CavinHuang-comfyui-nodes-docs/nodes-docs/en-US/ComfyUI-Easy-Use/docs/easy loadImageBase64.md

tags

tags
Image

Load Image (Base64)

Documentation

• Class name: easy loadImageBase64
• Category: EasyUse/Image/LoadImage
• Output node: True

The node easy loadImageBase64 is designed to load images encoded in Base64 format, converting them into a format suitable for further image processing or manipulation within the ComfyUI framework. It serves as a bridge between encoded image data and the internal image representation used in image processing pipelines, facilitating the integration of externally sourced images.

Input types

Required

• base64_data
  • The base64_data parameter is the Base64 encoded string of the image data. It is essential for decoding the image back into a usable format for processing and manipulation within the node.
  • Comfy dtype: STRING
  • Python dtype: str
• image_output
  • The image_output parameter specifies how the loaded image should be handled, such as displaying, hiding, or saving the image.
  • Comfy dtype: COMBO[STRING]
  • Python dtype: str
• save_prefix
  • The save_prefix parameter determines the prefix for the filename when saving the processed image.
  • Comfy dtype: STRING
  • Python dtype: str

Optional

Output types

• image
  • Comfy dtype: IMAGE
  • The image output is the processed image in a tensor format, ready for further manipulation or analysis within the ComfyUI framework.
  • Python dtype: torch.Tensor
• mask
  • Comfy dtype: MASK
  • The mask output provides an optional mask tensor if the image contains transparency information, useful for further image processing steps.
  • Python dtype: Optional[torch.Tensor]

Usage tips

• Infra type: CPU
• Common nodes: unknown

Source code

class loadImageBase64:
  @classmethod
  def INPUT_TYPES(s):
    return {
      "required": {
        "base64_data": ("STRING", {"default": ""}),
        "image_output": (["Hide", "Preview", "Save", "Hide/Save"], {"default": "Preview"}),
        "save_prefix": ("STRING", {"default": "ComfyUI"}),
      },
      "optional": {

      },
      "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
    }

  RETURN_TYPES = ("IMAGE", "MASK")
  OUTPUT_NODE = True
  FUNCTION = "load_image"
  CATEGORY = "EasyUse/Image/LoadImage"

  def convert_color(self, image,):
    if len(image.shape) > 2 and image.shape[2] >= 4:
      return cv2.cvtColor(image, cv2.COLOR_BGRA2RGB)
    return cv2.cvtColor(image, cv2.COLOR_BGR2RGB)

  def load_image(self, base64_data, image_output, save_prefix, prompt=None, extra_pnginfo=None):
    nparr = np.frombuffer(base64.b64decode(base64_data), np.uint8)

    result = cv2.imdecode(nparr, cv2.IMREAD_UNCHANGED)
    channels = cv2.split(result)
    if len(channels) > 3:
      mask = channels[3].astype(np.float32) / 255.0
      mask = torch.from_numpy(mask)
    else:
      mask = torch.ones(channels[0].shape, dtype=torch.float32, device="cpu")

    result = self.convert_color(result)
    result = result.astype(np.float32) / 255.0
    new_images = torch.from_numpy(result)[None,]

    results = easySave(new_images, save_prefix, image_output, None, None)
    mask = mask.unsqueeze(0)

    if image_output in ("Hide", "Hide/Save"):
      return {"ui": {},
              "result": (new_images, mask)}

    return {"ui": {"images": results},
            "result": (new_images, mask)}