DOGMA Nodes

DOGMA Nodes

Custom ComfyUI nodes for DOGMA AI video workflows.

Nodes

WAN VACE Keyframe Control Prep

Category:

video/WAN VACE

This node prepares a WAN VACE control video and control mask video from:

video             IMAGE batch
mask_video        IMAGE batch
reference_frames  IMAGE batch
keyframe_indices  STRING

It replaces selected video frames with the corresponding reference frames, turns the mask fully black at those same frames, and pads the result to a WAN VACE-compatible frame count.

WAN VACE expects frame counts in the form:

4n + 1

So the node pads the sequence by duplicating frames at the beginning and end, symmetrically, with preference for the beginning when the padding count is odd.

keyframe_indices supports comma, space, or semicolon separated values.

Examples:

start, 25, end
0 24 48
first; 32; last

Indexing is 0-based.

0 = first frame
24 = 25th frame
end = last frame

Outputs:

control_video       IMAGE batch
control_mask_video  IMAGE batch
frame_count         INT
padding_info        WANVACE_PAD_INFO

WAN VACE Remove Added Padding

Category:

video/WAN VACE

This node removes the replicated start/end frames that were added by WAN VACE Keyframe Control Prep.

Use it after WAN VACE generation when a later crop-and-stitch step needs the generated video to return to the original unpadded frame count.

Inputs:

video         IMAGE batch
padding_info  WANVACE_PAD_INFO

Output:

video        IMAGE batch
frame_count  INT

Typical use:

WAN VACE Keyframe Control Prep → padding_info
WAN generated video            → WAN VACE Remove Added Padding

DOGMA Sampler Select

Category:

sampling/custom_sampling/samplers

This node returns a DOGMA sampler as a SAMPLER object. Use it with SamplerCustomAdvanced and any SIGMAS source, including custom hand-drawn sigma curves.

The same DOGMA samplers are also registered into normal ComfyUI sampler menus after restart, so they can appear in ordinary KSampler, KSampler Advanced, and KSamplerSelect dropdowns.

Available samplers:

| Sampler | Intended use | Approximate model calls | |---|---|---:| | DOGMA_klein_distilled_REBUILD | T2I, strong edit, heavily damaged upscale tile | 2 × non-final steps + 1 | | DOGMA_klein_distilled_BALANCED | General T2I / i2i / edit | 2 × non-final steps + 1 | | DOGMA_klein_distilled_DETAIL | Soft edit, good upscale tile, fine reconstruction | 3 × non-final steps + 1 | | DOGMA_klein_basemodel_REBUILD | Fast strong reconstruction, bad source anatomy or structure | 1 × steps | | DOGMA_klein_basemodel_BALANCED | General base-model work with selective correction | Usually 1.2-1.35 × steps | | DOGMA_klein_basemodel_DETAIL | Soft edit and upscale refinement; extra work at low sigma | Usually 1.4-1.5 × steps |

These are experimental ODE samplers designed around FLUX.2 Klein 9B workflows: three for the 4-6 step distilled model and three for the 20-50 step base model. No LoRA is included or required.

Install

Install through ComfyUI Manager as DOGMA Nodes, or with:

comfy node install comfyui-dogma-nodes

Notes

The nodes use only PyTorch and ComfyUI's built-in sampler APIs. No extra Python dependencies are required.