repo stringclasses 454
values | file_path stringlengths 5 201 | extension stringclasses 1
value | content stringlengths 8 509k | num_lines int64 3 16.9k | size_bytes int64 8 511k |
|---|---|---|---|---|---|
InvokeAI | invokeai/app/invocations/flux_control_lora_loader.py | .py | from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
invocation,
invocation_output,
)
from invokeai.app.invocations.fields import FieldDescriptions, ImageField, InputField, OutputField
from invokeai.app.invocations.model import ControlLoRAField, ModelIdentifierFiel... | 52 | 1,872 |
InvokeAI | invokeai/app/invocations/ideogram4_model_loader.py | .py | from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
Classification,
invocation,
invocation_output,
)
from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField
from invokeai.app.invocations.model import (
ModelIdentifierF... | 65 | 2,519 |
InvokeAI | invokeai/app/invocations/pid_decoder_loader.py | .py | from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
Classification,
invocation,
invocation_output,
)
from invokeai.app.invocations.fields import InputField, OutputField
from invokeai.app.invocations.model import ModelIdentifierField, PiDDecoderField
from invok... | 45 | 1,616 |
InvokeAI | invokeai/app/invocations/anima_denoise.py | .py | """Anima denoising invocation.
Implements the rectified flow denoising loop for Anima models:
- Direct prediction: denoised = input - output * sigma
- Fixed shift=3.0 via loglinear_timestep_shift (Flux paper by Black Forest Labs)
- Timestep convention: timestep = sigma * 1.0 (raw sigma, NOT 1-sigma like Z-Image)
- NO ... | 945 | 43,995 |
InvokeAI | invokeai/app/invocations/anima_latents_to_image.py | .py | """Anima latents-to-image invocation.
Decodes Anima latents using the QwenImage VAE (AutoencoderKLWan) or
compatible FLUX VAE as fallback.
Latents from the denoiser are in normalized space (zero-centered). Before
VAE decode, they must be denormalized using the Wan 2.1 per-channel
mean/std: latents = latents * std + m... | 210 | 9,789 |
InvokeAI | invokeai/app/invocations/ideogram4_caption.py | .py | from typing import Annotated, Optional
from pydantic import BaseModel, Field, field_validator
from invokeai.app.invocations.baseinvocation import BaseInvocation, Classification, invocation
from invokeai.app.invocations.fields import InputField, UIComponent
from invokeai.app.invocations.primitives import StringOutput
... | 92 | 3,947 |
InvokeAI | invokeai/app/invocations/sdxl_pid_decode.py | .py | """SDXL PiD decode invocation.
Replaces SDXL's AutoencoderKL decode with the PiD pixel-diffusion super-res
decoder (``PiD_res2kto4k_sr4x_official_sdxl_distill_4step``). Produces a 4x
super-resolved image from an SDXL latent in a single 4-step distill pass.
SDXL latents are 4-channel at an 8x spatial down-factor (``_P... | 211 | 10,175 |
InvokeAI | invokeai/app/invocations/wan_model_loader.py | .py | from typing import Optional
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
Classification,
invocation,
invocation_output,
)
from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField
from invokeai.app.invocations.model ... | 339 | 17,836 |
InvokeAI | invokeai/app/invocations/z_image_text_encoder.py | .py | from contextlib import ExitStack
from typing import Iterator, Optional
import torch
from transformers import PreTrainedModel, PreTrainedTokenizerBase
from invokeai.app.invocations.baseinvocation import BaseInvocation, Classification, invocation
from invokeai.app.invocations.fields import (
FieldDescriptions,
... | 210 | 9,781 |
InvokeAI | invokeai/app/invocations/z_image_latents_to_image.py | .py | from contextlib import nullcontext
from typing import Union
import torch
from diffusers.models.autoencoders.autoencoder_kl import AutoencoderKL
from einops import rearrange
from PIL import Image
from invokeai.app.invocations.baseinvocation import BaseInvocation, Classification, invocation
from invokeai.app.invocation... | 115 | 4,930 |
InvokeAI | invokeai/app/invocations/scheduler.py | .py | from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output
from invokeai.app.invocations.fields import (
FieldDescriptions,
InputField,
OutputField,
UIType,
)
from invokeai.app.services.shared.invocation_context import InvocationContext
from i... | 35 | 1,101 |
InvokeAI | invokeai/app/invocations/qwen_image_pid_decode.py | .py | """Qwen-Image PiD decode invocation.
