Merge branch 'main' into refactor/nodes-on-generator

invokeai/app/cli_app.py

@@ -102,6 +102,29 @@ def generate_matching_edges(
     return edges
 
 
+class SessionError(Exception):
+    """Raised when a session error has occurred"""
+    pass
+
+
+def invoke_all(context: CliContext):
+    """Runs all invocations in the specified session"""
+    context.invoker.invoke(context.session, invoke_all=True)
+    while not context.session.is_complete():
+        # Wait some time
+        session = context.get_session()
+        time.sleep(0.1)
+
+    # Print any errors
+    if context.session.has_error():
+        for n in context.session.errors:
+            print(
+                f"Error in node {n} (source node {context.session.prepared_source_mapping[n]}): {session.errors[n]}"
+            )
+        
+        raise SessionError()
+
+
 def invoke_cli():
     args = Args()
     config = args.parse_args()
@@ -130,7 +153,6 @@ def invoke_cli():
 
     invoker = Invoker(services)
     session: GraphExecutionState = invoker.create_execution_state()
-
     parser = get_command_parser()
 
     # Uncomment to print out previous sessions at startup
@@ -147,8 +169,7 @@ def invoke_cli():
 
         try:
             # Refresh the state of the session
-            session = invoker.services.graph_execution_manager.get(session.id)
+            history = list(get_graph_execution_history(context.session))
-            history = list(get_graph_execution_history(session))
 
             # Split the command for piping
             cmds = cmd_input.split("|")
@@ -160,7 +181,7 @@ def invoke_cli():
                     raise InvalidArgs("Empty command")
 
                 # Parse args to create invocation
-                args = vars(parser.parse_args(shlex.split(cmd.strip())))
+                args = vars(context.parser.parse_args(shlex.split(cmd.strip())))
 
                 # Override defaults
                 for field_name, field_default in context.defaults.items():
@@ -172,11 +193,11 @@ def invoke_cli():
                 command = CliCommand(command=args)
 
                 # Run any CLI commands immediately
-                # TODO: this won't behave as expected if piping and using e.g. history,
-                # since invocations are gathered and then run together at the end.
-                # This is more efficient if the CLI is running against a distributed
-                # backend, so it's preferable not to change that behavior.
                 if isinstance(command.command, BaseCommand):
+                    # Invoke all current nodes to preserve operation order
+                    invoke_all(context)
+
+                    # Run the command
                     command.command.run(context)
                     continue
 
@@ -189,7 +210,7 @@ def invoke_cli():
                     from_node = (
                         next(filter(lambda n: n[0].id == from_id, new_invocations))[0]
                         if current_id != start_id
-                        else session.graph.get_node(from_id)
+                        else context.session.graph.get_node(from_id)
                     )
                     matching_edges = generate_matching_edges(
                         from_node, command.command
@@ -199,7 +220,7 @@ def invoke_cli():
                 # Parse provided links
                 if "link_node" in args and args["link_node"]:
                     for link in args["link_node"]:
-                        link_node = session.graph.get_node(link)
+                        link_node = context.session.graph.get_node(link)
                         matching_edges = generate_matching_edges(
                             link_node, command.command
                         )
@@ -223,37 +244,24 @@ def invoke_cli():
 
                 current_id = current_id + 1
 
-            # Command line was parsed successfully
+                # Add the node to the session
-            # Add the invocations to the session
+                context.session.add_node(command.command)
-            for invocation in new_invocations:
+                for edge in edges:
-                session.add_node(invocation[0])
-                for edge in invocation[1]:
                     print(edge)
-                    session.add_edge(edge)
+                    context.session.add_edge(edge)
 
-            # Execute all available invocations
+            # Execute all remaining nodes
-            invoker.invoke(session, invoke_all=True)
+            invoke_all(context)
-            while not session.is_complete():
-                # Wait some time
-                session = context.get_session()
-                time.sleep(0.1)
-
-            # Print any errors
-            if session.has_error():
-                for n in session.errors:
-                    print(
-                        f"Error in node {n} (source node {session.prepared_source_mapping[n]}): {session.errors[n]}"
-                    )
-
-                # Start a new session
-                print("Creating a new session")
-                session = invoker.create_execution_state()
-                context.session = session
 
         except InvalidArgs:
             print('Invalid command, use "help" to list commands')
             continue
 
