62 lines
2.5 KiB
Markdown
62 lines
2.5 KiB
Markdown
# Documentation
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- Class name: Sharpen
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- Category: postprocessing/Filters
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- Output node: False
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- Repo Ref: https://github.com/EllangoK/ComfyUI-post-processing-nodes
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锐化节点通过增强局部对比度来提高图像清晰度。它将锐化核应用于输入图像，放大边缘和细微细节，从而产生更明确和清晰的视觉效果。
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# Input types
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## Required
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- image
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- 图像参数是锐化节点的主要输入，对于节点来说至关重要。它决定了将要进行锐化处理的源材料，影响最终输出的质量和清晰度。
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- Comfy dtype: IMAGE
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- Python dtype: torch.Tensor
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- sharpen_radius
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- 锐化半径参数控制锐化效果的程度。较大的半径会导致更明显的锐化效果，更积极地增强边缘和细节，而较小的半径则产生更微妙的效果。
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- Comfy dtype: INT
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- Python dtype: int
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- alpha
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- alpha参数调整锐化效果的强度。较高的alpha值增加了对比度增强，导致更戏剧性的锐化，而较低的值则产生较轻微的效果。
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- Comfy dtype: FLOAT
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- Python dtype: float
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# Output types
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- result
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- 结果参数是锐化节点的输出，代表锐化后的图像。它反映了锐化效果的应用，展示了提高的清晰度和定义明确的边缘。
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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 Sharpen:
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(s):
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return {'required': {'image': ('IMAGE',), 'sharpen_radius': ('INT', {'default': 1, 'min': 1, 'max': 15, 'step': 1}), 'alpha': ('FLOAT', {'default': 1.0, 'min': 0.1, 'max': 5.0, 'step': 0.1})}}
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RETURN_TYPES = ('IMAGE',)
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FUNCTION = 'sharpen'
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CATEGORY = 'postprocessing/Filters'
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def sharpen(self, image: torch.Tensor, blur_radius: int, alpha: float):
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if blur_radius == 0:
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return (image,)
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(batch_size, height, width, channels) = image.shape
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kernel_size = blur_radius * 2 + 1
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kernel = torch.ones((kernel_size, kernel_size), dtype=torch.float32) * -1
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center = kernel_size // 2
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kernel[center, center] = kernel_size ** 2
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kernel *= alpha
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kernel = kernel.repeat(channels, 1, 1).unsqueeze(1)
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tensor_image = image.permute(0, 3, 1, 2)
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sharpened = F.conv2d(tensor_image, kernel, padding=center, groups=channels)
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sharpened = sharpened.permute(0, 2, 3, 1)
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result = torch.clamp(sharpened, 0, 1)
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return (result,)
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``` |