Replaces Qwen-Image's AutoencoderKLQwenImage decode with the PiD pixel-diffusion
super-res decoder (``PiD_res2kto4k_sr4x_official_qwenimage_distill_4step``).
Produces a 4x super-resolved image from a Qwen-Image latent in a single 4-step
distill pass.
Qwen-Image is 16-channel at an... | 238 | 12,059 |
InvokeAI | invokeai/app/invocations/crop_latents.py | .py | from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR
from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, LatentsField
from invokeai.app.invocations.primitives import LatentsOutput
from invokeai.app... | 62 | 2,718 |
InvokeAI | invokeai/app/invocations/llava_onevision_vllm.py | .py | from typing import Any
import torch
from PIL.Image import Image
from pydantic import field_validator
from transformers import AutoProcessor, LlavaOnevisionForConditionalGeneration, LlavaOnevisionProcessor
from invokeai.app.invocations.baseinvocation import BaseInvocation, Classification, invocation
from invokeai.app.... | 77 | 2,981 |
InvokeAI | invokeai/app/invocations/flux2_klein_text_encoder.py | .py | """Flux2 Klein Text Encoder Invocation.
Flux2 Klein uses Qwen3 as the text encoder instead of CLIP+T5.
The key difference is that it extracts hidden states from layers (9, 18, 27)
and stacks them together for richer text representations.
This implementation matches the diffusers Flux2KleinPipeline exactly.
"""
from ... | 210 | 9,264 |
InvokeAI | invokeai/app/invocations/z_image_model_loader.py | .py | from typing import Optional
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
Classification,
invocation,
invocation_output,
)
from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField
from invokeai.app.invocations.model ... | 178 | 9,026 |
InvokeAI | invokeai/app/invocations/upscale.py | .py | # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654) & the InvokeAI Team
from typing import Literal
import cv2
import numpy as np
from PIL import Image
from pydantic import ConfigDict
from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
from invokeai.app.invocations.fields imp... | 115 | 4,430 |
InvokeAI | invokeai/app/invocations/resize_latents.py | .py | from typing import Literal
import torch
from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR
from invokeai.app.invocations.fields import (
FieldDescriptions,
Input,
InputField,
LatentsField,
)
from invokeai.ap... | 104 | 3,802 |
InvokeAI | invokeai/app/invocations/gemma2_encoder_loader.py | .py | from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
Classification,
invocation,
invocation_output,
)
from invokeai.app.invocations.fields import InputField, OutputField
from invokeai.app.invocations.model import Gemma2EncoderField, ModelIdentifierField
from in... | 50 | 1,874 |
InvokeAI | invokeai/app/invocations/cogview4_denoise.py | .py | from typing import Callable, Optional
import torch
import torchvision.transforms as tv_transforms
from diffusers.models.transformers.transformer_cogview4 import CogView4Transformer2DModel
from torchvision.transforms.functional import resize as tv_resize
from tqdm import tqdm
from invokeai.app.invocations.baseinvocati... | 378 | 16,962 |
InvokeAI | invokeai/app/invocations/wan_ideal_dimensions.py | .py | """Compute Wan 2.2-compatible pixel dimensions for a target short-side resolution.
Wan's transformer ``patch_size=(1, 2, 2)`` adds a 2x patchify on top of the VAE's
spatial compression, so pixel dimensions must be a multiple of (2 × VAE scale):
- I2V-A14B / T2V (8x VAE) → multiples of 16
- TI2V-5B (Wan 2.2... | 210 | 8,285 |
InvokeAI | invokeai/app/invocations/image_to_latents.py | .py | from contextlib import nullcontext
from functools import singledispatchmethod
from typing import Literal
import einops
import torch
from diffusers.models.attention_processor import (
AttnProcessor2_0,
LoRAAttnProcessor2_0,
LoRAXFormersAttnProcessor,
XFormersAttnProcessor,
)
from diffusers.models.autoen... | 183 | 7,452 |
InvokeAI | invokeai/app/invocations/krea2_lora_loader.py | .py | from typing import Optional
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
invocation,
invocation_output,
)
from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField
from invokeai.app.invocations.model import LoRAField, Mo... | 186 | 7,763 |
InvokeAI | invokeai/app/invocations/pidi.py | .py | from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
from invokeai.app.invocations.fields import FieldDescriptions, ImageField, InputField, WithBoard, WithMetadata
from invokeai.app.invocations.primitives import ImageOutput
from invokeai.app.services.shared.invocation_context import Invocation... | 34 | 1,598 |
InvokeAI | invokeai/app/invocations/model.py | .py | import copy
from typing import List, Optional
from pydantic import BaseModel, Field
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
invocation,
invocation_output,
)
from invokeai.app.invocations.fields import FieldDescriptions, ImageField, Input, InputField,... | 751 | 28,693 |
InvokeAI | invokeai/app/invocations/infill.py | .py | from abc import abstractmethod
from typing import Literal, get_args
from PIL import Image
from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
from invokeai.app.invocations.fields import ColorField, ImageField, InputField, WithBoard, WithMetadata
from invokeai.app.invocations.image import PI... | 174 | 7,069 |
InvokeAI | invokeai/app/invocations/wan_text_encoder.py | .py | import torch
from invokeai.app.invocations.baseinvocation import BaseInvocation, Classification, invocation
from invokeai.app.invocations.fields import (
FieldDescriptions,
Input,
InputField,
UIComponent,
)
from invokeai.app.invocations.model import WanT5EncoderField
from invokeai.app.invocations.primi... | 114 | 4,892 |
InvokeAI | invokeai/app/invocations/anima_image_to_latents.py | .py | """Anima image-to-latents invocation.
