90 lines
2.8 KiB
Markdown
90 lines
2.8 KiB
Markdown
|
|
# Documentation
|
|
- Class name: SaltBatchCropDataExtractor
|
|
- Category: SALT/Masking/Process
|
|
- Output node: False
|
|
- Repo Ref: https://github.com/comfyanonymous/ComfyUI
|
|
|
|
SaltBatchCropDataExtractor节点用于处理一批裁剪数据，从批次中提取特定索引的裁剪信息和尺寸。它旨在通过提供详细的指标（如宽度、高度和边界坐标）来促进裁剪数据的操作和分析。
|
|
|
|
# Input types
|
|
## Required
|
|
- crop_data_batch
|
|
- 待处理的裁剪数据批次。它对于确定要提取的特定裁剪信息和尺寸至关重要。
|
|
- Comfy dtype: CROP_DATA_BATCH
|
|
- Python dtype: List[Tuple[Tuple[int, int], Tuple[int, int, int, int]]]
|
|
- index
|
|
- 裁剪数据批次中要提取裁剪信息的索引。它决定了要处理的具体裁剪数据。
|
|
- Comfy dtype: INT
|
|
- Python dtype: int
|
|
|
|
# Output types
|
|
- crop_data_batch
|
|
- 指定索引的提取裁剪数据，包括尺寸和边界坐标。
|
|
- Comfy dtype: CROP_DATA_BATCH
|
|
- Python dtype: List[Tuple[Tuple[int, int], Tuple[int, int, int, int]]]
|
|
- width
|
|
- 裁剪区域的宽度。
|
|
- Comfy dtype: INT
|
|
- Python dtype: int
|
|
- height
|
|
- 裁剪区域的高度。
|
|
- Comfy dtype: INT
|
|
- Python dtype: int
|
|
- top
|
|
- 裁剪区域的上边界坐标。
|
|
- Comfy dtype: INT
|
|
- Python dtype: int
|
|
- left
|
|
- 裁剪区域的左边界坐标。
|
|
- Comfy dtype: INT
|
|
- Python dtype: int
|
|
- right
|
|
- 裁剪区域的右边界坐标。
|
|
- Comfy dtype: INT
|
|
- Python dtype: int
|
|
- bottom
|
|
- 裁剪区域的下边界坐标。
|
|
- Comfy dtype: INT
|
|
- Python dtype: int
|
|
|
|
|
|
## Usage tips
|
|
- Infra type: `CPU`
|
|
- Common nodes: unknown
|
|
|
|
|
|
## Source code
|
|
```python
|
|
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
|
|
|
|
```
|