+        except SessionError:
+            # Start a new session
+            print("Session error: creating a new session")
+            context.session = context.invoker.create_execution_state()
+
         except ExitCli:
             break
 

invokeai/backend/generator/base.py

@@ -347,6 +347,7 @@ class Generator:
             h_symmetry_time_pct=h_symmetry_time_pct,
             v_symmetry_time_pct=v_symmetry_time_pct,
             attention_maps_callback=attention_maps_callback,
+            seed=seed,
             **kwargs,
         )
         results = []
@@ -537,9 +538,7 @@ class Generator:
             if self.variation_amount > 0:
                 random.seed()  # reset RNG to an actually random state, so we can get a random seed for variations
                 seed = random.randrange(0, np.iinfo(np.uint32).max)
-            return (seed, initial_noise)
+        return (seed, initial_noise)
-        else:
-            return (seed, None)
 
     def get_perlin_noise(self, width, height):
         fixdevice = "cpu" if (self.model.device.type == "mps") else self.model.device

invokeai/backend/generator/img2img.py

@@ -1,8 +1,10 @@
 """
 invokeai.backend.generator.img2img descends from .generator
 """
+from typing import Optional
 
 import torch
+from accelerate.utils import set_seed
 from diffusers import logging
 
 from ..stable_diffusion import (
@@ -35,6 +37,7 @@ class Img2Img(Generator):
         h_symmetry_time_pct=None,
         v_symmetry_time_pct=None,
         attention_maps_callback=None,
+        seed=None,
         **kwargs,
     ):
         """
@@ -65,6 +68,7 @@ class Img2Img(Generator):
             # FIXME: use x_T for initial seeded noise
             # We're not at the moment because the pipeline automatically resizes init_image if
             # necessary, which the x_T input might not match.
+            # In the meantime, reset the seed prior to generating pipeline output so we at least get the same result.
             logging.set_verbosity_error()  # quench safety check warnings
             pipeline_output = pipeline.img2img_from_embeddings(
                 init_image,
@@ -73,6 +77,7 @@ class Img2Img(Generator):
                 conditioning_data,
                 noise_func=self.get_noise_like,
                 callback=step_callback,
+                seed=seed
             )
             if (
                 pipeline_output.attention_map_saver is not None
@@ -83,7 +88,9 @@ class Img2Img(Generator):
 
         return make_image
 
-    def get_noise_like(self, like: torch.Tensor):
+    def get_noise_like(self, like: torch.Tensor, seed: Optional[int]):
+        if seed is not None:
+            set_seed(seed)
         device = like.device
         if device.type == "mps":
             x = torch.randn_like(like, device="cpu").to(device)

invokeai/backend/generator/inpaint.py

@@ -223,6 +223,7 @@ class Inpaint(Img2Img):
         inpaint_height=None,
         inpaint_fill: tuple(int) = (0x7F, 0x7F, 0x7F, 0xFF),
         attention_maps_callback=None,
+        seed=None,
         **kwargs,
     ):
         """
@@ -319,6 +320,7 @@ class Inpaint(Img2Img):
                 conditioning_data=conditioning_data,
                 noise_func=self.get_noise_like,
                 callback=step_callback,
+                seed=seed
             )
 
             if (

invokeai/backend/stable_diffusion/diffusers_pipeline.py

@@ -690,6 +690,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
         callback: Callable[[PipelineIntermediateState], None] = None,
         run_id=None,
         noise_func=None,
+        seed=None,
     ) -> InvokeAIStableDiffusionPipelineOutput:
         if isinstance(init_image, PIL.Image.Image):
             init_image = image_resized_to_grid_as_tensor(init_image.convert("RGB"))
@@ -703,7 +704,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
             device=self._model_group.device_for(self.unet),
             dtype=self.unet.dtype,
         )
-        noise = noise_func(initial_latents)
+        noise = noise_func(initial_latents, seed)
 