Encodes an image to latent space using the Anima VAE (AutoencoderKLWan or FLUX VAE).
For Wan VAE (AutoencoderKLWan):
- Input image is converted to 5D tensor [B, C, T, H, W] with T=1
- After encoding, latents are normalized: (latents - mean) / std
(inverse of the denormalization... | 134 | 5,862 |
InvokeAI | invokeai/app/invocations/util.py | .py | from typing import Union
def validate_weights(weights: Union[float, list[float]]) -> None:
"""Validate that all control weights in the valid range"""
to_validate = weights if isinstance(weights, list) else [weights]
if any(i < -1 or i > 2 for i in to_validate):
raise ValueError("Control weights mu... | 15 | 665 |
InvokeAI | invokeai/app/invocations/compel.py | .py | from typing import Iterator, List, Optional, Tuple, Union, cast
import torch
from compel import Compel, ReturnedEmbeddingsType, SplitLongTextMode
from compel.prompt_parser import Blend, Conjunction, CrossAttentionControlSubstitute, FlattenedPrompt, Fragment
from transformers import CLIPTextModel, CLIPTextModelWithProj... | 535 | 20,643 |
InvokeAI | invokeai/app/invocations/wan_image_to_latents.py | .py | """Wan 2.2 image-to-latents invocation.
Encodes an image to latent space using the Wan VAE (AutoencoderKLWan). The Wan
VAE expects 5D ``[B, C, T, H, W]`` input with ``T=1`` for single images. After
encoding, latents are normalised against the per-channel ``latents_mean`` and
``latents_std`` stored in the VAE config — ... | 107 | 4,584 |
InvokeAI | invokeai/app/invocations/external_image_generation.py | .py | from typing import TYPE_CHECKING, Any, ClassVar, Literal
from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, invocation
from invokeai.app.invocations.fields import (
FieldDescriptions,
ImageField,
InputField,
MetadataField,
WithBoard,
WithMetadata,
)
from i... | 352 | 14,972 |
InvokeAI | invokeai/app/invocations/segment_anything.py | .py | from itertools import zip_longest
from pathlib import Path
from typing import Literal
import numpy as np
import torch
from PIL import Image
from pydantic import BaseModel, Field, model_validator
from transformers.models.sam import SamModel
from transformers.models.sam.processing_sam import SamProcessor
from transforme... | 218 | 10,416 |
InvokeAI | invokeai/app/invocations/z_image_pid_decode.py | .py | """Z-Image PiD decode invocation.
Z-Image shares FLUX.1's 16-channel VAE, so the FLUX-trained PiD decoder
(``PiD_res2k_sr4x_official_flux_distill_4step``) is the correct choice for
Z-Image latents. This node replaces the regular Z-Image VAE decode with a
PiD super-resolution decode (4x scale, ~256×256 latent → 2048×20... | 230 | 11,199 |
InvokeAI | invokeai/app/invocations/mask.py | .py | import numpy as np
import torch
from PIL import Image
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
InvocationContext,
invocation,
)
from invokeai.app.invocations.fields import (
BoundingBoxField,
ColorField,
ImageField,
InputField,
TensorField,
WithBoard,
... | 267 | 9,508 |
InvokeAI | invokeai/app/invocations/__init__.py | .py | from pathlib import Path
# add core nodes to __all__
python_files = filter(lambda f: not f.name.startswith("_"), Path(__file__).parent.glob("*.py"))
__all__ = [f.stem for f in python_files] # type: ignore
| 6 | 207 |
InvokeAI | invokeai/app/invocations/flux_pid_decode.py | .py | """FLUX PiD decode invocation.
