ComfyUI Extension: Skoogeer-Noise

Authored by ttulttul

Created 15 days ago

Updated 5 days ago

5 stars

Noise, conditioning, and perturbation utility nodes for ComfyUI (procedural noise, mesh drag, latent channel stats preview).

Custom Nodes (0)

README

Skoogeer-Noise

A ComfyUI custom node pack containing:

Spatial perturbations (mesh drag warps) for LATENT and IMAGE
Seeded Gaussian noise utilities for LATENT, IMAGE, and CONDITIONING
Procedural / structured noise generators (Perlin, Simplex, Worley, reaction-diffusion, fBm, swirl)
Low/high frequency split helpers for LATENT and CONDITIONING
Latent diagnostics preview nodes

This pack was extracted from ComfyUI-FlowMatching-Upscaler and also includes the latent/image/conditioning noise + filtering nodes that were previously shipped in ComfyUI-QwenRectifiedFlowInverter.

Installation

Clone into ComfyUI/custom_nodes/Skoogeer-Noise
Restart ComfyUI

Dependencies: torch and numpy (ComfyUI typically already includes these).

Data types / shapes

`LATENT`

ComfyUI latents are dictionaries containing a "samples" tensor.

Most SD-style latents: (B, C, H, W)
Some video / flow-matching latents: (B, C, T, H, W)

All latent nodes in this pack operate on latent["samples"] and preserve other latent dict keys. Latent Mesh Drag also warps latent["noise_mask"] when present.

`IMAGE`

ComfyUI images are torch tensors in BHWC format: (B, H, W, C) (usually C=3). Some nodes also accept 5D “video” tensors: (B, T, H, W, C).

`CONDITIONING`

ComfyUI conditioning is a list of [embedding, metadata] entries. The conditioning nodes in this pack operate on:

the embedding tensor (commonly shaped like (tokens, features) or (B, tokens, features)), and
metadata["pooled_output"] when present.

Parameter conventions

Seed (seed): 64-bit integer used to make perturbations repeatable.
Strength (strength): unless stated otherwise, noise nodes scale their generated pattern by the standard deviation of the input (per-sample).
Channel mode (channel_mode):
- shared: reuse one generated field for all channels
- per_channel: reseed and generate per channel
Temporal mode (temporal_mode) (5D tensors only):
- locked: reuse one pattern across frames (temporally stable)
- animated: reseed per frame (more variation, can flicker)

Node index

| Node | Category | Output(s) | |------|----------|-----------| | Latent Mesh Drag | latent/perturb | LATENT | | Image Mesh Drag | image/perturb | IMAGE | | Latent Noise | latent/perturb | LATENT | | Image Noise | image/perturb | IMAGE | | Latent Channel Stats Preview | latent/debug | IMAGE | | Latent Gaussian Blur | Latent/Filter | LATENT | | Latent Frequency Split | Latent/Filter | LATENT (low), LATENT (high) | | Latent Frequency Merge | Latent/Filter | LATENT | | Add Latent Noise (Seeded) | Latent/Noise | LATENT | | Add Image Noise (Seeded) | Image/Noise | IMAGE | | Latent Perlin Fractal Noise | Latent/Noise | LATENT | | Image Perlin Fractal Noise | Image/Noise | IMAGE | | Latent Simplex Noise | Latent/Noise | LATENT | | Image Simplex Noise | Image/Noise | IMAGE | | Latent Worley Noise | Latent/Noise | LATENT | | Image Worley Noise | Image/Noise | IMAGE | | Latent Reaction-Diffusion | Latent/Noise | LATENT | | Image Reaction-Diffusion | Image/Noise | IMAGE | | Latent Fractal Brownian Motion | Latent/Noise | LATENT | | Image Fractal Brownian Motion | Image/Noise | IMAGE | | Latent Swirl Noise | Latent/Noise | LATENT | | Image Swirl Noise | Image/Noise | IMAGE | | Forward Diffusion (Add Scheduled Noise) | Latent/Noise | LATENT | | Conditioning (Add Noise) | conditioning/noise | CONDITIONING | | Conditioning (Gaussian Blur) | conditioning/filter | CONDITIONING | | Conditioning (Frequency Split) | conditioning/filter | CONDITIONING (low), CONDITIONING (high) | | Conditioning (Frequency Merge) | conditioning/filter | CONDITIONING | | Conditioning (Scale) | conditioning/filter | CONDITIONING |

Nodes

Latent Mesh Drag

Applies a cloth-like spatial warp to a LATENT by randomly dragging control vertices on a coarse mesh and interpolating a smooth displacement field.