         return self.img2img_from_latents_and_embeddings(
             initial_latents,
@@ -731,9 +732,11 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
             device=self._model_group.device_for(self.unet),
         )
         result_latents, result_attention_maps = self.latents_from_embeddings(
-            initial_latents,
+            latents=initial_latents if strength < 1.0 else torch.zeros_like(
-            num_inference_steps,
+                initial_latents, device=initial_latents.device, dtype=initial_latents.dtype
-            conditioning_data,
+            ),
+            num_inference_steps=num_inference_steps,
+            conditioning_data=conditioning_data,
             timesteps=timesteps,
             noise=noise,
             run_id=run_id,
@@ -779,6 +782,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
         callback: Callable[[PipelineIntermediateState], None] = None,
         run_id=None,
         noise_func=None,
+        seed=None,
     ) -> InvokeAIStableDiffusionPipelineOutput:
         device = self._model_group.device_for(self.unet)
         latents_dtype = self.unet.dtype
@@ -802,7 +806,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
         init_image_latents = self.non_noised_latents_from_image(
             init_image, device=device, dtype=latents_dtype
         )
-        noise = noise_func(init_image_latents)
+        noise = noise_func(init_image_latents, seed)
 
         if mask.dim() == 3:
             mask = mask.unsqueeze(0)
@@ -831,9 +835,11 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
 
         try:
             result_latents, result_attention_maps = self.latents_from_embeddings(
-                init_image_latents,
+                latents=init_image_latents if strength < 1.0 else torch.zeros_like(
-                num_inference_steps,
+                    init_image_latents, device=init_image_latents.device, dtype=init_image_latents.dtype
-                conditioning_data,
+                ),
+                num_inference_steps=num_inference_steps,
+                conditioning_data=conditioning_data,
                 noise=noise,
                 timesteps=timesteps,
                 additional_guidance=guidance,

invokeai/frontend/web/dist/assets/ThemeLocaleProvider-20e303dd.js

@@ -1,4 +1,4 @@
-import{j as y,cM as Ie,r as _,cN as bt,q as Vr,cO as o,cP as b,cQ as v,cR as S,cS as Lr,cT as ut,cU as vt,cV as ft,cW as mt,n as ht,cX as gt,E as pt}from"./index-b928084d.js";import{d as yt,i as St,T as xt,j as $t,s as kt,g as _t}from"./scrollbar-f59ed469.js";var Or=`
+import{j as y,cM as Ie,r as _,cN as bt,q as Vr,cO as o,cP as b,cQ as v,cR as S,cS as Lr,cT as ut,cU as vt,cV as ft,cW as mt,n as ht,cX as gt,E as pt}from"./index-61f10aa8.js";import{d as yt,i as St,T as xt,j as $t,s as kt,g as _t}from"./scrollbar-7e342734.js";var Or=`
   :root {
     --chakra-vh: 100vh;
   }

invokeai/frontend/web/dist/index.html

@@ -12,7 +12,7 @@
         margin: 0;
       }
     </style>
-    <script type="module" crossorigin src="./assets/index-b928084d.js"></script>
+    <script type="module" crossorigin src="./assets/index-61f10aa8.js"></script>
     <link rel="stylesheet" href="./assets/index-5483945c.css">
   </head>
 

invokeai/frontend/web/dist/locales/en.json

@@ -1,4 +1,8 @@
 {
+    "accessibility": {
+        "modelSelect": "Model Select",
+        "invokeProgressBar": "Invoke progress bar"
+    },
     "common": {
         "hotkeysLabel": "Hotkeys",
         "themeLabel": "Theme",

invokeai/frontend/web/dist/locales/es.json

@@ -363,7 +363,6 @@
         "convertToDiffusersHelpText6": "¿Desea transformar este modelo?",
         "convertToDiffusersSaveLocation": "Guardar ubicación",
         "v1": "v1",
-        "v2": "v2",
         "statusConverting": "Adaptar",
         "modelConverted": "Modelo adaptado",
         "sameFolder": "La misma carpeta",

invokeai/frontend/web/dist/locales/fr.json

@@ -45,7 +45,9 @@
         "statusUpscaling": "Mise à échelle",
         "statusUpscalingESRGAN": "Mise à échelle (ESRGAN)",
         "statusLoadingModel": "Chargement du modèle",
-        "statusModelChanged": "Modèle changé"
+        "statusModelChanged": "Modèle changé",
+        "discordLabel": "Discord",
+        "githubLabel": "Github"
     },
     "gallery": {
         "generations": "Générations",

invokeai/frontend/web/dist/locales/he.json

@@ -92,7 +92,6 @@
         "modelThree": "מודל 3",
         "mergedModelName": "שם מודל ממוזג",
         "v1": "v1",
-        "v2": "v2",
         "invokeRoot": "תיקיית InvokeAI",
         "customConfig": "תצורה מותאמת אישית",
         "pathToCustomConfig": "נתיב לתצורה מותאמת אישית",

