CavinHuang-comfyui-nodes-docs/nodes-docs/en-US/SaltAI/docs/SaltBatchCropDataExtractor.md

tags

tags
Crop Image ImageTransformation

Extract Crop Data from Batch

Documentation

• Class name: SaltBatchCropDataExtractor
• Category: SALT/Masking/Process
• Output node: False

The SaltBatchCropDataExtractor node is designed to process a batch of crop data, extracting specific crop information and dimensions for a given index within the batch. It aims to facilitate the manipulation and analysis of crop data by providing detailed metrics such as width, height, and boundary coordinates.

Input types

Required

• crop_data_batch
  • The batch of crop data to be processed. It is essential for determining the specific crop information and dimensions to be extracted.
  • Comfy dtype: CROP_DATA_BATCH
  • Python dtype: List[Tuple[Tuple[int, int], Tuple[int, int, int, int]]]
• index
  • The index within the crop data batch from which to extract crop information. It dictates the specific crop data to be processed.
  • Comfy dtype: INT
  • Python dtype: int

Output types

• crop_data_batch
  • Comfy dtype: CROP_DATA_BATCH
  • The extracted crop data for the specified index, including size and boundary coordinates.
  • Python dtype: List[Tuple[Tuple[int, int], Tuple[int, int, int, int]]]
• width
  • Comfy dtype: INT
  • The width of the crop area.
  • Python dtype: int
• height
  • Comfy dtype: INT
  • The height of the crop area.
  • Python dtype: int
• top
  • Comfy dtype: INT
  • The top boundary coordinate of the crop area.
  • Python dtype: int
• left
  • Comfy dtype: INT
  • The left boundary coordinate of the crop area.
  • Python dtype: int
• right
  • Comfy dtype: INT
  • The right boundary coordinate of the crop area.
  • Python dtype: int
• bottom
  • Comfy dtype: INT
  • The bottom boundary coordinate of the crop area.
  • Python dtype: int

Usage tips

• Infra type: CPU
• Common nodes: unknown

Source code

class SaltBatchCropDataExtractor:
    @classmethod
    def INPUT_TYPES(cls):
        return {
            "required": {
                "crop_data_batch": ("CROP_DATA_BATCH",),
                "index": ("INT", {"min": 0}),
            }
        }

    RETURN_TYPES = ("CROP_DATA_BATCH", "INT", "INT", "INT", "INT", "INT", "INT")
    RETURN_NAMES = ("crop_data_batch", "width", "height", "top", "left", "right", "bottom")

    FUNCTION = "extract"
    CATEGORY = f"{NAME}/Masking/Process"

    def extract(self, crop_data_batch, index):
        if index < 0 or index >= len(crop_data_batch):
            raise ValueError("Index out of range")

        try:
            crop_size, (crop_left, crop_top, crop_right, crop_bottom) = crop_data_batch[index]
            width = crop_right - crop_left
            height = crop_bottom - crop_top
            single_crop_data = [(crop_size, (crop_left, crop_top, crop_right, crop_bottom))]
            return single_crop_data, width, height, crop_top, crop_left, crop_right, crop_bottom
        except Exception as e:
            print(e)
            return [((0, 0), (0, 0, 0, 0))], 0, 0, 0, 0, 0, 0