67 lines
2.7 KiB
Markdown
67 lines
2.7 KiB
Markdown
# Documentation
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- Class name: PixelKSampleHookCombine
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- Category: image_processing
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- Output node: False
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- Repo Ref: https://github.com/ltdrdata/ComfyUI-Impact-Pack.git
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PixelKSampleHookCombine 是一个节点，旨在将两个独立的钩子顺序应用于一系列图像处理操作。它协调钩子以特定顺序预处理、解码、放大和编码像素数据，确保图像操作任务的协同工作流程。
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# Input types
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## Required
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- hook1
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- 第一个要顺序应用的钩子。它在图像处理的初始阶段起着至关重要的作用，为后续操作奠定基础。
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- Comfy dtype: PixelKSampleHook
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- Python dtype: PixelKSampleHook
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- hook2
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- 第二个要顺序应用的钩子，它在第一个钩子应用后进一步细化图像处理流水线，提高整体输出质量。
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- Comfy dtype: PixelKSampleHook
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- Python dtype: PixelKSampleHook
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# Output types
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- processed_pixels
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- PixelKSampleHookCombine 节点的输出是将两个钩子应用于输入像素数据后的结果。它代表了所有处理步骤完成后图像的最终状态。
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- Comfy dtype: COMBO[str, torch.Tensor]
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- Python dtype: Union[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 PixelKSampleHookCombine(PixelKSampleHook):
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hook1 = None
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hook2 = None
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def __init__(self, hook1, hook2):
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super().__init__()
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self.hook1 = hook1
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self.hook2 = hook2
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def set_steps(self, info):
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self.hook1.set_steps(info)
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self.hook2.set_steps(info)
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def pre_decode(self, samples):
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return self.hook2.pre_decode(self.hook1.pre_decode(samples))
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def post_decode(self, pixels):
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return self.hook2.post_decode(self.hook1.post_decode(pixels))
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def post_upscale(self, pixels):
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return self.hook2.post_upscale(self.hook1.post_upscale(pixels))
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def post_encode(self, samples):
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return self.hook2.post_encode(self.hook1.post_encode(samples))
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def post_crop_region(self, w, h, item_bbox, crop_region):
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crop_region = self.hook1.post_crop_region(w, h, item_bbox, crop_region)
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return self.hook2.post_crop_region(w, h, item_bbox, crop_region)
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def touch_scaled_size(self, w, h):
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(w, h) = self.hook1.touch_scaled_size(w, h)
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return self.hook2.touch_scaled_size(w, h)
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def pre_ksample(self, model, seed, steps, cfg, sampler_name, scheduler, positive, negative, upscaled_latent, denoise):
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(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, upscaled_latent, denoise) = self.hook1.pre_ksample(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, upscaled_latent, denoise)
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return self.hook2.pre_ksample(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, upscaled_latent, denoise)
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``` |