CavinHuang-comfyui-nodes-docs/docs/LayerUtility%3A ImageRemoveAlpha.md

Documentation

• Class name: ImageRemoveAlpha
• Category: 😺dzNodes/LayerUtility
• Output node: False
• Repo Ref: https://github.com/chflame163/ComfyUI_LayerStyle

移除图片的alpha通道，将图片转换为RGB模式。可选择填充背景以及设置背景颜色。

Input types

Required

• RGBA_image

  • 输入的图像，支持RGBA或RGB模式。
  • Comfy dtype: IMAGE
  • Python dtype: torch.Tensor

• fill_background

  • 填充背景。
  • Comfy dtype: BOOLEAN
  • Python dtype: bool

• background_color

  • 背景颜色。
  • Comfy dtype: STRING
  • Python dtype: str

Optional

• mask
  • 可选输入遮罩。如果有输入遮罩将优先使用, 忽略RGBA_image自带的alpha。
  • Comfy dtype: MASK
  • Python dtype: torch.Tensor

Output types

• RGB_image
  • 处理后的RGB图片。
  • Comfy dtype: IMAGE
  • Python dtype: torch.Tensor

Usage tips

• Infra type: CPU

Source code

class ImageRemoveAlpha:

    def __init__(self):
        pass

    @classmethod
    def INPUT_TYPES(self):

        return {
            "required": {
                "RGBA_image": ("IMAGE", ),  #
                "fill_background": ("BOOLEAN", {"default": False}),
                "background_color": ("STRING", {"default": "#000000"}),
            },
            "optional": {
                "mask": ("MASK",),  #
            }
        }

    RETURN_TYPES = ("IMAGE", )
    RETURN_NAMES = ("RGB_image", )
    FUNCTION = 'image_remove_alpha'
    CATEGORY = '😺dzNodes/LayerUtility'

    def image_remove_alpha(self, RGBA_image, fill_background, background_color, mask=None):

        ret_images = []

        for index, img in enumerate(RGBA_image):
            _image = tensor2pil(img)

            if fill_background:
                if mask is not None:
                    m = mask[index].unsqueeze(0) if index < len(mask) else mask[-1].unsqueeze(0)
                    alpha = tensor2pil(m).convert('L')
                elif _image.mode == "RGBA":
                    alpha = _image.split()[-1]
                else:
                    log(f"Error: {NODE_NAME} skipped, because the input image is not RGBA and mask is None.",
                        message_type='error')
                    return (RGBA_image,)
                ret_image = Image.new('RGB', size=_image.size, color=background_color)
                ret_image.paste(_image, mask=alpha)
                ret_images.append(pil2tensor(ret_image))

            else:
                ret_images.append(pil2tensor(tensor2pil(i).convert('RGB')))

        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
        return (torch.cat(ret_images, dim=0), )