invokeai/frontend/web/dist/locales/it.json

@@ -361,7 +361,6 @@
         "convertToDiffusersHelpText5": "Assicurati di avere spazio su disco sufficiente. I modelli generalmente variano tra 4 GB e 7 GB di dimensioni.",
         "convertToDiffusersHelpText6": "Vuoi convertire questo modello?",
         "convertToDiffusersSaveLocation": "Ubicazione salvataggio",
-        "v2": "v2",
         "inpainting": "v1 Inpainting",
         "customConfig": "Configurazione personalizzata",
         "statusConverting": "Conversione in corso",

invokeai/frontend/web/dist/locales/nl.json

@@ -302,7 +302,7 @@
         "name": "Naam",
         "nameValidationMsg": "Geef een naam voor je model",
         "description": "Beschrijving",
-        "descriptionValidationMsg": "Voeg een beschrijving toe voor je model",
+        "descriptionValidationMsg": "Voeg een beschrijving toe voor je model.",
         "config": "Configuratie",
         "configValidationMsg": "Pad naar het configuratiebestand van je model.",
         "modelLocation": "Locatie model",
@@ -364,7 +364,6 @@
         "convertToDiffusersHelpText5": "Zorg ervoor dat je genoeg schijfruimte hebt. Modellen nemen gewoonlijk ongeveer 4 - 7 GB ruimte in beslag.",
         "convertToDiffusersSaveLocation": "Bewaarlocatie",
         "v1": "v1",
-        "v2": "v2",
         "inpainting": "v1-inpainting",
         "customConfig": "Eigen configuratie",
         "pathToCustomConfig": "Pad naar eigen configuratie",