Replaces the regular FLUX VAE decode with the PiD pixel-diffusion super-res
decoder (``PiD_res2k_sr4x_official_flux_distill_4step``). Produces a 4x
super-resolved image from a FLUX latent in a single 4-step distill pass.
"""
from contextlib import ExitStack
import torch
from einops imp... | 172 | 7,877 |
InvokeAI | invokeai/app/invocations/image.py | .py | # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
from pathlib import Path
from typing import Literal, Optional
import cv2
import numpy
import torch
from PIL import Image, ImageChops, ImageFilter, ImageOps
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
Classification,... | 1,681 | 64,109 |
InvokeAI | invokeai/app/invocations/constants.py | .py | from typing import Literal
LATENT_SCALE_FACTOR = 8
"""
HACK: Many nodes are currently hard-coded to use a fixed latent scale factor of 8. This is fragile, and will need to
be addressed if future models use a different latent scale factor. Also, note that there may be places where the scale
factor is hard-coded to a li... | 13 | 583 |
InvokeAI | invokeai/app/invocations/wan_lora_loader.py | .py | from typing import Literal, Optional
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
Classification,
invocation,
invocation_output,
)
from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField
from invokeai.app.invocatio... | 266 | 10,763 |
InvokeAI | invokeai/app/invocations/pbr_maps.py | .py | import pathlib
from typing import Literal
from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output
from invokeai.app.invocations.fields import ImageField, InputField, OutputField, WithBoard, WithMetadata
from invokeai.app.services.shared.invocation_context... | 62 | 3,100 |
InvokeAI | invokeai/app/invocations/flux_controlnet.py | .py | from pydantic import BaseModel, Field, field_validator, model_validator
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
invocation,
invocation_output,
)
from invokeai.app.invocations.fields import FieldDescriptions, ImageField, InputField, OutputField
from in... | 101 | 4,318 |
InvokeAI | invokeai/app/invocations/qwen_image_text_encoder.py | .py | from typing import Literal
import torch
from PIL import Image as PILImage
from invokeai.app.invocations.baseinvocation import BaseInvocation, Classification, invocation
from invokeai.app.invocations.fields import (
FieldDescriptions,
ImageField,
Input,
InputField,
UIComponent,
)
from invokeai.app.... | 326 | 14,403 |
InvokeAI | invokeai/app/invocations/z_image_seed_variance_enhancer.py | .py | import torch
from invokeai.app.invocations.baseinvocation import BaseInvocation, Classification, invocation
from invokeai.app.invocations.fields import (
FieldDescriptions,
Input,
InputField,
ZImageConditioningField,
)
from invokeai.app.invocations.primitives import ZImageConditioningOutput
from invoke... | 111 | 4,442 |
InvokeAI | invokeai/app/invocations/ideogram4_text_encoder.py | .py | from contextlib import ExitStack
import torch
from invokeai.app.invocations.baseinvocation import BaseInvocation, Classification, invocation
from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, UIComponent
from invokeai.app.invocations.model import Qwen3EncoderField
from invokeai.app.invo... | 62 | 2,579 |
InvokeAI | invokeai/app/invocations/ernie_image_model_loader.py | .py | import json
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
Classification,
invocation,
invocation_output,
)
from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField
from invokeai.app.invocations.model import (
Mis... | 112 | 5,291 |
InvokeAI | invokeai/app/invocations/math.py | .py | # Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
from typing import Literal
import numpy as np
from pydantic import ValidationInfo, field_validator
from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
from invokeai.app.invocations.fields import FieldDescriptions, InputFie... | 293 | 10,441 |
InvokeAI | invokeai/app/invocations/wan_latents_to_video.py | .py | """Wan 2.2 latents-to-video invocation.
