This workflow turns a single image into a short, cinematic video using LTX‑2.5’s DFR (Diffusion Fidelity Rendering) path. The subgraph “Image to Video (LTX‑2.5 DFR)” runs a half‑resolution generation to establish motion and generate detailing keyframes, then applies a spatial ×2 detailing pass with a pixel‑spatial IC‑LoRA to recover fine texture. For projects that need extra smoothness, you can optionally add a temporal ×2 pass to densify motion between frames. The result is a cohesive clip that preserves your image’s look while adding natural camera movement and subject animation, with synchronized audio when provided by the subgraph.
Technically, the pipeline is compact and easy to drive in ComfyUI: LoadImage brings in your source frame, ResolutionSelector sets aspect and target size, and the DFR subgraph node (97d5d35b-bb0d-4212-b2f2-97ab13cbfb1f) encapsulates the LTX‑2 family model and its IC‑LoRA detailing passes. PreviewImage helps you quickly inspect a representative frame before final encoding, and SaveVideo writes the finished clip (including audio if the subgraph outputs it). MarkdownNote nodes in the template annotate key choices and link to ComfyUI’s Subgraph feature, so you can open the subgraph and tweak options without getting lost.
API
코드에서 이 워크플로우 사용하기
모든 Comfy 워크플로우는 JSON 그래프입니다. 아래 페이로드는 이 워크플로우 그 자체로, ComfyUI에서 실행되는 것과 동일합니다 — URL에서 가져오거나, 버전 관리에 보관하거나, ComfyUI에서 불러와 노드별로 실행할 수 있습니다.
Comfy SDK로 TypeScript 또는 Python에서 실행하세요. 동일한 코드는 Comfy Cloud 또는 직접 호스팅하는 ComfyUI 모두에 적용됩니다 — 기본 URL만 다릅니다.
// Install (beta)
npm i @comfyorg/sdk
// Run this workflow (TypeScript)
import { Comfy } from "@comfyorg/sdk";
const client = new Comfy({ apiKey: "comfyui-..." });
const wf = await client.workflows.fromFile("workflow_api.json");
const job = await client.run(wf);
await job.getOutputs("<output-node-id>")[0].toFile("output.png");SDK는 API 형식의 워크플로우를 사용합니다: 이 워크플로우를 ComfyUI에서 열고 파일 → 워크플로우 내보내기(API)를 사용하세요.
