84 lines
3.5 KiB
Markdown
84 lines
3.5 KiB
Markdown
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# Documentation
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- Class name: Inference_Core_PixelPerfectResolution
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- Category: ControlNet Preprocessors
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- Output node: False
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- Repo Ref: https://github.com/comfyanonymous/ComfyUI
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Inference_Core_PixelPerfectResolution节点旨在为图像生成任务计算最佳分辨率。它通过基于目标尺寸和指定的调整模式来调整图像大小，确保像素完美的精确度。该节点专注于实现最高保真度的视觉输出，并根据目标分辨率的要求进行定制。
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# Input types
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## Required
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- original_image
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- 作为计算最佳分辨率基础的原始图像（以numpy数组形式）。这个输入是整个处理过程的起点，决定了最终输出的基本特征。
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- Comfy dtype: IMAGE
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- Python dtype: np.ndarray
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- image_gen_width
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- 图像的目标宽度，指导计算过程以达到这个维度。它直接影响最终输出图像的横向尺寸，是决定视觉效果的关键参数之一。
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- Comfy dtype: INT
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- Python dtype: int
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- image_gen_height
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- 图像的目标高度，指导计算过程以达到这个维度。它直接影响最终输出图像的纵向尺寸，与宽度一起决定了图像的整体比例和分辨率。
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- Comfy dtype: INT
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- Python dtype: int
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- resize_mode
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- 指定调整大小的模式（如内部适应、外部适应等），用于确定如何缩放图像以满足目标尺寸。这个参数决定了图像在调整过程中如何保持其原有特征，对最终视觉效果有重要影响。
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- Comfy dtype: COMBO[STRING]
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- Python dtype: ResizeMode
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# Output types
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- RESOLUTION (INT)
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- 计算出的图像最佳维度（以整数形式），确保像素完美的分辨率。这个输出代表了经过优化后的图像尺寸，能够在保持原始图像特征的同时，最大程度地满足目标分辨率的要求。
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- Comfy dtype: INT
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- Python dtype: int
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## Usage tips
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- Infra type: `CPU`
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- Common nodes: unknown
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## Source code
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```python
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class PixelPerfectResolution:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"original_image": ("IMAGE", ),
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"image_gen_width": ("INT", {"default": 512, "min": 64, "max": MAX_IMAGEGEN_RESOLUTION, "step": 8}),
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"image_gen_height": ("INT", {"default": 512, "min": 64, "max": MAX_IMAGEGEN_RESOLUTION, "step": 8}),
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#https://github.com/comfyanonymous/ComfyUI/blob/c910b4a01ca58b04e5d4ab4c747680b996ada02b/nodes.py#L854
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"resize_mode": (RESIZE_MODES, {"default": ResizeMode.RESIZE.value})
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}
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}
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RETURN_TYPES = ("INT",)
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RETURN_NAMES = ("RESOLUTION (INT)", )
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FUNCTION = "execute"
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CATEGORY = "ControlNet Preprocessors"
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def execute(self, original_image, image_gen_width, image_gen_height, resize_mode):
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_, raw_H, raw_W, _ = original_image.shape
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k0 = float(image_gen_height) / float(raw_H)
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k1 = float(image_gen_width) / float(raw_W)
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if resize_mode == ResizeMode.OUTER_FIT.value:
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estimation = min(k0, k1) * float(min(raw_H, raw_W))
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else:
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estimation = max(k0, k1) * float(min(raw_H, raw_W))
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log.debug(f"Pixel Perfect Computation:")
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log.debug(f"resize_mode = {resize_mode}")
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log.debug(f"raw_H = {raw_H}")
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log.debug(f"raw_W = {raw_W}")
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log.debug(f"target_H = {image_gen_height}")
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log.debug(f"target_W = {image_gen_width}")
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log.debug(f"estimation = {estimation}")
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return (int(np.round(estimation)), )
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```
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