61 lines
2.3 KiB
Markdown
61 lines
2.3 KiB
Markdown
# Documentation
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- Class name: InjectNoise
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- Category: latent/noise
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- Output node: False
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- Repo Ref: https://github.com/BlenderNeko/ComfyUI_Noise.git
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InjectNoise节点旨在向一组潜在表示中引入噪声，从而模拟噪声对生成过程的影响。它的作用是通过控制的变异性增强数据，这可以提高生成输出的鲁棒性和多样性。
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# Input types
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## Required
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- latents
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- latents参数至关重要，因为它包含将要进行噪声注入的原始潜在表示。它直接影响噪声增强过程的结果。
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- Comfy dtype: LATENT
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- Python dtype: Dict[str, torch.Tensor]
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- strength
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- strength参数决定了要注入到latents中的噪声的强度。它对于控制引入数据的变异程度至关重要。
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- Comfy dtype: FLOAT
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- Python dtype: float
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- noise
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- 可选的noise参数提供了要应用于latents的噪声源。它很重要，因为它允许定制噪声特性。
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- Comfy dtype: LATENT
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- Python dtype: Dict[str, torch.Tensor]
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- mask
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- 当提供mask参数时，它指定latents的哪些区域应该受到噪声的影响。这对于针对性的噪声应用很重要。
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- Comfy dtype: MASK
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- Python dtype: torch.Tensor
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# Output types
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- latents
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- 输出的latents是已经注入了噪声的修改后的潜在表示，准备进行进一步的处理或生成。
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- Comfy dtype: LATENT
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- Python dtype: Dict[str, 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 InjectNoise:
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@classmethod
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def INPUT_TYPES(s):
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return {'required': {'latents': ('LATENT',), 'strength': ('FLOAT', {'default': 1.0, 'min': 0.0, 'max': 200.0, 'step': 0.01})}, 'optional': {'noise': ('LATENT',), 'mask': ('MASK',)}}
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RETURN_TYPES = ('LATENT',)
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FUNCTION = 'inject_noise'
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CATEGORY = 'latent/noise'
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def inject_noise(self, latents, strength, noise=None, mask=None):
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s = latents.copy()
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if noise is None:
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return (s,)
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if latents['samples'].shape != noise['samples'].shape:
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print('warning, shapes in InjectNoise not the same, ignoring')
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return (s,)
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noised = s['samples'].clone() + noise['samples'].clone() * strength
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if mask is not None:
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mask = prepare_mask(mask, noised.shape)
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noised = mask * noised + (1 - mask) * latents['samples']
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s['samples'] = noised
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return (s,)
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``` |