Release/3.1.0 (#4397)

## What type of PR is this? (check all applicable)

This is the 3.1.0 release candidate. Minor bugfixes will be applied here
during testing and then merged into main upon release.

installer/create_installer.sh

@@ -46,6 +46,7 @@ if [[ $(python -c 'from importlib.util import find_spec; print(find_spec("build"
     pip install --user build
 fi
 
+rm -r ../build
 python -m build --wheel --outdir dist/ ../.
 
 # ----------------------

invokeai/app/invocations/compel.py

@@ -302,6 +302,29 @@ class SDXLCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase):
 
         add_time_ids = torch.tensor([original_size + crop_coords + target_size])
 
+        # [1, 77, 768], [1, 154, 1280]
+        if c1.shape[1] < c2.shape[1]:
+            c1 = torch.cat(
+                [
+                    c1,
+                    torch.zeros(
+                        (c1.shape[0], c2.shape[1] - c1.shape[1], c1.shape[2]), device=c1.device, dtype=c1.dtype
+                    ),
+                ],
+                dim=1,
+            )
+
+        elif c1.shape[1] > c2.shape[1]:
+            c2 = torch.cat(
+                [
+                    c2,
+                    torch.zeros(
+                        (c2.shape[0], c1.shape[1] - c2.shape[1], c2.shape[2]), device=c2.device, dtype=c2.dtype
+                    ),
+                ],
+                dim=1,
+            )
+
         conditioning_data = ConditioningFieldData(
             conditionings=[
                 SDXLConditioningInfo(

invokeai/app/invocations/latent.py

@@ -445,8 +445,14 @@ class DenoiseLatentsInvocation(BaseInvocation):
                 latents = context.services.latents.get(self.latents.latents_name)
                 if seed is None:
                     seed = self.latents.seed
-            else:
+
+                if noise is not None and noise.shape[1:] != latents.shape[1:]:
+                    raise Exception(f"Incompatable 'noise' and 'latents' shapes: {latents.shape=} {noise.shape=}")
+
+            elif noise is not None:
                 latents = torch.zeros_like(noise)
+            else:
+                raise Exception("'latents' or 'noise' must be provided!")
 
             if seed is None:
                 seed = 0

invokeai/app/invocations/primitives.py

@@ -109,7 +109,7 @@ class IntegerCollectionInvocation(BaseInvocation):
     """A collection of integer primitive values"""
 
     collection: list[int] = InputField(
-        default=0, description="The collection of integer values", ui_type=UIType.IntegerCollection
+        default_factory=list, description="The collection of integer values", ui_type=UIType.IntegerCollection
     )
 
     def invoke(self, context: InvocationContext) -> IntegerCollectionOutput:
@@ -261,7 +261,7 @@ class ImageCollectionInvocation(BaseInvocation):
     """A collection of image primitive values"""
 
     collection: list[ImageField] = InputField(
-        default=0, description="The collection of image values", ui_type=UIType.ImageCollection
+        default_factory=list, description="The collection of image values", ui_type=UIType.ImageCollection
     )
 
     def invoke(self, context: InvocationContext) -> ImageCollectionOutput:
@@ -451,7 +451,9 @@ class ConditioningCollectionInvocation(BaseInvocation):
     """A collection of conditioning tensor primitive values"""
 
     collection: list[ConditioningField] = InputField(
-        default=0, description="The collection of conditioning tensors", ui_type=UIType.ConditioningCollection
+        default_factory=list,
+        description="The collection of conditioning tensors",
+        ui_type=UIType.ConditioningCollection,
     )
 
     def invoke(self, context: InvocationContext) -> ConditioningCollectionOutput:

invokeai/app/services/config/__init__.py

@@ -6,3 +6,4 @@ from .invokeai_config import (  # noqa F401
     InvokeAIAppConfig,
     get_invokeai_config,
 )
+from .base import PagingArgumentParser  # noqa F401

invokeai/backend/install/migrate_to_3.py

@@ -492,10 +492,10 @@ def _parse_legacy_yamlfile(root: Path, initfile: Path) -> ModelPaths:
     loras = paths.get("lora_dir", "loras")
     controlnets = paths.get("controlnet_dir", "controlnets")
     return ModelPaths(
-        models=root / models,
-        embeddings=root / embeddings,
-        loras=root / loras,
-        controlnets=root / controlnets,
+        models=root / models if models else None,
+        embeddings=root / embeddings if embeddings else None,
+        loras=root / loras if loras else None,
+        controlnets=root / controlnets if controlnets else None,
     )
 