Menu category: latent/perturb
Returns: LATENT

Inputs

| Field | Type | Default | Range/Options | Notes | |------|------|---------|--------------|------| | latent | LATENT | – | – | Latent to warp spatially using a random mesh drag. | | seed | INT | 0 | 0..2^64-1 | Seed controlling which mesh points are dragged and by how much. | | points | INT | 12 | 0..2048 | Number of mesh vertices to randomly drag. | | drag_min | FLOAT | 0.0 | 0.0..128.0 | Minimum drag distance (latent pixels). | | drag_max | FLOAT | 4.0 | 0.0..128.0 | Maximum drag distance (latent pixels). | | direction | FLOAT | -1.0 | -1.0..360.0 | Drag direction in degrees (0=up, 90=right, 180=down, 270=left). -1 allows random directions. | | stroke_width | FLOAT | -1.0 | -1.0..4096.0 | When >0, limits the warp to narrow brush-stroke channels aligned with the direction (one per dragged mesh point; when direction>=0, stroke centers are jittered so they aren't grid-aligned). Units are latent pixels. -1 disables. | | displacement_interpolation | enum | bicubic | bilinear/bicubic/bspline/nearest | How to interpolate sparse mesh drags into a full displacement field (bspline is smoother). | | spline_passes | INT | 2 | 0..16 | Only used when displacement_interpolation = bspline. | | sampling_interpolation | enum | bilinear | bilinear/bicubic/nearest | How to sample the source tensor when applying the warp. |

Notes

Drag distances are specified in latent pixels (multiply by ~8 for image-space pixels with SD-style VAEs).
If the input latent contains a noise_mask tensor, it is warped using the same displacement.

Image Mesh Drag

Applies the same mesh-drag deformation in image space (pixel units) to ComfyUI IMAGE tensors.

Menu category: image/perturb
Returns: IMAGE

Inputs

| Field | Type | Default | Range/Options | Notes | |------|------|---------|--------------|------| | image | IMAGE | – | – | Image to warp spatially using a random mesh drag. | | seed | INT | 0 | 0..2^64-1 | Seed controlling which mesh points are dragged and by how much. | | points | INT | 12 | 0..4096 | Number of mesh vertices to randomly drag. | | drag_min | FLOAT | 0.0 | 0.0..4096.0 | Minimum drag distance (image pixels). | | drag_max | FLOAT | 32.0 | 0.0..4096.0 | Maximum drag distance (image pixels). | | direction | FLOAT | -1.0 | -1.0..360.0 | Drag direction in degrees (0=up, 90=right, 180=down, 270=left). -1 allows random directions. | | stroke_width | FLOAT | -1.0 | -1.0..16384.0 | When >0, limits the warp to narrow brush-stroke channels aligned with the direction (one per dragged mesh point; when direction>=0, stroke centers are jittered so they aren't grid-aligned). Units are image pixels. -1 disables. | | displacement_interpolation | enum | bicubic | bilinear/bicubic/bspline/nearest | How to interpolate sparse mesh drags into a full displacement field (bspline is smoother). | | spline_passes | INT | 2 | 0..16 | Only used when displacement_interpolation = bspline. | | sampling_interpolation | enum | bilinear | bilinear/bicubic/nearest | How to sample the source image when applying the warp. |

Latent Noise

Adds seeded Gaussian noise to a ComfyUI LATENT dictionary.

