66 lines
2.7 KiB
Markdown
66 lines
2.7 KiB
Markdown
# Documentation
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- Class name: ImageBorder
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- Category: Mikey/Image
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- Output node: False
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- Repo Ref: https://github.com/bash-j/mikey_nodes
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ImageBorder节点旨在为图像添加装饰性边框，增强其视觉吸引力。它支持各种边框样式，如棋盘格、模糊或纯色，允许定制以适应不同的设计需求。
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# Input types
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## Required
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- image
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- 图像参数是必需的，因为它是将应用边框的基础输入。它直接影响最终输出的外观。
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- Comfy dtype: IMAGE
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- Python dtype: PIL.Image.Image or torch.Tensor
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- border_width
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- border_width参数定义了要添加在图像周围的边框的厚度，这显著影响带边框图像的整体美学。
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- Comfy dtype: INT
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- Python dtype: int
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- border_color
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- border_color参数允许用户指定边框的颜色，可以是纯色、棋盘格图案或模糊效果，以获得更精致的外观。
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- Comfy dtype: STRING
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- Python dtype: str
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# Output types
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- image
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- 输出图像包括带有新应用边框的原始图像，可供进一步处理或展示。
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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 ImageBorder:
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@classmethod
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def INPUT_TYPES(cls):
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return {'required': {'image': ('IMAGE',), 'border_width': ('INT', {'default': 10, 'min': 0, 'max': 1000}), 'border_color': ('STRING', {'default': 'black'})}}
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RETURN_TYPES = ('IMAGE',)
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RETURN_NAMES = ('image',)
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FUNCTION = 'border'
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CATEGORY = 'Mikey/Image'
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def blur_border(self, image, border_width):
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scale_factor = (image.width + border_width * 2) / image.width
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border_image = image.resize((int(image.width * scale_factor), int(image.height * scale_factor)))
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border_image = border_image.filter(ImageFilter.GaussianBlur(radius=border_width * 0.5))
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border_image.paste(image, (border_width, border_width))
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return pil2tensor(border_image)[None, :, :, :]
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@apply_to_batch
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def border(self, image, border_width, border_color):
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orig_image = tensor2pil(image)
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(width, height) = orig_image.size
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if border_color == 'checkerboard':
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return checkerboard_border(image, border_width, 'black')
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if border_color == 'blur':
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return self.blur_border(orig_image, border_width)
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if border_color.startswith('(') and border_color.endswith(')'):
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border_color = border_color[1:-1]
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border_color = tuple(map(int, border_color.split(',')))
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border_image = Image.new('RGB', (width + border_width * 2, height + border_width * 2), border_color)
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border_image.paste(orig_image, (border_width, border_width))
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return pil2tensor(border_image)
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``` |