 

invokeai/backend/stable_diffusion/diffusion/cross_attention_control.py

@@ -265,7 +265,7 @@ class InvokeAICrossAttentionMixin:
         if q.shape[1] <= 4096:  # (512x512) max q.shape[1]: 4096
             return self.einsum_lowest_level(q, k, v, None, None, None)
         else:
-            slice_size = math.floor(2**30 / (q.shape[0] * q.shape[1]))
+            slice_size = math.floor(2 ** 30 / (q.shape[0] * q.shape[1]))
             return self.einsum_op_slice_dim1(q, k, v, slice_size)
 
     def einsum_op_mps_v2(self, q, k, v):

invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py

@@ -215,10 +215,7 @@ class InvokeAIDiffuserComponent:
                                 dim=0,
                             ),
                         }
-                    (
-                        encoder_hidden_states,
-                        encoder_attention_mask,
-                    ) = self._concat_conditionings_for_batch(
+                    (encoder_hidden_states, encoder_attention_mask,) = self._concat_conditionings_for_batch(
                         conditioning_data.unconditioned_embeddings.embeds,
                         conditioning_data.text_embeddings.embeds,
                     )
@@ -280,10 +277,7 @@ class InvokeAIDiffuserComponent:
         wants_cross_attention_control = len(cross_attention_control_types_to_do) > 0
 
         if wants_cross_attention_control:
-            (
-                unconditioned_next_x,
-                conditioned_next_x,
-            ) = self._apply_cross_attention_controlled_conditioning(
+            (unconditioned_next_x, conditioned_next_x,) = self._apply_cross_attention_controlled_conditioning(
                 sample,
                 timestep,
                 conditioning_data,
@@ -291,10 +285,7 @@ class InvokeAIDiffuserComponent:
                 **kwargs,
             )
         elif self.sequential_guidance:
-            (
-                unconditioned_next_x,
-                conditioned_next_x,
-            ) = self._apply_standard_conditioning_sequentially(
+            (unconditioned_next_x, conditioned_next_x,) = self._apply_standard_conditioning_sequentially(
                 sample,
                 timestep,
                 conditioning_data,
@@ -302,10 +293,7 @@ class InvokeAIDiffuserComponent:
             )
 
         else:
-            (
-                unconditioned_next_x,
-                conditioned_next_x,
-            ) = self._apply_standard_conditioning(
+            (unconditioned_next_x, conditioned_next_x,) = self._apply_standard_conditioning(
                 sample,
                 timestep,
                 conditioning_data,

invokeai/backend/stable_diffusion/image_degradation/bsrgan.py

@@ -395,7 +395,7 @@ def add_Gaussian_noise(img, noise_level1=2, noise_level2=25):
         D = np.diag(np.random.rand(3))
         U = orth(np.random.rand(3, 3))
         conv = np.dot(np.dot(np.transpose(U), D), U)
-        img = img + np.random.multivariate_normal([0, 0, 0], np.abs(L**2 * conv), img.shape[:2]).astype(np.float32)
+        img = img + np.random.multivariate_normal([0, 0, 0], np.abs(L ** 2 * conv), img.shape[:2]).astype(np.float32)
     img = np.clip(img, 0.0, 1.0)
     return img
 
@@ -413,7 +413,7 @@ def add_speckle_noise(img, noise_level1=2, noise_level2=25):
         D = np.diag(np.random.rand(3))
         U = orth(np.random.rand(3, 3))
         conv = np.dot(np.dot(np.transpose(U), D), U)
-        img += img * np.random.multivariate_normal([0, 0, 0], np.abs(L**2 * conv), img.shape[:2]).astype(np.float32)
+        img += img * np.random.multivariate_normal([0, 0, 0], np.abs(L ** 2 * conv), img.shape[:2]).astype(np.float32)
     img = np.clip(img, 0.0, 1.0)
     return img
 

invokeai/backend/stable_diffusion/image_degradation/bsrgan_light.py

@@ -399,7 +399,7 @@ def add_Gaussian_noise(img, noise_level1=2, noise_level2=25):
         D = np.diag(np.random.rand(3))
         U = orth(np.random.rand(3, 3))
         conv = np.dot(np.dot(np.transpose(U), D), U)
-        img = img + np.random.multivariate_normal([0, 0, 0], np.abs(L**2 * conv), img.shape[:2]).astype(np.float32)
+        img = img + np.random.multivariate_normal([0, 0, 0], np.abs(L ** 2 * conv), img.shape[:2]).astype(np.float32)
     img = np.clip(img, 0.0, 1.0)
     return img
 