Menu category: latent/perturb
Returns: LATENT

Inputs

| Field | Type | Default | Range/Options | Notes | |------|------|---------|--------------|------| | latent | LATENT | – | – | Latent to receive additional Gaussian noise. | | seed | INT | 0 | 0..2^64-1 | Seed for generating repeatable noise. | | strength | FLOAT | 1.0 | 0.0..10.0 | Noise strength relative to the latent's standard deviation. |

Image Noise

Adds seeded Gaussian noise to a ComfyUI IMAGE tensor.

Menu category: image/perturb
Returns: IMAGE

Inputs

| Field | Type | Default | Range/Options | Notes | |------|------|---------|--------------|------| | image | IMAGE | – | – | Image to receive additional Gaussian noise. | | seed | INT | 0 | 0..2^64-1 | Seed for generating repeatable noise. | | strength | FLOAT | 1.0 | 0.0..10.0 | Noise strength relative to the image's standard deviation. |

Latent Channel Stats Preview

Renders a bar-chart preview of per-channel mean and standard deviation for LATENT["samples"].

Menu category: latent/debug
Returns: IMAGE

Inputs

| Field | Type | Default | Range/Options | Notes | |------|------|---------|--------------|------| | latent | LATENT | – | – | Latent to analyze. | | channel_limit | INT | 16 | 1..64 | Number of channels to display. | | height | INT | 256 | 72..1024 | Output image height (layout adjusts automatically). |

Latent Gaussian Blur

Gaussian blur for latents (supports both 4D and 5D latents).

Menu category: Latent/Filter
Returns: LATENT

Inputs

| Field | Type | Default | Range/Options | Notes | |------|------|---------|--------------|------| | latent | LATENT | – | – | Latent tensor to blur. | | sigma | FLOAT | 1.0 | 0.0..10.0 | Standard deviation for the Gaussian kernel. 0 is a no-op. | | blur_mode | enum | Spatial Only | Spatial Only/Spatial and Channel | When Spatial and Channel, also blurs across the channel dimension. |

Latent Frequency Split

Splits a latent into low-pass and high-pass bands by subtracting a Gaussian-smoothed version.

Menu category: Latent/Filter
Returns: LATENT (low), LATENT (high)

Inputs

| Field | Type | Default | Range/Options | Notes | |------|------|---------|--------------|------| | latent | LATENT | – | – | Latent to decompose into low/high frequency bands. | | sigma | FLOAT | 1.5 | 0.0..20.0 | Radius of Gaussian low-pass. Higher moves more detail into the high band. |

Outputs

low_pass: blurred latent
high_pass: latent - low_pass (zeros when sigma <= 0)

Latent Frequency Merge

Merges the low-pass and high-pass bands back into a single latent.

Menu category: Latent/Filter
Returns: LATENT

Inputs

| Field | Type | Default | Range/Options | Notes | |------|------|---------|--------------|------| | low_pass | LATENT | – | – | Low-frequency latent band produced by Latent Frequency Split. | | high_pass | LATENT | – | – | High-frequency latent band to merge back in. | | low_gain | FLOAT | 1.0 | -5.0..5.0 | Multiplier for the low-pass band before merging. | | high_gain | FLOAT | 1.0 | -5.0..5.0 | Multiplier for the high-pass band before merging. |

Output

merged: low_pass * low_gain + high_pass * high_gain

Add Latent Noise (Seeded)

Adds seeded Gaussian noise to LATENT["samples"] (strength is relative to the latent's standard deviation).

Menu category: Latent/Noise
Returns: LATENT

Inputs

| Field | Type | Default | Range/Options | Notes | |------|------|---------|--------------|------| | latent | LATENT | – | – | Latent to receive additional Gaussian noise. | | seed | INT | 0 | 0..2^64-1 | Seed for generating repeatable noise. | | strength | FLOAT | 1.0 | 0.0..10.0 | 1.0 adds noise with roughly the same std as the latent. |

Add Image Noise (Seeded)

Adds seeded Gaussian noise to an IMAGE tensor (strength is relative to the image's standard deviation).

