118 lines
3.6 KiB
Markdown
118 lines
3.6 KiB
Markdown
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# Documentation
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- Class name: DF_Image_scale_to_side
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- Category: Derfuu_Nodes/Modded nodes/Image
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- Output node: False
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该节点旨在将图像放大到指定的边长，同时保持纵横比。它允许用户选择要缩放的边（宽度、高度、最长边或最短边）、放大方法以及是否应用裁剪，为图像处理任务提供了灵活性。
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# Input types
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## Required
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- image
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- 需要放大的输入图像。它作为放大过程的基础，决定了将被调整的初始尺寸和纵横比。
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- Comfy dtype: IMAGE
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- Python dtype: torch.Tensor
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- side_length
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- 指定图像将被缩放到的目标边长（宽度或高度）。这个值直接影响放大后图像的最终尺寸。
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- Comfy dtype: INT
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- Python dtype: int
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- side
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- 决定图像的哪一边（宽度、高度、最长边或最短边）将被缩放到指定的边长，影响放大的方向和最终的纵横比。
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- Comfy dtype: COMBO[STRING]
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- Python dtype: str
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- upscale_method
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- 用于放大图像的方法，影响输出图像的质量和特征。
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- Comfy dtype: COMBO[STRING]
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- Python dtype: str
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- crop
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- 指示是否以及如何裁剪放大后的图像，影响最终的构图和尺寸。
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- Comfy dtype: COMBO[STRING]
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- Python dtype: str
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# Output types
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- image
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- 放大后的图像，已调整到指定的边长，同时保持原始纵横比。
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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: `GPU`
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- Common nodes:
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- Reroute
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- [ImpactImageInfo](../../ComfyUI-Impact-Pack/Nodes/ImpactImageInfo.md)
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- [VAEEncode](../../Comfy/Nodes/VAEEncode.md)
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## Source code
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```python
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class ImageScale_Side:
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scale_methods = scale_methods
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crop_methods = ["disabled", "center"]
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def __init__(self) -> None:
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pass
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"image": Field.image(),
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"side_length": Field.int(),
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"side": Field.combo(["Longest", "Shortest", "Width", "Height"]),
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"upscale_method": Field.combo(cls.scale_methods),
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"crop": Field.combo(cls.crop_methods)
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}
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}
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RETURN_TYPES = ("IMAGE",)
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FUNCTION = "upscale"
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CATEGORY = TREE_IMAGES
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def upscale(self, image, upscale_method, side_length: int, side: str, crop):
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samples = image.movedim(-1, 1)
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size = get_image_size(image)
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width_B = int(size[0])
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height_B = int(size[1])
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width = width_B
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height = height_B
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def determineSide(_side: str) -> tuple[int, int]:
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width, height = 0, 0
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if _side == "Width":
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heigh_ratio = height_B / width_B
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width = side_length
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height = heigh_ratio * width
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elif _side == "Height":
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width_ratio = width_B / height_B
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height = side_length
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width = width_ratio * height
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return width, height
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if side == "Longest":
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if width > height:
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width, height = determineSide("Width")
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else:
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width, height = determineSide("Height")
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elif side == "Shortest":
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if width < height:
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width, height = determineSide("Width")
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else:
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width, height = determineSide("Height")
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else:
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width, height = determineSide(side)
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width = math.ceil(width)
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height = math.ceil(height)
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cls = common_upscale(samples, width, height, upscale_method, crop)
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cls = cls.movedim(1, -1)
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return (cls,)
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```
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