◧ AP CLIPSeg Text Mask

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.