Menu category: Image/Noise
Returns: IMAGE

Inputs

| Field | Type | Default | Range/Options | Notes | |------|------|---------|--------------|------| | image | IMAGE | – | – | Image to receive additional Gaussian noise. | | seed | INT | 0 | 0..2^64-1 | Seed for generating repeatable noise. | | strength | FLOAT | 1.0 | 0.0..10.0 | 1.0 adds noise with roughly the same std as the image. |

Latent Perlin Fractal Noise

Adds smooth fractal Perlin noise to a latent for structured variation.

Menu category: Latent/Noise
Returns: LATENT

Inputs

| Field | Type | Default | Range/Options | Notes | |------|------|---------|--------------|------| | latent | LATENT | – | – | Latent that will be perturbed with fractal Perlin noise. | | seed | INT | 0 | 0..2^64-1 | Seed controlling the procedural noise pattern. | | frequency | FLOAT | 2.0 | 0.01..64.0 | Base lattice frequency (higher = finer detail). | | octaves | INT | 4 | 1..12 | Number of noise layers to accumulate. | | persistence | FLOAT | 0.5 | 0.0..1.0 | Amplitude multiplier between octaves. | | lacunarity | FLOAT | 2.0 | 1.0..6.0 | Frequency multiplier between octaves. | | strength | FLOAT | 0.5 | 0.0..5.0 | Scales normalized noise relative to the latent's standard deviation. | | channel_mode | enum | shared | shared/per_channel | Shared noise across channels or unique noise per channel. |

Notes

For 5D latents (B,C,T,H,W), this node generates 3D Perlin noise across (T,H,W) (no temporal_mode parameter).

Image Perlin Fractal Noise

Adds smooth fractal Perlin noise to an image for structured variation.

Menu category: Image/Noise
Returns: IMAGE

Inputs

| Field | Type | Default | Range/Options | Notes | |------|------|---------|--------------|------| | image | IMAGE | – | – | Image that will be perturbed with fractal Perlin noise. | | seed | INT | 0 | 0..2^64-1 | Seed controlling the procedural noise pattern. | | frequency | FLOAT | 2.0 | 0.01..64.0 | Base lattice frequency (higher = finer detail). | | octaves | INT | 4 | 1..12 | Number of noise layers to accumulate. | | persistence | FLOAT | 0.5 | 0.0..1.0 | Amplitude multiplier between octaves. | | lacunarity | FLOAT | 2.0 | 1.0..6.0 | Frequency multiplier between octaves. | | strength | FLOAT | 0.5 | 0.0..5.0 | Scales normalized noise relative to the image's standard deviation. | | channel_mode | enum | shared | shared/per_channel | Reuse a single noise field for all channels or reseed per channel. | | temporal_mode | enum | locked | locked/animated | 5D images only: reuse or reseed the pattern per frame. |

Latent Simplex Noise

Adds layered fractal simplex noise to a latent for organic perturbations.

Menu category: Latent/Noise
Returns: LATENT

Inputs

| Field | Type | Default | Range/Options | Notes | |------|------|---------|--------------|------| | latent | LATENT | – | – | Latent to perturb with simplex noise. | | seed | INT | 0 | 0..2^64-1 | Seed controlling the simplex lattice offsets. | | frequency | FLOAT | 2.0 | 0.01..64.0 | Base lattice frequency for the simplex grid. | | octaves | INT | 4 | 1..12 | Number of simplex layers to accumulate. | | persistence | FLOAT | 0.5 | 0.0..1.0 | Amplitude multiplier applied between octaves. | | lacunarity | FLOAT | 2.0 | 1.0..6.0 | Frequency multiplier applied between octaves. | | strength | FLOAT | 0.5 | 0.0..5.0 | Scales normalized simplex noise relative to the latent's standard deviation. | | channel_mode | enum | shared | shared/per_channel | Reuse a single noise field for all channels or reseed per channel. | | temporal_mode | enum | locked | locked/animated | 5D latents only: reuse or reseed the pattern per frame. |

Image Simplex Noise

Adds layered fractal simplex noise to an image.