Decodes multi-frame Wan latents with the Wan VAE and encodes the result to an
MP4 file via :mod:`imageio` (backed by the bundled FFmpeg binary from
``imageio-ffmpeg``). The video is then persisted through ``context.videos.save``,
which moves the temp file into ``outputs/videos/`... | 234 | 10,384 |
InvokeAI | invokeai/app/invocations/qwen_image_lora_loader.py | .py | from typing import Optional
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
Classification,
invocation,
invocation_output,
)
from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField
from invokeai.app.invocations.model ... | 120 | 4,090 |
InvokeAI | invokeai/app/invocations/sd3_denoise.py | .py | from typing import Callable, Optional, Tuple
import torch
import torchvision.transforms as tv_transforms
from diffusers.models.transformers.transformer_sd3 import SD3Transformer2DModel
from torchvision.transforms.functional import resize as tv_resize
from tqdm import tqdm
from invokeai.app.invocations.baseinvocation ... | 355 | 15,431 |
InvokeAI | invokeai/app/invocations/flux2_klein_model_loader.py | .py | """Flux2 Klein Model Loader Invocation.
Loads a Flux2 Klein model with its Qwen3 text encoder and VAE.
Unlike standard FLUX which uses CLIP+T5, Klein uses only Qwen3.
"""
from typing import Literal, Optional
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
Class... | 280 | 14,611 |
InvokeAI | invokeai/app/invocations/krea2_model_loader.py | .py | from typing import Optional
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
Classification,
invocation,
invocation_output,
)
from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField
from invokeai.app.invocations.model ... | 129 | 5,768 |
InvokeAI | invokeai/app/invocations/z_image_lora_loader.py | .py | from typing import Optional
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
invocation,
invocation_output,
)
from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField
from invokeai.app.invocations.model import LoRAField, Mo... | 182 | 7,277 |
InvokeAI | invokeai/app/invocations/create_gradient_mask.py | .py | from typing import Literal, Optional
import cv2
import numpy as np
import torch
import torchvision.transforms as T
from PIL import Image
from torchvision.transforms.functional import resize as tv_resize
from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_ou... | 230 | 10,750 |
InvokeAI | invokeai/app/invocations/qwen_image_latents_to_image.py | .py | from contextlib import nullcontext
import torch
from einops import rearrange
from PIL import Image
from invokeai.app.invocations.baseinvocation import BaseInvocation, Classification, invocation
from invokeai.app.invocations.fields import (
FieldDescriptions,
Input,
InputField,
LatentsField,
WithBo... | 107 | 5,254 |
InvokeAI | invokeai/app/invocations/image_panels.py | .py | from pydantic import ValidationInfo, field_validator
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
Classification,
invocation,
invocation_output,
)
from invokeai.app.invocations.fields import InputField, OutputField
from invokeai.app.services.shared.inv... | 60 | 2,724 |
InvokeAI | invokeai/app/invocations/flux_lora_loader.py | .py | from typing import Optional
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
invocation,
invocation_output,
)
from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField
from invokeai.app.invocations.model import CLIPField, Lo... | 187 | 6,664 |
InvokeAI | invokeai/app/invocations/anima_lora_loader.py | .py | from typing import Optional
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
Classification,
invocation,
invocation_output,
)
from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField
from invokeai.app.invocations.model ... | 167 | 6,001 |
InvokeAI | invokeai/app/invocations/pid_upscale.py | .py | """PiD super-resolution upscale invocation.
Stand-alone 4x super-resolution path that does **not** require a Generator
latent. Pipeline::
image
-> FLUX VAE encode (denormalised back to raw)
-> Gemma-2 caption encode
-> PiD decoder (4x SR)
-> image (4x linear)
This is the PiD analogue of E... | 212 | 10,121 |
InvokeAI | invokeai/app/invocations/anima_model_loader.py | .py | from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
Classification,
invocation,
invocation_output,
)
from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField
from invokeai.app.invocations.model import (
ModelIdentifierF... | 87 | 3,328 |
InvokeAI | invokeai/app/invocations/flux2_vae_encode.py | .py | """Flux2 Klein VAE Encode Invocation.
Encodes images to latents using the FLUX.2 32-channel VAE (AutoencoderKLFlux2).
"""
import einops
import torch
from invokeai.app.invocations.baseinvocation import BaseInvocation, Classification, invocation
from invokeai.app.invocations.fields import (
FieldDescriptions,
... | 89 | 3,437 |
InvokeAI | invokeai/app/invocations/wan_ref_image_encoder.py | .py | """Reference-image (VAE-latent) encoder for Wan 2.2 image-to-video conditioning.
