本ComfyUI工作流可根据用户自定义的镜头或主体路径，从单张图片生成短视频。它采用Wan 2.1 I2V ATI模型，将文本提示、参考图片和轨迹JSON结合，使镜头移动或物体运动可控。核心节点包括UNETLoader（Wan2_1-I2V-ATI-14B_fp8_e4m3fn.safetensors）、VAELoader（wan_2.1_vae.safetensors）作为扩散主干，CLIPLoader和CLIPTextEncode用于提示词条件，CLIPVisionLoader和CLIPVisionEncode用于图像条件，WanTrackToVideo实现轨迹控制。KSampler（由ModelSamplingSD3驱动）负责去噪，VAEDecode将潜变量转为帧，CreateVideo和SaveVideo输出最终视频。
技术上，工作流通过CLIPTextEncode编码正/负提示词，通过CLIPVisionEncode提取输入图像特征。PrimitiveStringMultiline节点存放从Trajectory-Annotation-Tool导出的轨迹JSON，WanTrackToVideo读取该JSON并将逐帧运动控制注入采样过程。ModelSamplingSD3配置调度器，使KSampler的去噪与Wan 2.1训练设置兼容。采样后，VAEDecode重建帧，CreateVideo按设定分辨率和帧率组装。以4090D 24GB显卡、720x480分辨率为例，首次运行约500秒，权重缓存后约463秒（实际时间视设置而定）。
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 "Wan ATI" (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("video_wan_ati_api.json");
const asset = client.assets.fromFile("input.png");
wf.setInput("240", "image", asset); // LoadImage
wf.setInput("6", "text", "your prompt here"); // CLIPTextEncode
const job = await client.run(wf);
await job.getOutputs("258")[0].toFile("output.png"); // SaveVideoThe 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.
常见问题