Menu category: Image/Noise
Returns: IMAGE

Inputs

| Field | Type | Default | Range/Options | Notes | |------|------|---------|--------------|------| | image | IMAGE | – | – | Image to perturb with simplex noise. | | seed | INT | 0 | 0..2^64-1 | Seed controlling the simplex lattice offsets. | | frequency | FLOAT | 2.0 | 0.01..64.0 | Base lattice frequency for the simplex grid. | | octaves | INT | 4 | 1..12 | Number of simplex layers to accumulate. | | persistence | FLOAT | 0.5 | 0.0..1.0 | Amplitude multiplier applied between octaves. | | lacunarity | FLOAT | 2.0 | 1.0..6.0 | Frequency multiplier applied between octaves. | | strength | FLOAT | 0.5 | 0.0..5.0 | Scales normalized simplex noise relative to the image's standard deviation. | | channel_mode | enum | shared | shared/per_channel | Reuse a single noise field for all channels or reseed per channel. | | temporal_mode | enum | locked | locked/animated | 5D images only: reuse or reseed the pattern per frame. |

Latent Worley Noise

Generates cellular (Worley) noise for cracked / biological / bubble-like textures.

Menu category: Latent/Noise
Returns: LATENT

Inputs

| Field | Type | Default | Range/Options | Notes | |------|------|---------|--------------|------| | latent | LATENT | – | – | Latent to perturb with Worley (cellular) noise. | | seed | INT | 0 | 0..2^64-1 | Seed for the feature point distribution. | | feature_points | INT | 16 | 1..4096 | Base number of feature points scattered across the plane. | | octaves | INT | 3 | 1..8 | Number of cellular layers to accumulate. | | persistence | FLOAT | 0.65 | 0.0..1.0 | Amplitude multiplier between Worley octaves. | | lacunarity | FLOAT | 2.0 | 1.0..6.0 | Multiplier for the feature point count between octaves. | | distance_metric | enum | euclidean | euclidean/manhattan/chebyshev | Distance metric used when measuring feature proximity. | | jitter | FLOAT | 0.35 | 0.0..1.0 | How far feature points can drift inside each cell. | | strength | FLOAT | 0.5 | 0.0..5.0 | Scales normalized Worley noise relative to the latent's standard deviation. | | channel_mode | enum | shared | shared/per_channel | Shared noise for all channels or reseeded per channel. | | temporal_mode | enum | locked | locked/animated | 5D latents only: reuse or reseed the pattern per frame. |

Image Worley Noise

Generates cellular (Worley) noise and injects it into an image.

Menu category: Image/Noise
Returns: IMAGE

Inputs

| Field | Type | Default | Range/Options | Notes | |------|------|---------|--------------|------| | image | IMAGE | – | – | Image to perturb with Worley (cellular) noise. | | seed | INT | 0 | 0..2^64-1 | Seed for the feature point distribution. | | feature_points | INT | 16 | 1..4096 | Base number of feature points scattered across the plane. | | octaves | INT | 3 | 1..8 | Number of cellular layers to accumulate. | | persistence | FLOAT | 0.65 | 0.0..1.0 | Amplitude multiplier between Worley octaves. | | lacunarity | FLOAT | 2.0 | 1.0..6.0 | Multiplier for the feature point count between octaves. | | distance_metric | enum | euclidean | euclidean/manhattan/chebyshev | Distance metric used when measuring feature proximity. | | jitter | FLOAT | 0.35 | 0.0..1.0 | How far feature points can drift inside each cell. | | strength | FLOAT | 0.5 | 0.0..5.0 | Scales normalized Worley noise relative to the image's standard deviation. | | channel_mode | enum | shared | shared/per_channel | Shared noise for all channels or reseeded per channel. | | temporal_mode | enum | locked | locked/animated | 5D images only: reuse or reseed the pattern per frame. |

Latent Reaction-Diffusion

Runs a Gray-Scott reaction-diffusion simulation and injects the resulting pattern into a latent.