Wan 2.2 I2V conditions on a reference image by VAE-encoding it. The condition
shape depends on the wired VAE (which selects the model family):
- **A14B** (16-channel Wan 2.1 VAE): a 20-channel condition tensor (4-ch
first-frame mask + ... | 210 | 10,161 |
InvokeAI | invokeai/app/invocations/t2i_adapter.py | .py | from typing import Union
from pydantic import BaseModel, Field, field_validator, model_validator
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
invocation,
invocation_output,
)
from invokeai.app.invocations.fields import FieldDescriptions, ImageField, Input... | 103 | 4,055 |
InvokeAI | invokeai/app/invocations/flux_text_encoder.py | .py | from contextlib import ExitStack
from typing import Iterator, Literal, Optional
import torch
from transformers import CLIPTextModel, CLIPTokenizer, T5EncoderModel, T5Tokenizer
from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
from invokeai.app.invocations.fields import (
FieldDescript... | 286 | 12,485 |
InvokeAI | invokeai/app/invocations/sd3_image_to_latents.py | .py | import einops
import torch
from diffusers.models.autoencoders.autoencoder_kl import AutoencoderKL
from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
from invokeai.app.invocations.fields import (
FieldDescriptions,
ImageField,
Input,
InputField,
WithBoard,
WithMetadat... | 73 | 2,923 |
InvokeAI | invokeai/app/invocations/flux_redux.py | .py | import math
from typing import Literal, Optional
import torch
from PIL import Image
from transformers import SiglipImageProcessor, SiglipVisionModel
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
Classification,
invocation,
invocation_output,
)
from inv... | 172 | 7,243 |
InvokeAI | invokeai/app/invocations/sd3_model_loader.py | .py | from typing import Optional
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
invocation,
invocation_output,
)
from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField
from invokeai.app.invocations.model import CLIPField, Mo... | 110 | 4,646 |
InvokeAI | invokeai/app/invocations/lineart.py | .py | from builtins import bool
from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
from invokeai.app.invocations.fields import ImageField, InputField, WithBoard, WithMetadata
from invokeai.app.invocations.primitives import ImageOutput
from invokeai.app.services.shared.invocation_context import In... | 35 | 1,477 |
InvokeAI | invokeai/app/invocations/grounding_dino.py | .py | from pathlib import Path
from typing import Literal
import torch
from PIL import Image
from transformers import pipeline
from transformers.pipelines import ZeroShotObjectDetectionPipeline
from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
from invokeai.app.invocations.fields import Boundin... | 101 | 4,567 |
InvokeAI | invokeai/app/invocations/video_frame_extract.py | .py | """Extract a single frame from a video as an image.
Enables I2V "shot extension": take the last frame of one clip and feed it back
in as the reference image for the next clip, then concatenate the MP4s
externally to get a video longer than the model's single-shot frame budget.
Also useful as a general-purpose video-to... | 76 | 3,309 |
InvokeAI | invokeai/app/invocations/param_easing.py | .py | import numpy as np
from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
from invokeai.app.invocations.fields import InputField
from invokeai.app.invocations.primitives import FloatCollectionOutput
from invokeai.app.services.shared.invocation_context import InvocationContext
@invocation(
... | 29 | 1,031 |
InvokeAI | invokeai/app/invocations/wan_denoise.py | .py | """Wan 2.2 denoise invocation.
Supports both single-transformer (TI2V-5B) and dual-expert MoE (A14B) denoising.
For A14B the high-noise expert handles timesteps ``t >= boundary_timestep`` and
the low-noise expert handles ``t < boundary_timestep``, where
``boundary_timestep = boundary_ratio * num_train_timesteps`` (typ... | 775 | 37,552 |
InvokeAI | invokeai/app/invocations/mlsd.py | .py | from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
from invokeai.app.invocations.fields import ImageField, InputField, WithBoard, WithMetadata
from invokeai.app.invocations.primitives import ImageOutput
from invokeai.app.services.shared.invocation_context import InvocationContext
from invoke... | 40 | 1,751 |
InvokeAI | invokeai/app/invocations/flux2_klein_lora_loader.py | .py | """FLUX.2 Klein LoRA Loader Invocation.
Applies LoRA models to a FLUX.2 Klein transformer and/or Qwen3 text encoder.
Unlike standard FLUX which uses CLIP+T5, Klein uses only Qwen3 for text encoding.
