Extensions/ComfyUI-DukeStereo
ComfyUI Extension

ComfyUI-DukeStereo

A ComfyUI custom node that converts video frames to side-by-side (SBS) stereo format for VR viewing.

By killertofu86·Created 6 months ago·Updated 6 months ago· 0
killertofu86/ComfyUI-DukeStereo
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CategoryStereo
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Updated6 months ago
Readme

ComfyUI-DukeStereo

A ComfyUI custom node that converts video frames to side-by-side (SBS) stereo format for VR viewing.

Features

  • Polylines Fill - High-quality gap filling during stereo warping (from StereoImage Node)
  • Edge-aware depth blur - Smooths depth while preserving edges
  • Streaming output - RAM-efficient, writes frames directly to video
  • H.264/yuv420p - VR-player compatible output
  • Format-Strings - %date:yyyy-MM-dd%, %time:HH-mm-ss%, %divergence%, %width% etc.
  • Home-Expansion - ~/video/... paths supported
  • Auto-Increment - Existing files get _001, _002 suffix

Installation

cd ComfyUI/custom_nodes
git clone https://github.com/killertofu86/ComfyUI-DukeStereo.git
pip install -r ComfyUI-DukeStereo/requirements.txt

Requirements

  • torch, transformers, numpy, Pillow, numba, scipy, ffmpeg

Parameters

| Parameter | Default | Description | |-----------|---------|-------------| | output_path | stereo_output.mp4 | Output path with format strings | | divergence | 2.5 | 3D strength (higher = more depth) | | separation | 0.0 | Additional horizontal offset | | stereo_offset_exponent | 2.0 | Non-linear depth curve | | convergence_point | 1.0 | Zero-parallax plane (0.0-1.0) | | fill_technique | polylines_soft | Gap filling: polylines_soft, polylines_sharp, none | | depth_blur | 0 | Depth blur kernel (0 = off) | | depth_blur_edge_threshold | 6.0 | Edge preservation threshold | | fps | 24 | Output framerate | | crf | 19 | Quality (lower = better) |

Inputs

  • images - Video frames (IMAGE)
  • depth_maps - Depth maps from LeReS or similar (IMAGE)

Output Path Examples

~/video/stereo_%date:yyyy-MM-dd%_%time:HH-mm-ss%.mp4
~/video/test_div%divergence%.mp4
/output/stereo_%width%x%height%.mp4

License

MIT