invokeai/frontend/web/dist/locales/pt_BR.json

@@ -358,7 +358,6 @@
         "convertToDiffusersHelpText6": "Você deseja converter este modelo?",
         "convertToDiffusersSaveLocation": "Local para Salvar",
         "v1": "v1",
-        "v2": "v2",
         "inpainting": "v1 Inpainting",
         "customConfig": "Configuração personalizada",
         "pathToCustomConfig": "Caminho para configuração personalizada",
@@ -381,7 +380,19 @@
         "allModels": "Todos os Modelos",
         "repoIDValidationMsg": "Repositório Online do seu Modelo",
         "convert": "Converter",
-        "convertToDiffusersHelpText2": "Este processo irá substituir sua entrada de Gerenciador de Modelos por uma versão Diffusers do mesmo modelo."
+        "convertToDiffusersHelpText2": "Este processo irá substituir sua entrada de Gerenciador de Modelos por uma versão Diffusers do mesmo modelo.",
+        "mergedModelCustomSaveLocation": "Caminho Personalizado",
+        "mergedModelSaveLocation": "Local de Salvamento",
+        "interpolationType": "Tipo de Interpolação",
+        "ignoreMismatch": "Ignorar Divergências entre Modelos Selecionados",
+        "invokeAIFolder": "Pasta Invoke AI",
+        "weightedSum": "Soma Ponderada",
+        "sigmoid": "Sigmóide",
+        "inverseSigmoid": "Sigmóide Inversa",
+        "modelMergeHeaderHelp1": "Você pode mesclar até três modelos diferentes para criar uma mistura que atenda às suas necessidades.",
+        "modelMergeInterpAddDifferenceHelp": "Neste modo, o Modelo 3 é primeiro subtraído do Modelo 2. A versão resultante é mesclada com o Modelo 1 com a taxa alpha definida acima.",
+        "modelMergeAlphaHelp": "Alpha controla a força da mistura dos modelos. Valores de alpha mais baixos resultam em uma influência menor do segundo modelo.",
+        "modelMergeHeaderHelp2": "Apenas Diffusers estão disponíveis para mesclagem. Se você deseja mesclar um modelo de checkpoint, por favor, converta-o para Diffusers primeiro."
     },
     "parameters": {
         "images": "Imagems",
@@ -441,7 +452,22 @@
         "info": "Informações",
         "deleteImage": "Apagar Imagem",
         "initialImage": "Imagem inicial",
-        "showOptionsPanel": "Mostrar Painel de Opções"
+        "showOptionsPanel": "Mostrar Painel de Opções",
+        "vSymmetryStep": "V Passo de Simetria",
+        "hSymmetryStep": "H Passo de Simetria",
+        "symmetry": "Simetria",
+        "copyImage": "Copiar imagem",
+        "negativePrompts": "Indicações negativas",
+        "hiresStrength": "Força da Alta Resolução",
+        "denoisingStrength": "A força de remoção de ruído",
+        "imageToImage": "Imagem para Imagem",
+        "cancel": {
+            "setType": "Definir tipo de cancelamento",
+            "isScheduled": "Cancelando",
+            "schedule": "Cancelar após a iteração atual",
+            "immediate": "Cancelar imediatamente"
+        },
+        "general": "Geral"
     },
     "settings": {
         "models": "Modelos",
@@ -454,7 +480,8 @@
         "resetWebUI": "Reiniciar Interface",
         "resetWebUIDesc1": "Reiniciar a interface apenas reinicia o cache local do broswer para imagens e configurações lembradas. Não apaga nenhuma imagem do disco.",
         "resetWebUIDesc2": "Se as imagens não estão aparecendo na galeria ou algo mais não está funcionando, favor tentar reiniciar antes de postar um problema no GitHub.",
-        "resetComplete": "A interface foi reiniciada. Atualize a página para carregar."
+        "resetComplete": "A interface foi reiniciada. Atualize a página para carregar.",
+        "useSlidersForAll": "Usar deslizadores para todas as opções"
     },
     "toast": {
         "tempFoldersEmptied": "Pasta de Arquivos Temporários Esvaziada",
@@ -546,5 +573,20 @@
         "betaDarkenOutside": "Escurecer Externamente",
         "betaLimitToBox": "Limitar Para a Caixa",
         "betaPreserveMasked": "Preservar Máscarado"
+    },
+    "tooltip": {
+        "feature": {
+            "seed": "O valor da semente afeta o ruído inicial a partir do qual a imagem é formada. Você pode usar as sementes já existentes de imagens anteriores. 'Limiar de ruído' é usado para mitigar artefatos em valores CFG altos (experimente a faixa de 0-10), e o Perlin para adicionar ruído Perlin durante a geração: ambos servem para adicionar variação às suas saídas.",
+            "gallery": "A galeria exibe as gerações da pasta de saída conforme elas são criadas. As configurações são armazenadas em arquivos e acessadas pelo menu de contexto.",
+            "other": "Essas opções ativam modos alternativos de processamento para o Invoke. 'Seamless tiling' criará padrões repetidos na saída. 'High resolution' é uma geração em duas etapas com img2img: use essa configuração quando desejar uma imagem maior e mais coerente sem artefatos. Levará mais tempo do que o txt2img usual.",
+            "boundingBox": "A caixa delimitadora é a mesma que as configurações de largura e altura para Texto para Imagem ou Imagem para Imagem. Apenas a área na caixa será processada.",
+            "upscale": "Use o ESRGAN para ampliar a imagem imediatamente após a geração.",
+            "seamCorrection": "Controla o tratamento das emendas visíveis que ocorrem entre as imagens geradas no canvas.",
+            "faceCorrection": "Correção de rosto com GFPGAN ou Codeformer: o algoritmo detecta rostos na imagem e corrige quaisquer defeitos. Um valor alto mudará mais a imagem, resultando em rostos mais atraentes. Codeformer com uma fidelidade maior preserva a imagem original às custas de uma correção de rosto mais forte.",
+            "prompt": "Este é o campo de prompt. O prompt inclui objetos de geração e termos estilísticos. Você também pode adicionar peso (importância do token) no prompt, mas comandos e parâmetros de CLI não funcionarão.",
+            "infillAndScaling": "Gerencie os métodos de preenchimento (usados em áreas mascaradas ou apagadas do canvas) e a escala (útil para tamanhos de caixa delimitadora pequenos).",
+            "imageToImage": "Image to Image carrega qualquer imagem como inicial, que é então usada para gerar uma nova junto com o prompt. Quanto maior o valor, mais a imagem resultante mudará. Valores de 0.0 a 1.0 são possíveis, a faixa recomendada é de 0.25 a 0.75",
+            "variations": "Experimente uma variação com um valor entre 0,1 e 1,0 para mudar o resultado para uma determinada semente. Variações interessantes da semente estão entre 0,1 e 0,3."
+        }
     }
 }

