This ComfyUI workflow is designed to convert video footage into a temporally stable pose control map using the OpenPose technique. It leverages the DWPose model to accurately detect and map human poses throughout the video sequence. The workflow utilizes several key nodes, including DWPreprocessor for initial data preparation, VHS_LoadVideo for importing video files, and VHS_VideoCombine for merging processed frames into a cohesive output. The use of comfyui-videohelpersuite and comfyui_controlnet_aux custom nodes ensures enhanced video processing capabilities and pose detection accuracy. This workflow is particularly useful for applications requiring detailed human pose analysis, such as animation, video editing, and motion capture.
API
Use this workflow from code
Every Comfy workflow is a JSON graph. The payload below is this workflow, exactly as ComfyUI runs it — fetch it from the URL, keep it in version control, or load it in ComfyUI and run it node by node.
Run it from TypeScript or Python with the Comfy SDK. The same code targets Comfy Cloud or a ComfyUI you host yourself — only the base URL changes.
// Install (beta)
npm i @comfyorg/sdk
// Run "Video to Pose Map - OpenPose" (TypeScript)
import { Comfy } from "@comfyorg/sdk";
const client = new Comfy({ apiKey: "comfyui-..." });
// This workflow, exported in API format (see note below)
const wf = await client.workflows.fromFile("utility-openpose-video_api.json");
const job = await client.run(wf);
await job.getOutputs("4")[0].toFile("output.png"); // VHS_VideoCombineThe SDK takes a workflow in API format: open this workflow in ComfyUI and use File → Export Workflow (API).
Comfy Cloud API access requires a plan with an API key.
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