CavinHuang-comfyui-nodes-docs/docs/BatchAverageUnJittered.md

Documentation

• Class name: BatchAverageUnJittered
• Category: image/filters/jitter
• Output node: False

BatchAverageUnJittered节点旨在通过应用平均或中值操作来处理一批图像，以减少抖动效应。它对图像的子批次进行操作，应用指定的操作来创建更平滑、更稳定的输出图像。

Input types

Required

• images
  • 需要处理的图像批次。这个输入对于确定将应用平均或中值操作的图像集至关重要。
  • Comfy dtype: IMAGE
  • Python dtype: torch.Tensor
• operation
  • 指定要应用于图像的操作（'mean'或'median'）。这个选择影响抖动减少的方法和输出图像的最终外观。
  • Comfy dtype: COMBO[STRING]
  • Python dtype: str

Output types

• image
  • 经过指定的平均或中值操作处理以减少抖动效应后的图像批次。
  • Comfy dtype: IMAGE
  • Python dtype: torch.Tensor

Usage tips

• Infra type: GPU
• Common nodes: unknown

Source code

class BatchAverageUnJittered:
    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "images": ("IMAGE",),
                "operation": (["mean", "median"],),
            },
        }

    RETURN_TYPES = ("IMAGE",)
    FUNCTION = "apply"

    CATEGORY = "image/filters/jitter"

    def apply(self, images, operation):
        t = images.detach().clone()
        
        batch = []
        for i in range(t.shape[0] // 9):
            if operation == "mean":
                batch.append(torch.mean(t[i*9:i*9+9], dim=0, keepdim=True))
            elif operation == "median":
                batch.append(torch.median(t[i*9:i*9+9], dim=0, keepdim=True)[0])
        
        return (torch.cat(batch, dim=0),)