{
  "job": "upscale",
  "rank": 3,
  "short": "second model",
  "title": {
    "zh": "双模型放大",
    "en": "Upscale with a second model"
  },
  "about": {
    "zh": "和「放大」一样，但重画换一个模型：底模放大时不稳（眼睛走样、多出肚脐）就换一个更稳的。新加的模型加载器先是同一个模型，由 AI 按你的意思换。 装了 KJNodes 时，还会把颜色对齐到原图，防止放大后颜色跑偏。",
    "en": "Like Upscale, but the redraw uses a second model, for a base model that goes wrong when enlarged. The new loader starts as the same model; the AI changes it as you say. With KJNodes, its colours are matched to the original, so they don't drift."
  },
  "source": {
    "zh": "参考工作流的「Refiner/放大」加载器和作者的说明",
    "en": "The reference workflow's upscale loader and its author's note"
  },
  "packs": {},
  "upscaler": true,
  "after": "The redraw's model comes from a new loader (second_model), for now the same checkpoint as the first: set_model it to the steadier one the user wants (ask_user, search_models), of the same family (SDXL with SDXL: it reuses the first model's prompts). Then run_workflow; the larger one is saved beside it (prefix upscaled).",
  "notes": "The source keeps a second loader for upscaling; its author: switch to it when the base model goes wrong enlarged. ColorMatch mkl after the redraw is the source's, optional (KJNodes).",
  "upscale_by": 1.25,
  "nodes": {
    "second_model": {
      "class_type": "CheckpointLoaderSimple",
      "like": "$loader",
      "inputs": {}
    },
    "upscaler": {
      "class_type": "UpscaleModelLoader",
      "inputs": {
        "model_name": "$upscaler"
      }
    },
    "enlarge": {
      "class_type": "ImageUpscaleWithModel",
      "inputs": {
        "upscale_model": [
          "upscaler",
          0
        ],
        "image": [
          "$save.images",
          "*"
        ]
      }
    },
    "fit": {
      "class_type": "ImageScaleBy",
      "inputs": {
        "image": [
          "enlarge",
          0
        ],
        "upscale_method": "lanczos",
        "scale_by": "$fit"
      }
    },
    "encode": {
      "class_type": "VAEEncode",
      "inputs": {
        "pixels": [
          "fit",
          0
        ],
        "vae": [
          "$decode.vae",
          "*"
        ]
      }
    },
    "redraw": {
      "class_type": "KSampler",
      "like": "$sampler",
      "inputs": {
        "model": [
          "second_model",
          0
        ],
        "positive": [
          "$sampler.positive",
          "*"
        ],
        "negative": [
          "$sampler.negative",
          "*"
        ],
        "latent_image": [
          "encode",
          0
        ],
        "denoise": 0.35
      }
    },
    "decode": {
      "class_type": "VAEDecode",
      "inputs": {
        "samples": [
          "redraw",
          0
        ],
        "vae": [
          "$decode.vae",
          "*"
        ]
      }
    },
    "match": {
      "class_type": "ColorMatch",
      "optional": true,
      "inputs": {
        "image_ref": [
          "fit",
          0
        ],
        "image_target": [
          "decode",
          0
        ],
        "method": "mkl",
        "strength": 1.0,
        "multithread": true
      }
    },
    "save": {
      "class_type": "SaveImage",
      "inputs": {
        "images": [
          "match|decode",
          0
        ],
        "filename_prefix": "upscaled"
      }
    }
  },
  "extras": {
    "ColorMatch": "ComfyUI-KJNodes"
  },
  "models": [
    "2x_animesharp_v4",
    "4x_ultrasharp"
  ],
  "tested": {
    "gpu": "RTX 4050 Laptop",
    "vram_gb": 6,
    "date": "2026-10-27",
    "runs": [
      {
        "model": "SDXL (Illustrious)",
        "size": "832×1216 → 1.25×",
        "seconds": 44
      }
    ]
  }
}