@@ -417,7 +417,7 @@ def add_speckle_noise(img, noise_level1=2, noise_level2=25):
         D = np.diag(np.random.rand(3))
         U = orth(np.random.rand(3, 3))
         conv = np.dot(np.dot(np.transpose(U), D), U)
-        img += img * np.random.multivariate_normal([0, 0, 0], np.abs(L**2 * conv), img.shape[:2]).astype(np.float32)
+        img += img * np.random.multivariate_normal([0, 0, 0], np.abs(L ** 2 * conv), img.shape[:2]).astype(np.float32)
     img = np.clip(img, 0.0, 1.0)
     return img
 

invokeai/backend/stable_diffusion/image_degradation/utils_image.py

@@ -562,14 +562,18 @@ def rgb2ycbcr(img, only_y=True):
     if only_y:
         rlt = np.dot(img, [65.481, 128.553, 24.966]) / 255.0 + 16.0
     else:
-        rlt = np.matmul(
-            img,
-            [
-                [65.481, -37.797, 112.0],
-                [128.553, -74.203, -93.786],
-                [24.966, 112.0, -18.214],
-            ],
-        ) / 255.0 + [16, 128, 128]
+        rlt = (
+            np.matmul(
+                img,
+                [
+                    [65.481, -37.797, 112.0],
+                    [128.553, -74.203, -93.786],
+                    [24.966, 112.0, -18.214],
+                ],
+            )
+            / 255.0
+            + [16, 128, 128]
+        )
     if in_img_type == np.uint8:
         rlt = rlt.round()
     else:
@@ -588,14 +592,18 @@ def ycbcr2rgb(img):
     if in_img_type != np.uint8:
         img *= 255.0
     # convert
-    rlt = np.matmul(
-        img,
-        [
-            [0.00456621, 0.00456621, 0.00456621],
-            [0, -0.00153632, 0.00791071],
-            [0.00625893, -0.00318811, 0],
-        ],
-    ) * 255.0 + [-222.921, 135.576, -276.836]
+    rlt = (
+        np.matmul(
+            img,
+            [
+                [0.00456621, 0.00456621, 0.00456621],
+                [0, -0.00153632, 0.00791071],
+                [0.00625893, -0.00318811, 0],
+            ],
+        )
+        * 255.0
+        + [-222.921, 135.576, -276.836]
+    )
     if in_img_type == np.uint8:
         rlt = rlt.round()
     else:
@@ -618,14 +626,18 @@ def bgr2ycbcr(img, only_y=True):
     if only_y:
         rlt = np.dot(img, [24.966, 128.553, 65.481]) / 255.0 + 16.0
     else:
-        rlt = np.matmul(
-            img,
-            [
-                [24.966, 112.0, -18.214],
-                [128.553, -74.203, -93.786],
-                [65.481, -37.797, 112.0],
-            ],
-        ) / 255.0 + [16, 128, 128]
+        rlt = (
+            np.matmul(
+                img,
+                [
+                    [24.966, 112.0, -18.214],
+                    [128.553, -74.203, -93.786],
+                    [65.481, -37.797, 112.0],
+                ],
+            )
+            / 255.0
+            + [16, 128, 128]
+        )
     if in_img_type == np.uint8:
         rlt = rlt.round()
     else:
@@ -716,11 +728,11 @@ def ssim(img1, img2):
 
     mu1 = cv2.filter2D(img1, -1, window)[5:-5, 5:-5]  # valid
     mu2 = cv2.filter2D(img2, -1, window)[5:-5, 5:-5]
-    mu1_sq = mu1**2
-    mu2_sq = mu2**2
+    mu1_sq = mu1 ** 2
+    mu2_sq = mu2 ** 2
     mu1_mu2 = mu1 * mu2
-    sigma1_sq = cv2.filter2D(img1**2, -1, window)[5:-5, 5:-5] - mu1_sq
-    sigma2_sq = cv2.filter2D(img2**2, -1, window)[5:-5, 5:-5] - mu2_sq
+    sigma1_sq = cv2.filter2D(img1 ** 2, -1, window)[5:-5, 5:-5] - mu1_sq
+    sigma2_sq = cv2.filter2D(img2 ** 2, -1, window)[5:-5, 5:-5] - mu2_sq
     sigma12 = cv2.filter2D(img1 * img2, -1, window)[5:-5, 5:-5] - mu1_mu2
 