invokeai/frontend/web/dist/locales/zh_Hant.json

@@ -1 +1,24 @@
-{}
+{
+    "common": {
+        "nodes": "節點",
+        "img2img": "圖片轉圖片",
+        "langSimplifiedChinese": "簡體中文",
+        "statusError": "錯誤",
+        "statusDisconnected": "已中斷連線",
+        "statusConnected": "已連線",
+        "back": "返回",
+        "load": "載入",
+        "close": "關閉",
+        "langEnglish": "英語",
+        "settingsLabel": "設定",
+        "upload": "上傳",
+        "langArabic": "阿拉伯語",
+        "greenTheme": "綠色",
+        "lightTheme": "淺色",
+        "darkTheme": "深色",
+        "discordLabel": "Discord",
+        "nodesDesc": "使用Node生成圖像的系統正在開發中。敬請期待有關於這項功能的更新。",
+        "reportBugLabel": "回報錯誤",
+        "githubLabel": "GitHub"
+    }
+}

invokeai/frontend/web/public/locales/en.json

@@ -1,4 +1,8 @@
 {
+    "accessibility": {
+        "modelSelect": "Model Select",
+        "invokeProgressBar": "Invoke progress bar"
+    },
     "common": {
         "hotkeysLabel": "Hotkeys",
         "themeLabel": "Theme",

invokeai/frontend/web/src/common/components/IAISimpleMenu.tsx

@@ -68,6 +68,7 @@ export default function IAISimpleMenu(props: IAIMenuProps) {
           <MenuButton
             as={menuType === 'icon' ? IconButton : Button}
             tooltip={iconTooltip}
+            aria-label={iconTooltip}
             icon={isOpen ? <MdArrowDropUp /> : <MdArrowDropDown />}
             paddingX={0}
             paddingY={menuType === 'regular' ? 2 : 0}

invokeai/frontend/web/src/component.tsx

@@ -0,0 +1,38 @@
+import React, { lazy } from 'react';
+import { Provider } from 'react-redux';
+import { PersistGate } from 'redux-persist/integration/react';
+import { store } from './app/store';
+import { persistor } from './persistor';
+import '@fontsource/inter/100.css';
+import '@fontsource/inter/200.css';
+import '@fontsource/inter/300.css';
+import '@fontsource/inter/400.css';
+import '@fontsource/inter/500.css';
+import '@fontsource/inter/600.css';
+import '@fontsource/inter/700.css';
+import '@fontsource/inter/800.css';
+import '@fontsource/inter/900.css';
+
+import Loading from './Loading';
+
+// Localization
+import './i18n';
+
+const App = lazy(() => import('./app/App'));
+const ThemeLocaleProvider = lazy(() => import('./app/ThemeLocaleProvider'));
+
+export default function Component() {
+  return (
+    <React.StrictMode>
+      <Provider store={store}>
+        <PersistGate loading={<Loading />} persistor={persistor}>
+          <React.Suspense fallback={<Loading showText />}>
+            <ThemeLocaleProvider>
+              <App />
+            </ThemeLocaleProvider>
+          </React.Suspense>
+        </PersistGate>
+      </Provider>
+    </React.StrictMode>
+  );
+}

invokeai/frontend/web/src/features/system/components/ModelSelect.tsx

@@ -6,6 +6,7 @@ import IAISelect from 'common/components/IAISelect';
 import { isEqual, map } from 'lodash';
 
 import { ChangeEvent } from 'react';
+import { useTranslation } from 'react-i18next';
 import { activeModelSelector, systemSelector } from '../store/systemSelectors';
 
 const selector = createSelector(
@@ -24,6 +25,7 @@ const selector = createSelector(
 
 const ModelSelect = () => {
   const dispatch = useAppDispatch();
+  const { t } = useTranslation();
   const { models, isProcessing } = useAppSelector(selector);
   const activeModel = useAppSelector(activeModelSelector);
   const handleChangeModel = (e: ChangeEvent<HTMLSelectElement>) => {
@@ -38,6 +40,7 @@ const ModelSelect = () => {
     >
       <IAISelect
         style={{ fontSize: 'sm' }}
+        aria-label={t('accessibility.modelSelect')}
         tooltip={activeModel.description}
         isDisabled={isProcessing}
         value={activeModel.name}

invokeai/frontend/web/src/features/system/components/ProgressBar.tsx

@@ -3,6 +3,7 @@ import { createSelector } from '@reduxjs/toolkit';
 import { useAppSelector } from 'app/storeHooks';
 import { SystemState } from 'features/system/store/systemSlice';
 import { isEqual } from 'lodash';
+import { useTranslation } from 'react-i18next';
 import { PROGRESS_BAR_THICKNESS } from 'theme/util/constants';
 import { systemSelector } from '../store/systemSelectors';
 
