65 lines
2.0 KiB
Markdown
65 lines
2.0 KiB
Markdown
|
|
# Documentation
|
|
- Class name: Scribble_PiDiNet_Preprocessor
|
|
- Category: ControlNet Preprocessors/Line Extractors
|
|
- Output node: False
|
|
|
|
该节点利用PiDiNet模型预处理图像以提取涂鸦线条，从而增强图像以供进一步处理或可视化。它专注于从输入图像中生成清晰的涂鸦式线条，适用于需要风格化线条绘图或素描的应用场景。
|
|
|
|
# Input types
|
|
## Required
|
|
- image
|
|
- 需要进行涂鸦线条提取处理的输入图像。
|
|
- Comfy dtype: IMAGE
|
|
- Python dtype: torch.Tensor
|
|
|
|
## Optional
|
|
- safe
|
|
- 一种模式，启用时会在处理过程中应用额外的安全检查或约束，以确保处理的稳健性。
|
|
- Comfy dtype: COMBO[STRING]
|
|
- Python dtype: str
|
|
- resolution
|
|
- 在处理前将输入图像缩放到的分辨率。这会影响提取线条的细节程度。
|
|
- Comfy dtype: INT
|
|
- Python dtype: int
|
|
|
|
# Output types
|
|
- image
|
|
- 处理后的图像，包含增强的涂鸦线条，适合可视化或进一步处理。
|
|
- Comfy dtype: IMAGE
|
|
- Python dtype: torch.Tensor
|
|
|
|
|
|
## Usage tips
|
|
- Infra type: `GPU`
|
|
- Common nodes: unknown
|
|
|
|
|
|
## Source code
|
|
```python
|
|
class Scribble_PiDiNet_Preprocessor:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return create_node_input_types(
|
|
safe=(["enable", "disable"], {"default": "enable"})
|
|
)
|
|
|
|
RETURN_TYPES = ("IMAGE",)
|
|
FUNCTION = "execute"
|
|
|
|
CATEGORY = "ControlNet Preprocessors/Line Extractors"
|
|
|
|
def execute(self, image, safe, resolution):
|
|
def model(img, **kwargs):
|
|
from controlnet_aux.pidi import PidiNetDetector
|
|
pidinet = PidiNetDetector.from_pretrained().to(model_management.get_torch_device())
|
|
result = pidinet(img, scribble=True, **kwargs)
|
|
result = nms(result, 127, 3.0)
|
|
result = cv2.GaussianBlur(result, (0, 0), 3.0)
|
|
result[result > 4] = 255
|
|
result[result < 255] = 0
|
|
return result
|
|
return (common_annotator_call(model, image, resolution=resolution, safe=safe=="enable"),)
|
|
|
|
```
|