PixelTiledKSampleUpscalerProvider

Documentation

• Class name: PixelTiledKSampleUpscalerProvider
• Category: ImpactPack/Upscale
• Output node: False

This node provides an interface for upscaling images using a tiled K-sample approach, integrating with external sampling tools and strategies for enhanced detail and quality in image upscaling tasks. It leverages a combination of model parameters, sampling techniques, and tiling strategies to optimize the upscaling process.

Input types

Required

• scale_method
  • Specifies the method used for scaling images, impacting the overall upscaling quality and technique.
  • Comfy dtype: COMBO[STRING]
  • Python dtype: str
• model
  • Defines the model used for upscaling, determining the core algorithm and its capabilities.
  • Comfy dtype: MODEL
  • Python dtype: str
• vae
  • The variational autoencoder used in conjunction with the model to enhance image details during upscaling.
  • Comfy dtype: VAE
  • Python dtype: str
• seed
  • Seed for random number generation, ensuring reproducibility of the upscaling results.
  • Comfy dtype: INT
  • Python dtype: int
• steps
  • The number of steps to perform in the upscaling process, affecting the detail and quality of the output.
  • Comfy dtype: INT
  • Python dtype: int
• cfg
  • Configuration setting for controlling aspects of the upscaling process, such as detail levels.
  • Comfy dtype: FLOAT
  • Python dtype: float
• sampler_name
  • The name of the sampler used, influencing the sampling strategy and outcome of the upscaling.
  • Comfy dtype: COMBO[STRING]
  • Python dtype: str
• scheduler
  • Scheduler used to manage the upscaling process, coordinating the execution of steps and tasks.
  • Comfy dtype: COMBO[STRING]
  • Python dtype: str
• positive
  • Positive feedback to guide the upscaling process towards desired outcomes.
  • Comfy dtype: CONDITIONING
  • Python dtype: str
• negative
  • Negative feedback to steer the upscaling away from undesired results.
  • Comfy dtype: CONDITIONING
  • Python dtype: str
• denoise
  • Indicates whether denoising is applied during upscaling, improving image clarity.
  • Comfy dtype: FLOAT
  • Python dtype: bool
• tile_width
  • The width of the tiles used in the tiling strategy, affecting the granularity of the upscaling.
  • Comfy dtype: INT
  • Python dtype: int
• tile_height
  • The height of the tiles used in the tiling strategy, impacting the detail level in specific image areas.
  • Comfy dtype: INT
  • Python dtype: int
• tiling_strategy
  • The strategy employed for tiling during upscaling, influencing the overall approach and effectiveness.
  • Comfy dtype: COMBO[STRING]
  • Python dtype: str

Optional

• upscale_model_opt
  • Optional upscale model to enhance the upscaling process.
  • Comfy dtype: UPSCALE_MODEL
  • Python dtype: str
• pk_hook_opt
  • Optional post-kernel hook for additional processing or adjustments during upscaling.
  • Comfy dtype: PK_HOOK
  • Python dtype: str
• tile_cnet_opt
  • Optional control network for managing tile-based upscaling strategies.
  • Comfy dtype: CONTROL_NET
  • Python dtype: str

Output types

• upscaler
  • Comfy dtype: UPSCALER
  • The result of the upscaling process, providing enhanced image quality and detail.
  • Python dtype: object

Usage tips

• Infra type: GPU
• Common nodes: unknown

Source code

class PixelTiledKSampleUpscalerProvider:
    upscale_methods = ["nearest-exact", "bilinear", "lanczos", "area"]

    @classmethod
    def INPUT_TYPES(s):
        return {"required": {
                    "scale_method": (s.upscale_methods,),
                    "model": ("MODEL",),
                    "vae": ("VAE",),
                    "seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
                    "steps": ("INT", {"default": 20, "min": 1, "max": 10000}),
                    "cfg": ("FLOAT", {"default": 8.0, "min": 0.0, "max": 100.0}),
                    "sampler_name": (comfy.samplers.KSampler.SAMPLERS, ),
                    "scheduler": (comfy.samplers.KSampler.SCHEDULERS, ),
                    "positive": ("CONDITIONING", ),
                    "negative": ("CONDITIONING", ),
                    "denoise": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}),
                    "tile_width": ("INT", {"default": 512, "min": 320, "max": MAX_RESOLUTION, "step": 64}),
                    "tile_height": ("INT", {"default": 512, "min": 320, "max": MAX_RESOLUTION, "step": 64}),
                    "tiling_strategy": (["random", "padded", 'simple'], ),
                    },
                "optional": {
                        "upscale_model_opt": ("UPSCALE_MODEL", ),
                        "pk_hook_opt": ("PK_HOOK", ),
                        "tile_cnet_opt": ("CONTROL_NET", ),
                    }
                }

    RETURN_TYPES = ("UPSCALER",)
    FUNCTION = "doit"

    CATEGORY = "ImpactPack/Upscale"

    def doit(self, scale_method, model, vae, seed, steps, cfg, sampler_name, scheduler, positive, negative, denoise, tile_width, tile_height, tiling_strategy, upscale_model_opt=None, pk_hook_opt=None, tile_cnet_opt=None):
        if "BNK_TiledKSampler" in nodes.NODE_CLASS_MAPPINGS:
            upscaler = core.PixelTiledKSampleUpscaler(scale_method, model, vae, seed, steps, cfg, sampler_name, scheduler, positive, negative, denoise, tile_width, tile_height, tiling_strategy, upscale_model_opt, pk_hook_opt, tile_cnet_opt, tile_size=max(tile_width, tile_height))
            return (upscaler, )
        else:
            print("[ERROR] PixelTiledKSampleUpscalerProvider: ComfyUI_TiledKSampler custom node isn't installed. You must install BlenderNeko/ComfyUI_TiledKSampler extension to use this node.")