SDPose-OOD: Video to Pose Map
Upload a video to extract pose keypoints and generate a pose map. The workflow supports multiple person detection and uses an enhanced SDPose model for accurate whole-body feature extraction.
简介
This ComfyUI tutorial walks you through SDPose-OOD: Video to Pose Map — a workflow that converts any input video into a clean pose map sequence. The pipeline starts with LoadVideo to decode frames, runs each frame through the SDPose-OOD pose extractor (backed by the sdpose_wholebody_fp16.safetensors checkpoint) to detect whole-body keypoints, and then assembles the pose frames into a final clip with CreateVideo and SaveVideo. The SDPose-OOD node (type ID 01b6a731-fb78-4070-9a38-c87146da9604) supports multi-person detection and outputs a rendered pose map per frame, covering body, hands, and face landmarks.
你需要提供
- 正在读取工作流
在 ComfyUI 中运行。 此工作流无法在本页面运行。你可以在 Comfy Cloud 中打开（已预先加载所需内容），或下载后在自己的 ComfyUI 中使用。
在 Cloud 中试用常见问答
Yes. The SDPose-OOD node supports multi-person detection and will render pose maps for all detected subjects per frame. For crowded scenes, consider raising the confidence threshold to reduce false positives.
Use sdpose_wholebody_fp16.safetensors. Place it in ComfyUI/models/checkpoints/. Then select it in the SDPose-OOD node before running the workflow.
Pass the frame rate from LoadVideo into CreateVideo, and keep the output resolution consistent with the input. This preserves one-to-one timing and sizing for downstream use.
Try increasing the input resolution for clearer details, raise the detection confidence to reduce noise, and ensure good lighting and contrast in the source. For performance-constrained GPUs, balance resolution and frame skip to maintain stability.