import modules.dat_model
+    return [x.name for x in modules.dat_model.get_dat_models(None)]
+
+
 def postprocessing_scripts():
     import modules.scripts
 

modules/shared_options.py

@@ -97,6 +97,9 @@ options_templates.update(options_section(('upscaling', "Upscaling", "postprocess
     "ESRGAN_tile": OptionInfo(192, "Tile size for ESRGAN upscalers.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}).info("0 = no tiling"),
     "ESRGAN_tile_overlap": OptionInfo(8, "Tile overlap for ESRGAN upscalers.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}).info("Low values = visible seam"),
     "realesrgan_enabled_models": OptionInfo(["R-ESRGAN 4x+", "R-ESRGAN 4x+ Anime6B"], "Select which Real-ESRGAN models to show in the web UI.", gr.CheckboxGroup, lambda: {"choices": shared_items.realesrgan_models_names()}),
+    "dat_enabled_models": OptionInfo(["DAT x2", "DAT x3", "DAT x4"], "Select which DAT models to show in the web UI.", gr.CheckboxGroup, lambda: {"choices": shared_items.dat_models_names()}),
+    "DAT_tile": OptionInfo(192, "Tile size for DAT upscalers.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}).info("0 = no tiling"),
+    "DAT_tile_overlap": OptionInfo(8, "Tile overlap for DAT upscalers.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}).info("Low values = visible seam"),
     "upscaler_for_img2img": OptionInfo(None, "Upscaler for img2img", gr.Dropdown, lambda: {"choices": [x.name for x in shared.sd_upscalers]}),
 }))
 

modules/txt2img.py

@@ -3,7 +3,7 @@ from contextlib import closing
 
 import modules.scripts
 from modules import processing, infotext_utils
-from modules.infotext_utils import create_override_settings_dict
+from modules.infotext_utils import create_override_settings_dict, parse_generation_parameters
 from modules.shared import opts
 import modules.shared as shared
 from modules.ui import plaintext_to_html
@@ -64,19 +64,18 @@ def txt2img_upscale(id_task: str, request: gr.Request, gallery, gallery_index, g
     p.enable_hr = True
     p.batch_size = 1
     p.n_iter = 1
+    p.txt2img_upscale = True
 
     geninfo = json.loads(generation_info)
-    all_seeds = geninfo["all_seeds"]
-    all_subseeds = geninfo["all_subseeds"]
 
     image_info = gallery[gallery_index] if 0 <= gallery_index < len(gallery) else gallery[0]
     p.firstpass_image = infotext_utils.image_from_url_text(image_info)
 
-    gallery_index_from_end = len(gallery) - gallery_index
-    seed = all_seeds[-gallery_index_from_end if gallery_index_from_end < len(all_seeds) + 1 else 0]
-    subseed = all_subseeds[-gallery_index_from_end if gallery_index_from_end < len(all_seeds) + 1 else 0]
-    p.seed = seed
-    p.subseed = subseed
+    parameters = parse_generation_parameters(geninfo.get('infotexts')[gallery_index], [])
+    p.seed = parameters.get('Seed', -1)
+    p.subseed = parameters.get('Variation seed', -1)
+
+    p.override_settings['save_images_before_highres_fix'] = False
 
     with closing(p):
         processed = modules.scripts.scripts_txt2img.run(p, *p.script_args)
@@ -88,17 +87,12 @@ def txt2img_upscale(id_task: str, request: gr.Request, gallery, gallery_index, g
 
     new_gallery = []
     for i, image in enumerate(gallery):
-        fake_image = Image.new(mode="RGB", size=(1, 1))
-
         if i == gallery_index:
-            already_saved_as = getattr(processed.images[0], 'already_saved_as', None)
-            if already_saved_as is not None:
-                fake_image.already_saved_as = already_saved_as
+            geninfo["infotexts"][gallery_index: gallery_index+1] = processed.infotexts
+            new_gallery.extend(processed.images)
         else:
-                fake_image = processed.images[0]
-        else:
-            fake_image.already_saved_as = image["name"]
-
+            fake_image = Image.new(mode="RGB", size=(1, 1))
+            fake_image.already_saved_as = image["name"].rsplit('?', 1)[0]
             new_gallery.append(fake_image)
 
     geninfo["infotexts"][gallery_index] = processed.info

modules/ui.py

@@ -532,7 +532,7 @@ def create_ui():
 
                     if category == "image":
                         with gr.Tabs(elem_id="mode_img2img"):
-                            img2img_selected_tab = gr.State(0)
+                            img2img_selected_tab = gr.Number(value=0, visible=False)
 
                             with gr.TabItem('img2img', id='img2img', elem_id="img2img_img2img_tab") as tab_img2img:
                                 init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool="editor", image_mode="RGBA", height=opts.img2img_editor_height)
@@ -613,7 +613,7 @@ def create_ui():
                     elif category == "dimensions":
                         with FormRow():
                             with gr.Column(elem_id="img2img_column_size", scale=4):
-                                selected_scale_tab = gr.State(value=0)
+                                selected_scale_tab = gr.Number(value=0, visible=False)
 