"""
from typing import Optional
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvo... | 213 | 8,885 |
InvokeAI | invokeai/app/invocations/cv.py | .py | # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
import cv2 as cv
import numpy
from PIL import Image, ImageOps
from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
from invokeai.app.invocations.fields import ImageField, InputField, WithBoard, WithMetadata
from invokeai.ap... | 40 | 1,623 |
InvokeAI | invokeai/app/invocations/tiles.py | .py | from typing import Literal
import numpy as np
from PIL import Image
from pydantic import BaseModel
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
invocation,
invocation_output,
)
from invokeai.app.invocations.fields import ImageField, Input, InputField, Out... | 285 | 11,363 |
InvokeAI | invokeai/app/invocations/cogview4_model_loader.py | .py | from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
Classification,
invocation,
invocation_output,
)
from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField
from invokeai.app.invocations.model import (
GlmEncoderField,... | 57 | 2,254 |
InvokeAI | invokeai/app/invocations/flux2_dev_lora_loader.py | .py | """FLUX.2 [dev] LoRA loader invocations.
Mirror of the Klein LoRA loader, but routes encoder LoRAs to the Mistral text
encoder rather than the Qwen3 encoder.
"""
from typing import Optional
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
Classification,
inv... | 185 | 7,775 |
InvokeAI | invokeai/app/invocations/ernie_image_vae_decode.py | .py | """ERNIE-Image VAE decode invocation.
The denoiser emits patched latents [B, 128, H/2, W/2]. Before the VAE can decode them
we have to (a) apply the VAE's BatchNorm denormalization, and (b) reverse the 2x2
patchify back to [B, 32, H, W]. This is the same sequence the upstream pipeline
performs at the end of `__call__`... | 70 | 2,735 |
InvokeAI | invokeai/app/invocations/krea2_denoise.py | .py | import json
import math
from contextlib import ExitStack
from pathlib import Path
from typing import Callable, Iterator, Optional
import torch
import torchvision.transforms as tv_transforms
from pydantic import field_validator
from torchvision.transforms.functional import resize as tv_resize
from tqdm import tqdm
fro... | 592 | 30,392 |
InvokeAI | invokeai/app/invocations/noise.py | .py | import torch
from pydantic import field_validator
from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output
from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR
from invokeai.app.invocations.fields import FieldDescriptions, InputField, Latents... | 85 | 2,945 |
InvokeAI | invokeai/app/invocations/workflow_return.py | .py | from typing import Any
from pydantic import BaseModel, Field
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
Classification,
invocation,
invocation_output,
)
from invokeai.app.invocations.fields import Input, InputField, OutputField, UIType
from invokeai... | 140 | 4,693 |
InvokeAI | invokeai/app/invocations/ideogram4_denoise.py | .py | from typing import Literal, Optional
import torch
from invokeai.app.invocations.baseinvocation import BaseInvocation, Classification, invocation
from invokeai.app.invocations.fields import (
FieldDescriptions,
Ideogram4ConditioningField,
Input,
InputField,
)
from invokeai.app.invocations.model import ... | 180 | 8,509 |
InvokeAI | invokeai/app/invocations/flux_denoise.py | .py | from contextlib import ExitStack
from typing import Callable, Iterator, Optional, Union
import einops
import numpy as np
import numpy.typing as npt
import torch
import torchvision.transforms as tv_transforms
from PIL import Image
from torchvision.transforms.functional import resize as tv_resize
from transformers impor... | 1,022 | 48,513 |
InvokeAI | invokeai/app/invocations/cogview4_text_encoder.py | .py | import torch
from transformers import GlmModel, PreTrainedTokenizerFast
from invokeai.app.invocations.baseinvocation import BaseInvocation, Classification, invocation
from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, UIComponent
from invokeai.app.invocations.model import GlmEncoderField... | 104 | 5,028 |
InvokeAI | invokeai/app/invocations/blend_latents.py | .py | from typing import Optional, Union
import numpy as np
import torch
import torchvision.transforms as T
from PIL import Image
from torchvision.transforms.functional import resize as tv_resize
from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
from invokeai.app.invocations.fields import Field... | 121 | 4,860 |
InvokeAI | invokeai/app/invocations/flux_kontext.py | .py | from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
invocation,
invocation_output,
)
from invokeai.app.invocations.fields import (
FieldDescriptions,
FluxKontextConditioningField,
InputField,
OutputField,
)
from invokeai.app.invocations.primitives ... | 41 | 1,344 |
InvokeAI | invokeai/app/invocations/ernie_image_text_encoder.py | .py | from contextlib import ExitStack
