Tensor Batch to Image

Documentation

• Class name: Tensor Batch to Image
• Category: WAS Suite/Latent/Transform
• Output node: False

This node is designed to convert a batch of tensor images into a single tensor image based on a specified index. It facilitates the selection of a specific image from a batch for further processing or visualization.

Input types

Required

• images_batch
  • A batch of images represented as tensors. This input is crucial for selecting a specific image from the batch for conversion.
  • Comfy dtype: IMAGE
  • Python dtype: List[torch.Tensor]
• batch_image_number
  • The index of the image within the batch to be converted into a tensor image. This parameter determines which image from the batch is selected for output.
  • Comfy dtype: INT
  • Python dtype: int

Output types

• image
  • Comfy dtype: IMAGE
  • The output is a single tensor image selected from the input batch based on the specified index.
  • Python dtype: torch.Tensor

Usage tips

• Infra type: GPU
• Common nodes: unknown

Source code

class WAS_Tensor_Batch_to_Image:
    def __init__(self):
        pass

    @classmethod
    def INPUT_TYPES(cls):
        return {
            "required": {
                "images_batch": ("IMAGE",),
                "batch_image_number": ("INT", {"default": 0, "min": 0, "max": 64, "step": 1}),
            },
        }

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

    CATEGORY = "WAS Suite/Latent/Transform"

    def tensor_batch_to_image(self, images_batch=[], batch_image_number=0):

        count = 0
        for _ in images_batch:
            if batch_image_number == count:
                return (images_batch[batch_image_number].unsqueeze(0), )
            count = count+1

        cstr(f"Batch number `{batch_image_number}` is not defined, returning last image").error.print()
        return (images_batch[-1].unsqueeze(0), )