     ssim_map = ((2 * mu1_mu2 + C1) * (2 * sigma12 + C2)) / ((mu1_sq + mu2_sq + C1) * (sigma1_sq + sigma2_sq + C2))
@@ -737,8 +749,8 @@ def ssim(img1, img2):
 # matlab 'imresize' function, now only support 'bicubic'
 def cubic(x):
     absx = torch.abs(x)
-    absx2 = absx**2
-    absx3 = absx**3
+    absx2 = absx ** 2
+    absx3 = absx ** 3
     return (1.5 * absx3 - 2.5 * absx2 + 1) * ((absx <= 1).type_as(absx)) + (
         -0.5 * absx3 + 2.5 * absx2 - 4 * absx + 2
     ) * (((absx > 1) * (absx <= 2)).type_as(absx))

invokeai/backend/training/textual_inversion_training.py

@@ -475,10 +475,7 @@ class TextualInversionDataset(Dataset):
 
         if self.center_crop:
             crop = min(img.shape[0], img.shape[1])
-            (
-                h,
-                w,
-            ) = (
+            (h, w,) = (
                 img.shape[0],
                 img.shape[1],
             )

invokeai/backend/util/mps_fixes.py

@@ -203,7 +203,7 @@ class ChunkedSlicedAttnProcessor:
         if attn.upcast_attention:
             out_item_size = 4
 
-        chunk_size = 2**29
+        chunk_size = 2 ** 29
 
         out_size = query.shape[1] * key.shape[1] * out_item_size
         chunks_count = min(query.shape[1], math.ceil((out_size - 1) / chunk_size))

invokeai/backend/util/util.py

@@ -207,7 +207,7 @@ def parallel_data_prefetch(
         return gather_res
 
 
-def rand_perlin_2d(shape, res, device, fade=lambda t: 6 * t**5 - 15 * t**4 + 10 * t**3):
+def rand_perlin_2d(shape, res, device, fade=lambda t: 6 * t ** 5 - 15 * t ** 4 + 10 * t ** 3):
     delta = (res[0] / shape[0], res[1] / shape[1])
     d = (shape[0] // res[0], shape[1] // res[1])
 

invokeai/configs/INITIAL_MODELS.yaml

@@ -4,14 +4,14 @@ sd-1/main/stable-diffusion-v1-5:
    repo_id: runwayml/stable-diffusion-v1-5
    recommended: True
    default: True
-sd-1/main/stable-diffusion-inpainting:
+sd-1/main/stable-diffusion-v1-5-inpainting:
    description: RunwayML SD 1.5 model optimized for inpainting, diffusers version (4.27 GB)
    repo_id: runwayml/stable-diffusion-inpainting
    recommended: True
 sd-2/main/stable-diffusion-2-1:
    description: Stable Diffusion version 2.1 diffusers model, trained on 768 pixel images (5.21 GB)
    repo_id: stabilityai/stable-diffusion-2-1
-   recommended: True
+   recommended: False
 sd-2/main/stable-diffusion-2-inpainting:
    description: Stable Diffusion version 2.0 inpainting model (5.21 GB)
    repo_id: stabilityai/stable-diffusion-2-inpainting
@@ -19,19 +19,19 @@ sd-2/main/stable-diffusion-2-inpainting:
 sdxl/main/stable-diffusion-xl-base-1-0:
    description: Stable Diffusion XL base model (12 GB)
    repo_id: stabilityai/stable-diffusion-xl-base-1.0
-   recommended: False
+   recommended: True
 sdxl-refiner/main/stable-diffusion-xl-refiner-1-0:
    description: Stable Diffusion XL refiner model (12 GB)
    repo_id: stabilityai/stable-diffusion-xl-refiner-1.0
-   recommended: false
+   recommended: False
 sdxl/vae/sdxl-1-0-vae-fix:
    description: Fine tuned version of the SDXL-1.0 VAE
    repo_id: madebyollin/sdxl-vae-fp16-fix
-   recommended: true
+   recommended: True
 sd-1/main/Analog-Diffusion:
    description: An SD-1.5 model trained on diverse analog photographs (2.13 GB)
    repo_id: wavymulder/Analog-Diffusion
-   recommended: false
+   recommended: False
 sd-1/main/Deliberate:
    description: Versatile model that produces detailed images up to 768px (4.27 GB)
    repo_id: XpucT/Deliberate

invokeai/frontend/install/import_images.py

@@ -60,7 +60,7 @@ class Config:
     thumbnail_path = None
 
     def find_and_load(self):
-        """find the yaml config file and load"""
+        """Find the yaml config file and load"""
         root = app_config.root_path
         if not self.confirm_and_load(os.path.abspath(root)):
             print("\r\nSpecify custom database and outputs paths:")
@@ -70,7 +70,7 @@ class Config:
         self.thumbnail_path = os.path.join(self.outputs_path, "thumbnails")
 