                                 with gr.Tabs():
                                     with gr.Tab(label="Resize to", elem_id="img2img_tab_resize_to") as tab_scale_to:

modules/ui_common.py

@@ -63,8 +63,9 @@ def save_files(js_data, images, do_make_zip, index):
     import csv
     filenames = []
     fullfns = []
+    parsed_infotexts = []
 
-    #quick dictionary to class object conversion. Its necessary due apply_filename_pattern requiring it
+    # quick dictionary to class object conversion. Its necessary due apply_filename_pattern requiring it
     class MyObject:
         def __init__(self, d=None):
             if d is not None:
@@ -72,16 +73,14 @@ def save_files(js_data, images, do_make_zip, index):
                     setattr(self, key, value)
 
     data = json.loads(js_data)
-
     p = MyObject(data)
+
     path = shared.opts.outdir_save
     save_to_dirs = shared.opts.use_save_to_dirs_for_ui
     extension: str = shared.opts.samples_format
     start_index = 0
-    only_one = False
 
     if index > -1 and shared.opts.save_selected_only and (index >= data["index_of_first_image"]):  # ensures we are looking at a specific non-grid picture, and we have save_selected_only
-        only_one = True
         images = [images[index]]
         start_index = index
 
@@ -117,10 +116,12 @@ def save_files(js_data, images, do_make_zip, index):
             image = image_from_url_text(filedata)
 
             is_grid = image_index < p.index_of_first_image
-            i = 0 if is_grid else (image_index - p.index_of_first_image)
 
             p.batch_index = image_index-1
-            fullfn, txt_fullfn = modules.images.save_image(image, path, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs)
+
+            parameters = parameters_copypaste.parse_generation_parameters(data["infotexts"][image_index], [])
+            parsed_infotexts.append(parameters)
+            fullfn, txt_fullfn = modules.images.save_image(image, path, "", seed=parameters['Seed'], prompt=parameters['Prompt'], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs)
 
             filename = os.path.relpath(fullfn, path)
             filenames.append(filename)
@@ -129,12 +130,12 @@ def save_files(js_data, images, do_make_zip, index):
                 filenames.append(os.path.basename(txt_fullfn))
                 fullfns.append(txt_fullfn)
 
-        writer.writerow([data["prompt"], data["seed"], data["width"], data["height"], data["sampler_name"], data["cfg_scale"], data["steps"], filenames[0], data["negative_prompt"], data["sd_model_name"], data["sd_model_hash"]])
+        writer.writerow([parsed_infotexts[0]['Prompt'], parsed_infotexts[0]['Seed'], data["width"], data["height"], data["sampler_name"], data["cfg_scale"], data["steps"], filenames[0], parsed_infotexts[0]['Negative prompt']])
 
     # Make Zip
     if do_make_zip:
-        zip_fileseed = p.all_seeds[index-1] if only_one else p.all_seeds[0]
-        namegen = modules.images.FilenameGenerator(p, zip_fileseed, p.all_prompts[0], image, True)
+        p.all_seeds = [parameters['Seed'] for parameters in parsed_infotexts]
+        namegen = modules.images.FilenameGenerator(p, parsed_infotexts[0]['Seed'], parsed_infotexts[0]['Prompt'], image, True)
         zip_filename = namegen.apply(shared.opts.grid_zip_filename_pattern or "[datetime]_[[model_name]]_[seed]-[seed_last]")
         zip_filepath = os.path.join(path, f"{zip_filename}.zip")
 

modules/ui_postprocessing.py

@@ -5,7 +5,7 @@ import modules.infotext_utils as parameters_copypaste
 
 def create_ui():
     dummy_component = gr.Label(visible=False)
-    tab_index = gr.State(value=0)
+    tab_index = gr.Number(value=0, visible=False)
 
     with gr.Row(equal_height=False, variant='compact'):
         with gr.Column(variant='compact'):

modules/ui_toprow.py

@@ -107,8 +107,9 @@ class Toprow:
             )
 
             def interrupt_function():
-                if shared.state.job_count > 1 and shared.opts.interrupt_after_current:
+                if not shared.state.stopping_generation and shared.state.job_count > 1 and shared.opts.interrupt_after_current:
                     shared.state.stop_generating()
+                    gr.Info("Generation will stop after finishing this image, click again to stop immediately.")
                 else:
                     shared.state.interrupt()
 

scripts/postprocessing_upscale.py

@@ -15,7 +15,7 @@ class ScriptPostprocessingUpscale(scripts_postprocessing.ScriptPostprocessing):
     order = 1000
 
     def ui(self):
-        selected_tab = gr.State(value=0)
+        selected_tab = gr.Number(value=0, visible=False)
 
         with gr.Column():
             with FormRow():