121 lines
4.1 KiB
Markdown
121 lines
4.1 KiB
Markdown
|
|
# Documentation
|
|
- Class name: Keyer
|
|
- Category: image/filters
|
|
- Output node: False
|
|
|
|
Keyer节点专门用于图像处理，特别是进行键控操作，根据颜色和亮度标准有选择地调整图像区域的透明度。它允许对图像进行复杂的操作，能够创建或修改alpha通道，以实现背景去除或合成等效果。
|
|
|
|
# Input types
|
|
## Required
|
|
- images
|
|
- 要处理的图像，作为键控操作的主要输入。这个参数对于定义哪些图像将经过键控过程至关重要。
|
|
- Comfy dtype: IMAGE
|
|
- Python dtype: List[Image]
|
|
- operation
|
|
- 指定要执行的键控操作，影响如何评估图像的颜色和亮度水平以确定透明度。
|
|
- Comfy dtype: COMBO[STRING]
|
|
- Python dtype: str
|
|
- low
|
|
- 定义键控操作的下限阈值，确定像素被视为透明的最小值。
|
|
- Comfy dtype: FLOAT
|
|
- Python dtype: float
|
|
- high
|
|
- 设置键控操作的上限阈值，确定像素被视为透明的最大值。
|
|
- Comfy dtype: FLOAT
|
|
- Python dtype: float
|
|
- gamma
|
|
- 调整键控操作的gamma值，影响中间调对比度和键控图像的整体外观。
|
|
- Comfy dtype: FLOAT
|
|
- Python dtype: float
|
|
- premult
|
|
- 决定输出图像是否应该与其alpha通道预乘，影响合成工作流程中的混合行为。
|
|
- Comfy dtype: BOOLEAN
|
|
- Python dtype: bool
|
|
|
|
# Output types
|
|
- image
|
|
- 键控操作后处理的图像，根据指定标准调整了透明度。
|
|
- Comfy dtype: IMAGE
|
|
- Python dtype: Image
|
|
- alpha
|
|
- 由键控操作生成或修改的alpha通道，代表处理后图像的透明度水平。
|
|
- Comfy dtype: IMAGE
|
|
- Python dtype: Alpha
|
|
- mask
|
|
- 从键控操作派生的遮罩，指示图像内的透明和不透明区域。
|
|
- Comfy dtype: MASK
|
|
- Python dtype: Mask
|
|
|
|
|
|
## Usage tips
|
|
- Infra type: `GPU`
|
|
- Common nodes: unknown
|
|
|
|
|
|
## Source code
|
|
```python
|
|
class Keyer:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {
|
|
"required": {
|
|
"images": ("IMAGE",),
|
|
"operation": (["luminance", "saturation", "max", "min", "red", "green", "blue", "redscreen", "greenscreen", "bluescreen"],),
|
|
"low": ("FLOAT",{"default": 0, "step": 0.001}),
|
|
"high": ("FLOAT",{"default": 1, "step": 0.001}),
|
|
"gamma": ("FLOAT",{"default": 1.0, "min": 0.001, "step": 0.001}),
|
|
"premult": ("BOOLEAN", {"default": True}),
|
|
},
|
|
}
|
|
|
|
RETURN_TYPES = ("IMAGE", "IMAGE", "MASK")
|
|
RETURN_NAMES = ("image", "alpha", "mask")
|
|
FUNCTION = "keyer"
|
|
|
|
CATEGORY = "image/filters"
|
|
|
|
def keyer(self, images, operation, low, high, gamma, premult):
|
|
t = images[:,:,:,:3].detach().clone()
|
|
|
|
if operation == "luminance":
|
|
alpha = 0.2126 * t[:,:,:,0] + 0.7152 * t[:,:,:,1] + 0.0722 * t[:,:,:,2]
|
|
elif operation == "saturation":
|
|
minV = torch.min(t, 3)[0]
|
|
maxV = torch.max(t, 3)[0]
|
|
mask = maxV != 0
|
|
alpha = maxV
|
|
alpha[mask] = (maxV[mask] - minV[mask]) / maxV[mask]
|
|
elif operation == "max":
|
|
alpha = torch.max(t, 3)[0]
|
|
elif operation == "min":
|
|
alpha = torch.min(t, 3)[0]
|
|
elif operation == "red":
|
|
alpha = t[:,:,:,0]
|
|
elif operation == "green":
|
|
alpha = t[:,:,:,1]
|
|
elif operation == "blue":
|
|
alpha = t[:,:,:,2]
|
|
elif operation == "redscreen":
|
|
alpha = 0.7 * (t[:,:,:,1] + t[:,:,:,2]) - t[:,:,:,0] + 1
|
|
elif operation == "greenscreen":
|
|
alpha = 0.7 * (t[:,:,:,0] + t[:,:,:,2]) - t[:,:,:,1] + 1
|
|
elif operation == "bluescreen":
|
|
alpha = 0.7 * (t[:,:,:,0] + t[:,:,:,1]) - t[:,:,:,2] + 1
|
|
else: # should never be reached
|
|
alpha = t[:,:,:,0] * 0
|
|
|
|
if low == high:
|
|
alpha = (alpha > high).to(t.dtype)
|
|
else:
|
|
alpha = (alpha - low) / (high - low)
|
|
|
|
if gamma != 1.0:
|
|
alpha = torch.pow(alpha, 1/gamma)
|
|
alpha = torch.clamp(alpha, min=0, max=1).unsqueeze(3).repeat(1,1,1,3)
|
|
if premult:
|
|
t *= alpha
|
|
return (t, alpha, alpha[:,:,:,0])
|
|
|
|
```
|