     def confirm_and_load(self, invoke_root):
-        """Validates a yaml path exists, confirms the user wants to use it and loads config."""
+        """Validate a yaml path exists, confirms the user wants to use it and loads config."""
         yaml_path = os.path.join(invoke_root, self.YAML_FILENAME)
         if os.path.exists(yaml_path):
             db_dir, outdir = self.load_paths_from_yaml(yaml_path)
@@ -337,33 +337,24 @@ class InvokeAIMetadataParser:
 
     def map_scheduler(self, old_scheduler):
         """Convert the legacy sampler names to matching 3.0 schedulers"""
+
+        # this was more elegant as a case statement, but that's not available in python 3.9
         if old_scheduler is None:
             return None
-
-        match (old_scheduler):
-            case "ddim":
-                return "ddim"
-            case "plms":
-                return "pnmd"
-            case "k_lms":
-                return "lms"
-            case "k_dpm_2":
-                return "kdpm_2"
-            case "k_dpm_2_a":
-                return "kdpm_2_a"
-            case "dpmpp_2":
-                return "dpmpp_2s"
-            case "k_dpmpp_2":
-                return "dpmpp_2m"
-            case "k_dpmpp_2_a":
-                return None  # invalid, in 2.3.x, selecting this sample would just fallback to last run or plms if new session
-            case "k_euler":
-                return "euler"
-            case "k_euler_a":
-                return "euler_a"
-            case "k_heun":
-                return "heun"
-        return None
+        scheduler_map = dict(
+            ddim="ddim",
+            plms="pnmd",
+            k_lms="lms",
+            k_dpm_2="kdpm_2",
+            k_dpm_2_a="kdpm_2_a",
+            dpmpp_2="dpmpp_2s",
+            k_dpmpp_2="dpmpp_2m",
+            k_dpmpp_2_a=None,  # invalid, in 2.3.x, selecting this sample would just fallback to last run or plms if new session
+            k_euler="euler",
+            k_euler_a="euler_a",
+            k_heun="heun",
+        )
+        return scheduler_map.get(old_scheduler)
 
     def split_prompt(self, raw_prompt: str):
         """Split the unified prompt strings by extracting all negative prompt blocks out into the negative prompt."""
@@ -524,27 +515,27 @@ class MediaImportProcessor:
                 "5) Create/add to board named 'IMPORT' with a the original file app_version appended (.e.g IMPORT_2.2.5)."
             )
             input_option = input("Specify desired board option: ")
-            match (input_option):
-                case "1":
-                    if len(board_names) < 1:
-                        print("\r\nThere are no existing board names to choose from. Select another option!")
-                        continue
-                    board_name = self.select_item_from_list(
-                        board_names, "board name", True, "Cancel, go back and choose a different board option."
-                    )
-                    if board_name is not None:
+            # This was more elegant as a case statement, but not supported in python 3.9
+            if input_option == "1":
+                if len(board_names) < 1:
+                    print("\r\nThere are no existing board names to choose from. Select another option!")
+                    continue
+                board_name = self.select_item_from_list(
+                    board_names, "board name", True, "Cancel, go back and choose a different board option."
+                )
+                if board_name is not None:
+                    return board_name
+            elif input_option == "2":
+                while True:
+                    board_name = input("Specify new/existing board name: ")
+                    if board_name:
                         return board_name
-                case "2":
-                    while True:
-                        board_name = input("Specify new/existing board name: ")
-                        if board_name:
-                            return board_name
-                case "3":
-                    return "IMPORT"
-                case "4":
-                    return f"IMPORT_{timestamp_string}"
-                case "5":
-                    return "IMPORT_APPVERSION"
+            elif input_option == "3":
+                return "IMPORT"
+            elif input_option == "4":
+                return f"IMPORT_{timestamp_string}"
+            elif input_option == "5":
+                return "IMPORT_APPVERSION"
 
     def select_item_from_list(self, items, entity_name, allow_cancel, cancel_string):
         """A general function to render a list of items to select in the console, prompt the user for a selection and ensure a valid entry is selected."""