Menu category: Latent/Noise
Returns: LATENT

Inputs

| Field | Type | Default | Range/Options | Notes | |------|------|---------|--------------|------| | latent | LATENT | – | – | Latent that will receive reaction-diffusion patterns. | | seed | INT | 0 | 0..2^64-1 | Seed for the initial chemical concentrations. | | iterations | INT | 200 | 1..2000 | Number of Gray-Scott simulation steps. | | feed_rate | FLOAT | 0.036 | 0.0..0.1 | Feed rate (F) controlling how quickly chemical U is replenished. | | kill_rate | FLOAT | 0.065 | 0.0..0.1 | Kill rate (K) regulating removal of chemical V. | | diffusion_u | FLOAT | 0.16 | 0.0..1.0 | Diffusion rate for chemical U. | | diffusion_v | FLOAT | 0.08 | 0.0..1.0 | Diffusion rate for chemical V. | | time_step | FLOAT | 1.0 | 0.01..5.0 | Simulation time step used during integration. | | strength | FLOAT | 0.75 | 0.0..5.0 | Scales normalized pattern relative to the latent's standard deviation. | | channel_mode | enum | shared | shared/per_channel | Reuse one simulation for all channels or rerun per channel. | | temporal_mode | enum | locked | locked/animated | 5D latents only: reuse or rerun simulation per frame. |

Image Reaction-Diffusion

Runs a Gray-Scott reaction-diffusion simulation and injects the resulting pattern into an image.

Menu category: Image/Noise
Returns: IMAGE

Inputs

| Field | Type | Default | Range/Options | Notes | |------|------|---------|--------------|------| | image | IMAGE | – | – | Image that will receive reaction-diffusion patterns. | | seed | INT | 0 | 0..2^64-1 | Seed for the initial chemical concentrations. | | iterations | INT | 200 | 1..2000 | Number of Gray-Scott simulation steps. | | feed_rate | FLOAT | 0.036 | 0.0..0.1 | Feed rate (F) controlling how quickly chemical U is replenished. | | kill_rate | FLOAT | 0.065 | 0.0..0.1 | Kill rate (K) regulating removal of chemical V. | | diffusion_u | FLOAT | 0.16 | 0.0..1.0 | Diffusion rate for chemical U. | | diffusion_v | FLOAT | 0.08 | 0.0..1.0 | Diffusion rate for chemical V. | | time_step | FLOAT | 1.0 | 0.01..5.0 | Simulation time step used during integration. | | strength | FLOAT | 0.75 | 0.0..5.0 | Scales normalized pattern relative to the image's standard deviation. | | channel_mode | enum | shared | shared/per_channel | Reuse one simulation for all channels or rerun per channel. | | temporal_mode | enum | locked | locked/animated | 5D images only: reuse or rerun simulation per frame. |

Latent Fractal Brownian Motion

Builds fractal Brownian motion (fBm) from a selectable base noise and injects it into a latent.

Menu category: Latent/Noise
Returns: LATENT

Inputs

| Field | Type | Default | Range/Options | Notes | |------|------|---------|--------------|------| | latent | LATENT | – | – | Latent to enrich with fractal Brownian motion. | | seed | INT | 0 | 0..2^64-1 | Seed for the base noise generator. | | base_noise | enum | simplex | simplex/perlin/worley | Noise primitive accumulated by the fBm stack. | | frequency | FLOAT | 2.0 | 0.01..64.0 | Fundamental frequency for simplex/perlin (acts as a multiplier for Worley). | | feature_points | INT | 16 | 1..4096 | Base feature point count (used when base_noise = worley). | | octaves | INT | 5 | 1..12 | Number of fBm layers to accumulate. | | persistence | FLOAT | 0.5 | 0.0..1.0 | Amplitude multiplier between fBm layers. | | lacunarity | FLOAT | 2.0 | 1.0..6.0 | Frequency multiplier between fBm layers. | | distance_metric | enum | euclidean | euclidean/manhattan/chebyshev | Distance metric used when the base noise is Worley. | | jitter | FLOAT | 0.35 | 0.0..1.0 | Feature jitter amount for Worley base noise. | | strength | FLOAT | 0.5 | 0.0..5.0 | Scales normalized fBm relative to the latent's standard deviation. | | channel_mode | enum | shared | shared/per_channel | Shared fBm field per sample or reseeded per channel. | | temporal_mode | enum | locked | locked/animated | 5D latents only: reuse or reseed the fBm per frame. |

Image Fractal Brownian Motion

Builds fractal Brownian motion (fBm) from a selectable base noise and injects it into an image.

