Lightweight ComfyUI node for text-prompted segmentation masks ◧ using CLIPSeg and mask auto-aligned trim. numpy 2.x safe, TensorFlow-free, auto model caching.

◧ AP ClipSEG Mask Light

Generates a segmentation mask from a text prompt using CLIPSeg.

Works with numpy 2.x.

prompt:
  Main text description of the region to segment, e.g. 'face' or 'person'.
  Separate multiple prompts with '|' to average their heatmaps:
  e.g.  'face | head | eyes'

threshold:
  Sigmoid-normalised heatmap value above which a pixel is considered foreground.
  Lower = larger mask, higher = tighter mask.

smooth_radius:
  Gaussian blur applied to the heatmap before thresholding.  Helps produce
  cleaner soft edges.  0 = no smoothing.

model:
  clipseg_rd64  – higher quality, ~350 MB download, slower
  clipseg_rd16  – faster, ~100 MB, slightly lower quality

device:
  auto = use cuda when available, else cpu.  Models are cached in memory so
  subsequent frames do not reload weights.

unload_after_run:
  Free the model from memory after each execution.  Enable to save VRAM when
  this node is not used every frame.

ComfyUI Node: ◧ AP CLIPSeg Text Mask

Category

Inputs

Outputs

Extension: ◧ AP ClipSEG Mask Light

More nodes in ◧ AP ClipSEG Mask Light

Run ComfyUI workflows without the setup