invokeai/frontend/web/dist/assets/ThemeLocaleProvider-90f0fcd3.css

@@ -1,4 +1,4 @@
-@font-face{font-family:Inter Variable;font-style:normal;font-display:swap;font-weight:100 900;src:url(./inter-cyrillic-ext-wght-normal-848492d3.woff2) format("woff2-variations");unicode-range:U+0460-052F,U+1C80-1C88,U+20B4,U+2DE0-2DFF,U+A640-A69F,U+FE2E-FE2F}@font-face{font-family:Inter Variable;font-style:normal;font-display:swap;font-weight:100 900;src:url(./inter-cyrillic-wght-normal-262a1054.woff2) format("woff2-variations");unicode-range:U+0301,U+0400-045F,U+0490-0491,U+04B0-04B1,U+2116}@font-face{font-family:Inter Variable;font-style:normal;font-display:swap;font-weight:100 900;src:url(./inter-greek-ext-wght-normal-fe977ddb.woff2) format("woff2-variations");unicode-range:U+1F00-1FFF}@font-face{font-family:Inter Variable;font-style:normal;font-display:swap;font-weight:100 900;src:url(./inter-greek-wght-normal-89b4a3fe.woff2) format("woff2-variations");unicode-range:U+0370-03FF}@font-face{font-family:Inter Variable;font-style:normal;font-display:swap;font-weight:100 900;src:url(./inter-vietnamese-wght-normal-ac4e131c.woff2) format("woff2-variations");unicode-range:U+0102-0103,U+0110-0111,U+0128-0129,U+0168-0169,U+01A0-01A1,U+01AF-01B0,U+0300-0301,U+0303-0304,U+0308-0309,U+0323,U+0329,U+1EA0-1EF9,U+20AB}@font-face{font-family:Inter Variable;font-style:normal;font-display:swap;font-weight:100 900;src:url(./inter-latin-ext-wght-normal-45606f83.woff2) format("woff2-variations");unicode-range:U+0100-02AF,U+0300-0301,U+0303-0304,U+0308-0309,U+0323,U+0329,U+1E00-1EFF,U+2020,U+20A0-20AB,U+20AD-20CF,U+2113,U+2C60-2C7F,U+A720-A7FF}@font-face{font-family:Inter Variable;font-style:normal;font-display:swap;font-weight:100 900;src:url(./inter-latin-wght-normal-450f3ba4.woff2) format("woff2-variations");unicode-range:U+0000-00FF,U+0131,U+0152-0153,U+02BB-02BC,U+02C6,U+02DA,U+02DC,U+0300-0301,U+0303-0304,U+0308-0309,U+0323,U+0329,U+2000-206F,U+2074,U+20AC,U+2122,U+2191,U+2193,U+2212,U+2215,U+FEFF,U+FFFD}/*! 
+@font-face{font-family:Inter Variable;font-style:normal;font-display:swap;font-weight:100 900;src:url(./inter-cyrillic-ext-wght-normal-848492d3.woff2) format("woff2-variations");unicode-range:U+0460-052F,U+1C80-1C88,U+20B4,U+2DE0-2DFF,U+A640-A69F,U+FE2E-FE2F}@font-face{font-family:Inter Variable;font-style:normal;font-display:swap;font-weight:100 900;src:url(./inter-cyrillic-wght-normal-262a1054.woff2) format("woff2-variations");unicode-range:U+0301,U+0400-045F,U+0490-0491,U+04B0-04B1,U+2116}@font-face{font-family:Inter Variable;font-style:normal;font-display:swap;font-weight:100 900;src:url(./inter-greek-ext-wght-normal-fe977ddb.woff2) format("woff2-variations");unicode-range:U+1F00-1FFF}@font-face{font-family:Inter Variable;font-style:normal;font-display:swap;font-weight:100 900;src:url(./inter-greek-wght-normal-89b4a3fe.woff2) format("woff2-variations");unicode-range:U+0370-03FF}@font-face{font-family:Inter Variable;font-style:normal;font-display:swap;font-weight:100 900;src:url(./inter-vietnamese-wght-normal-ac4e131c.woff2) format("woff2-variations");unicode-range:U+0102-0103,U+0110-0111,U+0128-0129,U+0168-0169,U+01A0-01A1,U+01AF-01B0,U+0300-0301,U+0303-0304,U+0308-0309,U+0323,U+0329,U+1EA0-1EF9,U+20AB}@font-face{font-family:Inter Variable;font-style:normal;font-display:swap;font-weight:100 900;src:url(./inter-latin-ext-wght-normal-45606f83.woff2) format("woff2-variations");unicode-range:U+0100-02AF,U+0304,U+0308,U+0329,U+1E00-1E9F,U+1EF2-1EFF,U+2020,U+20A0-20AB,U+20AD-20CF,U+2113,U+2C60-2C7F,U+A720-A7FF}@font-face{font-family:Inter Variable;font-style:normal;font-display:swap;font-weight:100 900;src:url(./inter-latin-wght-normal-450f3ba4.woff2) format("woff2-variations");unicode-range:U+0000-00FF,U+0131,U+0152-0153,U+02BB-02BC,U+02C6,U+02DA,U+02DC,U+0304,U+0308,U+0329,U+2000-206F,U+2074,U+20AC,U+2122,U+2191,U+2193,U+2212,U+2215,U+FEFF,U+FFFD}/*! 
 * OverlayScrollbars
 * Version: 2.2.1
 * 