Menu category: Image/Noise
Returns: IMAGE

Inputs

| Field | Type | Default | Range/Options | Notes | |------|------|---------|--------------|------| | image | IMAGE | – | – | Image to enrich with fractal Brownian motion. | | seed | INT | 0 | 0..2^64-1 | Seed for the base noise generator. | | base_noise | enum | simplex | simplex/perlin/worley | Noise primitive accumulated by the fBm stack. | | frequency | FLOAT | 2.0 | 0.01..64.0 | Fundamental frequency for simplex/perlin (acts as a multiplier for Worley). | | feature_points | INT | 16 | 1..4096 | Base feature point count (used when base_noise = worley). | | octaves | INT | 5 | 1..12 | Number of fBm layers to accumulate. | | persistence | FLOAT | 0.5 | 0.0..1.0 | Amplitude multiplier between fBm layers. | | lacunarity | FLOAT | 2.0 | 1.0..6.0 | Frequency multiplier between fBm layers. | | distance_metric | enum | euclidean | euclidean/manhattan/chebyshev | Distance metric used when the base noise is Worley. | | jitter | FLOAT | 0.35 | 0.0..1.0 | Feature jitter amount for Worley base noise. | | strength | FLOAT | 0.5 | 0.0..5.0 | Scales normalized fBm relative to the image's standard deviation. | | channel_mode | enum | shared | shared/per_channel | Shared fBm field per sample or reseeded per channel. | | temporal_mode | enum | locked | locked/animated | 5D images only: reuse or reseed the fBm per frame. |

Latent Swirl Noise

Swirls latent pixels around randomized centers (vortex-like warp). This is a spatial deformation, not additive noise.

Menu category: Latent/Noise
Returns: LATENT

Inputs

| Field | Type | Default | Range/Options | Notes | |------|------|---------|--------------|------| | latent | LATENT | – | – | Latent to deform with vortex-style warps. | | seed | INT | 0 | 0..2^64-1 | Seed for vortex placement and direction randomness. | | vortices | INT | 1 | 1..16 | Number of independent vortex centres to spawn per latent. | | channel_mode | enum | global | global/per_channel | Shared swirl grid for all affected channels or unique grid per channel. | | channel_fraction | FLOAT | 1.0 | 0.0..1.0 | Fraction of channels to swirl (subset chosen per sample). | | strength | FLOAT | 0.75 | 0.0..6.28 | Peak swirl rotation in radians near the vortex center. | | radius | FLOAT | 0.5 | 0.05..2.0 | Normalized radius controlling how far the vortex influence extends. | | center_spread | FLOAT | 0.25 | 0.0..1.0 | How far the vortex origin drifts from the latent center. | | direction_bias | FLOAT | 0.0 | -1.0..1.0 | Bias toward counter-clockwise (1) or clockwise (-1) swirl. | | mix | FLOAT | 1.0 | 0.0..1.0 | Blend between original (0) and fully swirled (1). |

Image Swirl Noise

Swirls image pixels around randomized centers (vortex-like warp). This is a spatial deformation, not additive noise.

Menu category: Image/Noise
Returns: IMAGE

Inputs

| Field | Type | Default | Range/Options | Notes | |------|------|---------|--------------|------| | image | IMAGE | – | – | Image to deform with vortex-style warps. | | seed | INT | 0 | 0..2^64-1 | Seed for vortex placement and direction randomness. | | vortices | INT | 1 | 1..16 | Number of independent vortex centres to spawn per image. | | channel_mode | enum | global | global/per_channel | Shared swirl grid for all affected channels or unique grid per channel. | | channel_fraction | FLOAT | 1.0 | 0.0..1.0 | Fraction of channels to swirl (subset chosen per sample). | | strength | FLOAT | 0.75 | 0.0..6.28 | Peak swirl rotation in radians near the vortex center. | | radius | FLOAT | 0.5 | 0.05..2.0 | Normalized radius controlling how far the vortex influence extends. | | center_spread | FLOAT | 0.25 | 0.0..1.0 | How far the vortex origin drifts from the image center. | | direction_bias | FLOAT | 0.0 | -1.0..1.0 | Bias toward counter-clockwise (1) or clockwise (-1) swirl. | | mix | FLOAT | 1.0 | 0.0..1.0 | Blend between original (0) and fully swirled (1). |

Forward Diffusion (Add Scheduled Noise)

Adds “sampler-like” scheduled noise to a clean latent, using the model's sigma schedule when available.

