119 lines
3.7 KiB
Markdown
119 lines
3.7 KiB
Markdown
# Documentation
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- Class name: GradientImage
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- Category: 😺dzNodes/LayerUtility
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- Output node: False
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- Repo Ref: https://github.com/chflame163/ComfyUI_LayerStyle
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生成一张指定大小和指定颜色渐变的图片。GradientImage的V2升级版。
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*仅限输入image和mask, 如果强制接入其他类型输入，将导致节点错误。
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*预设尺寸在custom_size.ini中定义，这个文件位于插件根目录下, 默认名字是custom_size.ini.example, 初次使用这个文件需将文件后缀改为.ini。用文本编辑软件打开，编辑自定义尺寸。每行表示一个尺寸，第一个数值是宽度，第二个是高度，中间用小写的"x"分隔。为避免错误请不要输入多余的字符。
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# Input types
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## Required
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- size
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- 图片的尺寸。
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- Comfy dtype: STRING
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- Python dtype: str
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- 可选值: 'custom',
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- custom_width
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- 图像宽度。当size设置为"custom"时有效。如果有size_as输入，此处选项将被忽略。
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- Comfy dtype: INT
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- Python dtype: int
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- custom_height
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- 图像高度。当size设置为"custom"时有效。如果有size_as输入，此处选项将被忽略。
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- Comfy dtype: INT
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- Python dtype: int
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- angle
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- 渐变的角度。
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- Comfy dtype: INT
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- Python dtype: int
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- start_color
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- 渐变的起始颜色。
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- Comfy dtype: STRING
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- Python dtype: str
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- end_color
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- 渐变的结束颜色。
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- Comfy dtype: STRING
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- Python dtype: str
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## Optional
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- size_as
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- 输入图像或遮罩，将按照其尺寸生成输出图像。注意，此输入优先级高于其他的尺寸设置。
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- Comfy dtype: IMAGE, MASK
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- Python dtype: torch.Tensor
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# Output types
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- image
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- 生成的图像。
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- Comfy dtype: IMAGE
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- Python dtype: torch.Tensor
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# Usage tips
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- Infra type: CPU
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# Source code
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```
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class GradientImageV2:
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(self):
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size_list = ['custom']
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size_list.extend(load_custom_size())
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return {
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"required": {
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"size": (size_list,),
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"custom_width": ("INT", {"default": 512, "min": 4, "max": 99999, "step": 1}),
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"custom_height": ("INT", {"default": 512, "min": 4, "max": 99999, "step": 1}),
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"angle": ("INT", {"default": 0, "min": -360, "max": 360, "step": 1}),
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"start_color": ("STRING", {"default": "#FFFFFF"},),
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"end_color": ("STRING", {"default": "#000000"},),
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},
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"optional": {
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"size_as": (any, {}),
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}
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}
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RETURN_TYPES = ("IMAGE", )
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RETURN_NAMES = ("image", )
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FUNCTION = 'gradient_image_v2'
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CATEGORY = '😺dzNodes/LayerUtility'
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def gradient_image_v2(self, size, custom_width, custom_height, angle, start_color, end_color, size_as=None):
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if size_as is not None:
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if size_as.shape[0] > 0:
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_asimage = tensor2pil(size_as[0])
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else:
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_asimage = tensor2pil(size_as)
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width, height = _asimage.size
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else:
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if size == 'custom':
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width = custom_width
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height = custom_height
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else:
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try:
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_s = size.split('x')
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width = int(_s[0].strip())
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height = int(_s[1].strip())
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except Exception as e:
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log(f"Warning: {NODE_NAME} invalid size, check {custom_size_file}", message_type='warning')
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width = custom_width
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height = custom_height
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ret_image = gradient(start_color, end_color, width, height, angle)
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return (pil2tensor(ret_image), )
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``` |