invokeai/frontend/web/dist/index.html

@@ -12,7 +12,7 @@
         margin: 0;
       }
     </style>
-    <script type="module" crossorigin src="./assets/index-2c171c8f.js"></script>
+    <script type="module" crossorigin src="./assets/index-08cda350.js"></script>
   </head>
 
   <body dir="ltr">

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

@@ -19,7 +19,7 @@
         "toggleAutoscroll": "Toggle autoscroll",
         "toggleLogViewer": "Toggle Log Viewer",
         "showGallery": "Show Gallery",
-        "showOptionsPanel": "Show Options Panel",
+        "showOptionsPanel": "Show Side Panel",
         "menu": "Menu"
     },
     "common": {
@@ -52,7 +52,7 @@
         "img2img": "Image To Image",
         "unifiedCanvas": "Unified Canvas",
         "linear": "Linear",
-        "nodes": "Node Editor",
+        "nodes": "Workflow Editor",
         "batch": "Batch Manager",
         "modelManager": "Model Manager",
         "postprocessing": "Post Processing",
@@ -95,7 +95,6 @@
         "statusModelConverted": "Model Converted",
         "statusMergingModels": "Merging Models",
         "statusMergedModels": "Models Merged",
-        "pinOptionsPanel": "Pin Options Panel",
         "loading": "Loading",
         "loadingInvokeAI": "Loading Invoke AI",
         "random": "Random",
@@ -116,7 +115,6 @@
         "maintainAspectRatio": "Maintain Aspect Ratio",
         "autoSwitchNewImages": "Auto-Switch to New Images",
         "singleColumnLayout": "Single Column Layout",
-        "pinGallery": "Pin Gallery",
         "allImagesLoaded": "All Images Loaded",
         "loadMore": "Load More",
         "noImagesInGallery": "No Images to Display",
@@ -133,6 +131,7 @@
         "generalHotkeys": "General Hotkeys",
         "galleryHotkeys": "Gallery Hotkeys",
         "unifiedCanvasHotkeys": "Unified Canvas Hotkeys",
+        "nodesHotkeys": "Nodes Hotkeys",
         "invoke": {
             "title": "Invoke",
             "desc": "Generate an image"
@@ -332,6 +331,10 @@
         "acceptStagingImage": {
             "title": "Accept Staging Image",
             "desc": "Accept Current Staging Area Image"
+        },
+        "addNodes": {
+            "title": "Add Nodes",
+            "desc": "Opens the add node menu"
         }
     },
     "modelManager": {
@@ -503,13 +506,15 @@
         "hiresStrength": "High Res Strength",
         "imageFit": "Fit Initial Image To Output Size",
         "codeformerFidelity": "Fidelity",
+        "compositingSettingsHeader": "Compositing Settings",
         "maskAdjustmentsHeader": "Mask Adjustments",
-        "maskBlur": "Mask Blur",
-        "maskBlurMethod": "Mask Blur Method",
-        "seamSize": "Seam Size",
-        "seamBlur": "Seam Blur",
-        "seamStrength": "Seam Strength",
-        "seamSteps": "Seam Steps",
+        "maskBlur": "Blur",
+        "maskBlurMethod": "Blur Method",
+        "coherencePassHeader": "Coherence Pass",
+        "coherenceSteps": "Steps",
+        "coherenceStrength": "Strength",
+        "seamLowThreshold": "Low",
+        "seamHighThreshold": "High",
         "scaleBeforeProcessing": "Scale Before Processing",
         "scaledWidth": "Scaled W",
         "scaledHeight": "Scaled H",
@@ -565,10 +570,11 @@
         "useSlidersForAll": "Use Sliders For All Options",
         "showProgressInViewer": "Show Progress Images in Viewer",
         "antialiasProgressImages": "Antialias Progress Images",
+        "autoChangeDimensions": "Update W/H To Model Defaults On Change",
         "resetWebUI": "Reset Web UI",
         "resetWebUIDesc1": "Resetting the web UI only resets the browser's local cache of your images and remembered settings. It does not delete any images from disk.",
         "resetWebUIDesc2": "If images aren't showing up in the gallery or something else isn't working, please try resetting before submitting an issue on GitHub.",
-        "resetComplete": "Web UI has been reset. Refresh the page to reload.",
+        "resetComplete": "Web UI has been reset.",
         "consoleLogLevel": "Log Level",
         "shouldLogToConsole": "Console Logging",
         "developer": "Developer",
@@ -708,14 +714,16 @@
     "ui": {
         "showProgressImages": "Show Progress Images",
         "hideProgressImages": "Hide Progress Images",
-        "swapSizes": "Swap Sizes"
+        "swapSizes": "Swap Sizes",
+        "lockRatio": "Lock Ratio"
     },
     "nodes": {
-        "reloadSchema": "Reload Schema",
-        "saveGraph": "Save Graph",
-        "loadGraph": "Load Graph (saved from Node Editor) (Do not copy-paste metadata)",
-        "clearGraph": "Clear Graph",
-        "clearGraphDesc": "Are you sure you want to clear all nodes?",
+        "reloadNodeTemplates": "Reload Node Templates",
+        "downloadWorkflow": "Download Workflow JSON",
+        "loadWorkflow": "Load Workflow",
+        "resetWorkflow": "Reset Workflow",
+        "resetWorkflowDesc": "Are you sure you want to reset this workflow?",
+        "resetWorkflowDesc2": "Resetting the workflow will clear all nodes, edges and workflow details.",
         "zoomInNodes": "Zoom In",
         "zoomOutNodes": "Zoom Out",
         "fitViewportNodes": "Fit View",