Menu category: Latent/Noise
Returns: LATENT

Inputs

| Field | Type | Default | Range/Options | Notes | |------|------|---------|--------------|------| | model | MODEL | – | – | Diffusion model that defines the forward noise schedule. | | latent | LATENT | – | – | Clean latent to push forward along the schedule. | | seed | INT | 0 | 0..2^64-1 | Seed for the forward diffusion noise. | | steps | INT | 20 | 1..10000 | Number of steps in the sampler's schedule. | | noise_strength | FLOAT | 0.8 | 0.0..1.0 | How far along the schedule to noise to (0 = no-op). |

Notes

When ComfyUI is available, this node pulls sigmas from comfy.samplers.KSampler(model, steps=...). Otherwise it falls back to a simple linear sigma schedule.
noise_strength is mapped to a start step via start_step = steps - int(steps * noise_strength).

Conditioning (Add Noise)

Adds seeded Gaussian noise to conditioning embeddings and their pooled_output when present.

Menu category: conditioning/noise
Returns: CONDITIONING

Inputs

| Field | Type | Default | Range/Options | Notes | |------|------|---------|--------------|------| | conditioning | CONDITIONING | – | – | Conditioning list to perturb with Gaussian noise. | | seed | INT | 0 | 0..2^64-1 | Seed that drives the conditioning noise. | | strength | FLOAT | 0.1 | 0.0..5.0 | Noise strength relative to each tensor's standard deviation. |

Conditioning (Gaussian Blur)

Applies Gaussian smoothing along the token dimension of conditioning embeddings.

Menu category: conditioning/filter
Returns: CONDITIONING

Inputs

| Field | Type | Default | Range/Options | Notes | |------|------|---------|--------------|------| | conditioning | CONDITIONING | – | – | Conditioning list whose token dimension will be blurred. | | sigma | FLOAT | 0.75 | 0.0..10.0 | Standard deviation of the blur kernel along the token axis. |

Conditioning (Frequency Split)

Separates conditioning embeddings into low/high bands via Gaussian smoothing along the token axis.

Menu category: conditioning/filter
Returns: CONDITIONING (low), CONDITIONING (high)

Inputs

| Field | Type | Default | Range/Options | Notes | |------|------|---------|--------------|------| | conditioning | CONDITIONING | – | – | Conditioning list to separate into low/high bands. | | sigma | FLOAT | 0.75 | 0.0..10.0 | Cutoff for the Gaussian low-pass applied along the token axis. |

Conditioning (Frequency Merge)

Recombines low/high conditioning bands back into a single conditioning list.

Menu category: conditioning/filter
Returns: CONDITIONING

Inputs

| Field | Type | Default | Range/Options | Notes | |------|------|---------|--------------|------| | low_pass | CONDITIONING | – | – | Low-frequency conditioning list produced by the split node. | | high_pass | CONDITIONING | – | – | High-frequency conditioning list to recombine. | | low_gain | FLOAT | 1.0 | -5.0..5.0 | Multiplier for the low-pass band before merging. | | high_gain | FLOAT | 1.0 | -5.0..5.0 | Multiplier for the high-pass band before merging. |

Conditioning (Scale)

Scales conditioning embeddings (and pooled_output when present) to amplify or mute prompt influence.

Menu category: conditioning/filter
Returns: CONDITIONING

Inputs

| Field | Type | Default | Range/Options | Notes | |------|------|---------|--------------|------| | conditioning | CONDITIONING | – | – | Conditioning list to scale. | | factor | FLOAT | 1.0 | 0.0..10.0 | Multiplier applied to embeddings. 0 mutes, 1 keeps original. |

Development

Run tests with pytest.