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
通过代码使用此工作流
每个 Comfy 工作流都是一个 JSON 图。下面的内容就是此工作流的完整数据，ComfyUI 运行时也是如此——你可以从该 URL 获取、放入版本控制，或在 ComfyUI 中加载并逐节点运行。
使用 Comfy SDK 从 TypeScript 或 Python 运行。相同代码可用于 Comfy Cloud 或你自托管的 ComfyUI——只需更改基础 URL。
// 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");SDK 需要 API 格式的工作流：在 ComfyUI 中打开此工作流，使用 文件 → 导出工作流（API）。