invokeai/frontend/web/src/features/nodes/types/types.ts

@@ -280,7 +280,7 @@ export type ConditioningInputFieldValue = z.infer<
 export const zControlNetModel = zModelIdentifier;
 export type ControlNetModel = z.infer<typeof zControlNetModel>;
 
-export const zControlField = zInputFieldValueBase.extend({
+export const zControlField = z.object({
   image: zImageField,
   control_model: zControlNetModel,
   control_weight: z.union([z.number(), z.array(z.number())]).optional(),
@@ -295,11 +295,11 @@ export const zControlField = zInputFieldValueBase.extend({
 });
 export type ControlField = z.infer<typeof zControlField>;
 
-export const zControlInputFieldTemplate = zInputFieldValueBase.extend({
+export const zControlInputFieldValue = zInputFieldValueBase.extend({
   type: z.literal('ControlField'),
   value: zControlField.optional(),
 });
-export type ControlInputFieldValue = z.infer<typeof zControlInputFieldTemplate>;
+export type ControlInputFieldValue = z.infer<typeof zControlInputFieldValue>;
 
 export const zModelType = z.enum([
   'onnx',
@@ -492,7 +492,7 @@ export const zInputFieldValue = z.discriminatedUnion('type', [
   zUNetInputFieldValue,
   zClipInputFieldValue,
   zVaeInputFieldValue,
-  zControlInputFieldTemplate,
+  zControlInputFieldValue,
   zEnumInputFieldValue,
   zMainModelInputFieldValue,
   zSDXLMainModelInputFieldValue,

invokeai/frontend/web/src/features/nodes/util/buildWorkflow.ts

@@ -12,17 +12,21 @@ export const buildWorkflow = (nodesState: NodesState): Workflow => {
     edges: [],
   };
 
-  nodes.forEach((node) => {
-    const result = zWorkflowNode.safeParse(node);
-    if (!result.success) {
-      const { message } = fromZodError(result.error, {
-        prefix: 'Unable to parse node',
-      });
-      logger('nodes').warn({ node: parseify(node) }, message);
-      return;
-    }
-    workflow.nodes.push(result.data);
-  });
+  nodes
+    .filter((n) =>
+      ['invocation', 'notes'].includes(n.type ?? '__UNKNOWN_NODE_TYPE__')
+    )
+    .forEach((node) => {
+      const result = zWorkflowNode.safeParse(node);
+      if (!result.success) {
+        const { message } = fromZodError(result.error, {
+          prefix: 'Unable to parse node',
+        });
+        logger('nodes').warn({ node: parseify(node) }, message);
+        return;
+      }
+      workflow.nodes.push(result.data);
+    });
 
   edges.forEach((edge) => {
     const result = zWorkflowEdge.safeParse(edge);

invokeai/version/invokeai_version.py

@@ -1 +1 @@
-__version__ = "3.0.2post1"
+__version__ = "3.1.0"