This ComfyUI tutorial workflow shows how to upscale a single image using SeedVR2 7B Int8, a one-step diffusion model trained with adversarial objectives and adaptive window attention. Instead of iterative sampling, SeedVR2 performs a single forward pass to enhance resolution and restore detail, making it fast and consistent. The Int8 quantized weights reduce memory usage while preserving most of the model’s fidelity, which is helpful on mid-range GPUs.
Technically, the graph is straightforward: LoadImage feeds your source into the SeedVR2 7B Int8 node (ID: 1970dcb4-982a-4c01-a373-4d239a3041e4), which wraps the SeedVR2 checkpoint and its paired VAE (seedvr2_ema_vae_fp16.safetensors). The model outputs an upscaled image in a single step, which you can preview with ImageCompare (original vs upscaled) and then export via SaveImage. A MarkdownNote in the graph provides quick tips and references. Because it’s a one-step diffusion upscaler, you don’t need to tune sampler steps or schedulers—just set your desired output size (or keep defaults), run, and review.
API
Usa este flujo de trabajo desde código
Cada flujo de trabajo de Comfy es un grafo JSON. El siguiente payload es este flujo de trabajo, exactamente como lo ejecuta ComfyUI: descárgalo desde la URL, guárdalo en control de versiones o cárgalo en ComfyUI y ejecútalo nodo por nodo.
Ejecuta desde TypeScript o Python con el Comfy SDK. El mismo código funciona en Comfy Cloud o en un ComfyUI propio: solo cambia la URL base.
// 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");El SDK utiliza un flujo de trabajo en formato API: abre este flujo de trabajo en ComfyUI y usa Archivo → Exportar flujo de trabajo (API).
El acceso a la API de Comfy Cloud requiere un plan con clave API.