import torch
from transformers import PreTrainedModel, PreTrainedTokenizerBase
from invokeai.app.invocations.baseinvocation import BaseInvocation, Classification, invocation
from invokeai.app.invocations.fields import (
ErnieImageConditioningField,
Input,
InputField,
U... | 84 | 3,732 |
InvokeAI | invokeai/app/invocations/primitives.py | .py | # Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
from typing import Optional
import torch
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
invocation,
invocation_output,
)
from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR
... | 737 | 24,701 |
InvokeAI | invokeai/app/invocations/cogview4_image_to_latents.py | .py | import einops
import torch
from diffusers.models.autoencoders.autoencoder_kl import AutoencoderKL
from invokeai.app.invocations.baseinvocation import BaseInvocation, Classification, invocation
from invokeai.app.invocations.fields import (
FieldDescriptions,
ImageField,
Input,
InputField,
WithBoard,... | 77 | 3,179 |
InvokeAI | invokeai/app/invocations/qwen_image_denoise.py | .py | import math
from contextlib import ExitStack
from typing import Callable, ClassVar, Iterator, Optional
import torch
import torchvision.transforms as tv_transforms
from diffusers.models.transformers.transformer_qwenimage import QwenImageTransformer2DModel
from torchvision.transforms.functional import resize as tv_resiz... | 559 | 26,563 |
InvokeAI | invokeai/app/invocations/call_saved_workflow.py | .py | from typing import Any
from invokeai.app.invocations.baseinvocation import BaseInvocation, Classification, invocation
from invokeai.app.invocations.fields import InputField, UIType
from invokeai.app.invocations.workflow_return import WorkflowReturnOutput
from invokeai.app.services.shared.invocation_context import Invo... | 76 | 3,290 |
InvokeAI | invokeai/app/invocations/content_shuffle.py | .py | from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
from invokeai.app.invocations.fields import ImageField, InputField, WithBoard, WithMetadata
from invokeai.app.invocations.primitives import ImageOutput
from invokeai.app.services.shared.invocation_context import InvocationContext
from invoke... | 26 | 1,189 |
InvokeAI | invokeai/app/invocations/baseinvocation.py | .py | # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654) and the InvokeAI team
from __future__ import annotations
import inspect
import re
import sys
import types
import typing
import warnings
from abc import ABC, abstractmethod
from enum import Enum
from functools import lru_cache
from inspect import sign... | 854 | 37,620 |
InvokeAI | invokeai/app/invocations/prompt.py | .py | from os.path import exists
from typing import Optional, Union
import numpy as np
from dynamicprompts.generators import CombinatorialPromptGenerator, RandomPromptGenerator
from pydantic import field_validator
from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
from invokeai.app.invocations.f... | 111 | 4,200 |
InvokeAI | invokeai/app/invocations/krea2_seed_variance.py | .py | import torch
from invokeai.app.invocations.baseinvocation import BaseInvocation, Classification, invocation
from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, Krea2ConditioningField
from invokeai.app.invocations.primitives import Krea2ConditioningOutput
from invokeai.app.services.shared.... | 87 | 4,213 |
InvokeAI | invokeai/app/invocations/qwen_image_model_loader.py | .py | from typing import Optional
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
Classification,
invocation,
invocation_output,
)
from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField
from invokeai.app.invocations.model ... | 148 | 6,621 |
InvokeAI | invokeai/app/invocations/sd3_pid_decode.py | .py | """SD3 PiD decode invocation.
Replaces SD3's AutoencoderKL decode with the PiD pixel-diffusion super-res
decoder (``PiD_res2k_sr4x_official_sd3_distill_4step``). Produces a 4x
super-resolved image from an SD3 latent in a 4-step distill pass.
"""
from contextlib import ExitStack
import torch
from einops import rearra... | 165 | 7,497 |
InvokeAI | invokeai/app/invocations/facetools.py | .py | import math
import re
from pathlib import Path
from typing import Optional, TypedDict
import cv2
import numpy as np
from mediapipe.python.solutions.face_mesh import FaceMesh # type: ignore[import]
from PIL import Image, ImageDraw, ImageFilter, ImageFont, ImageOps
from PIL.Image import Image as ImageType
from pydantic... | 690 | 26,486 |
InvokeAI | invokeai/app/invocations/logic.py | .py | from typing import Any, Optional
from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output
from invokeai.app.invocations.fields import InputField, OutputField, UIType
from invokeai.app.services.shared.invocation_context import InvocationContext
@invocatio... | 35 | 1,404 |
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