@@ -22,6 +23,7 @@ const progressBarSelector = createSelector(
 );
 
 const ProgressBar = () => {
+  const { t } = useTranslation();
   const { isProcessing, currentStep, totalSteps, currentStatusHasSteps } =
     useAppSelector(progressBarSelector);
 
@@ -30,6 +32,7 @@ const ProgressBar = () => {
   return (
     <Progress
       value={value}
+      aria-label={t('accessibility.invokeProgressBar')}
       isIndeterminate={isProcessing && !currentStatusHasSteps}
       height={PROGRESS_BAR_THICKNESS}
       zIndex={99}

invokeai/frontend/web/src/features/ui/components/InvokeTabs.tsx

@@ -6,6 +6,7 @@ import {
   TabPanels,
   Tabs,
   Tooltip,
+  VisuallyHidden,
 } from '@chakra-ui/react';
 import { RootState } from 'app/store';
 import { useAppDispatch, useAppSelector } from 'app/storeHooks';
@@ -164,7 +165,12 @@ export default function InvokeTabs() {
           label={tabDict[key as keyof typeof tabDict].tooltip}
           placement="end"
         >
-          <Tab>{tabDict[key as keyof typeof tabDict].title}</Tab>
+          <Tab>
+            <VisuallyHidden>
+              {tabDict[key as keyof typeof tabDict].tooltip}
+            </VisuallyHidden>
+            {tabDict[key as keyof typeof tabDict].title}
+          </Tab>
         </Tooltip>
       );
     });

invokeai/frontend/web/src/features/ui/components/UnifiedCanvas/UnifiedCanvasBeta/UnifiedCanvasToolbar/UnifiedCanvasLayerSelect.tsx

@@ -61,6 +61,7 @@ export default function UnifiedCanvasLayerSelect() {
   return (
     <IAISelect
       tooltip={`${t('unifiedCanvas.layer')} (Q)`}
+      aria-label={`${t('unifiedCanvas.layer')} (Q)`}
       tooltipProps={{ hasArrow: true, placement: 'top' }}
       value={layer}
       validValues={LAYER_NAMES_DICT}

invokeai/frontend/web/src/main.tsx

@@ -1,37 +1,7 @@
-import React, { lazy } from 'react';
 import ReactDOM from 'react-dom/client';
-import { Provider } from 'react-redux';
-import { PersistGate } from 'redux-persist/integration/react';
-import { store } from './app/store';
-import { persistor } from './persistor';
-import '@fontsource/inter/100.css';
-import '@fontsource/inter/200.css';
-import '@fontsource/inter/300.css';
-import '@fontsource/inter/400.css';
-import '@fontsource/inter/500.css';
-import '@fontsource/inter/600.css';
-import '@fontsource/inter/700.css';
-import '@fontsource/inter/800.css';
-import '@fontsource/inter/900.css';
 
-import Loading from './Loading';
+import Component from './component';
-
-// Localization
-import './i18n';
-
-const App = lazy(() => import('./app/App'));
-const ThemeLocaleProvider = lazy(() => import('./app/ThemeLocaleProvider'));
 
 ReactDOM.createRoot(document.getElementById('root') as HTMLElement).render(
-  <React.StrictMode>
+  <Component />
-    <Provider store={store}>
-      <PersistGate loading={<Loading />} persistor={persistor}>
-        <React.Suspense fallback={<Loading showText />}>
-          <ThemeLocaleProvider>
-            <App />
-          </ThemeLocaleProvider>
-        </React.Suspense>
-      </PersistGate>
-    </Provider>
-  </React.StrictMode>
 );

pyproject.toml

@@ -63,6 +63,7 @@ dependencies = [
   "prompt-toolkit",
   "pypatchmatch",
   "pyreadline3",
+  "pytorch-lightning==1.7.7",
   "realesrgan",
   "requests==2.28.2",
   "rich~=13.3",