137 lines
5.2 KiB
Markdown
137 lines
5.2 KiB
Markdown
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# Documentation
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- Class name: CreateShapeMaskOnPath
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- Category: KJNodes/masking/generate
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- Output node: False
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- Repo Ref: https://github.com/comfyanonymous/ComfyUI
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CreateShapeMaskOnPath节点用于沿指定路径生成基于形状的遮罩，能够创建动态和动画化的遮罩效果。它利用形状参数和路径坐标来制作可随时间变化的遮罩，为视觉效果和图像处理提供了一个多功能工具。
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# Input types
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## Required
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- shape
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- 指定要创建的遮罩的几何形状。这个选择影响遮罩的外观，可以是圆形、正方形或三角形，为遮罩提供多种视觉风格选择。
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- Comfy dtype: COMBO[STRING]
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- Python dtype: str
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- coordinates
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- 定义遮罩创建沿路径的中心位置。这些坐标决定了遮罩在画面中的放置位置，允许精确控制遮罩的位置。
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- Comfy dtype: STRING
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- Python dtype: str
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- grow
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- 决定每一帧中形状增长的量，使得可以创建随时间变化大小的动画遮罩。
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- Comfy dtype: INT
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- Python dtype: int
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- frame_width
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- 设置创建遮罩的帧的宽度，定义了遮罩生成的空间边界。
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- Comfy dtype: INT
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- Python dtype: int
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- frame_height
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- 设置创建遮罩的帧的高度，定义了遮罩生成的空间边界。
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- Comfy dtype: INT
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- Python dtype: int
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- shape_width
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- 指定用于创建遮罩的形状的初始宽度，影响遮罩的大小和覆盖区域。
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- Comfy dtype: INT
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- Python dtype: int
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- shape_height
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- 指定用于创建遮罩的形状的初始高度，影响遮罩的大小和覆盖区域。
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- Comfy dtype: INT
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- Python dtype: int
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# Output types
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- mask
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- 根据指定的形状和路径坐标创建的主要输出遮罩。
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- Comfy dtype: MASK
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- Python dtype: Tensor
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- mask_inverted
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- 主要遮罩的反转版本，提供了另一种遮罩选项，其中形状区域是透明的，而周围区域是不透明的。
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- Comfy dtype: MASK
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- Python dtype: Tensor
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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 CreateShapeMaskOnPath:
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RETURN_TYPES = ("MASK", "MASK",)
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RETURN_NAMES = ("mask", "mask_inverted",)
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FUNCTION = "createshapemask"
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CATEGORY = "KJNodes/masking/generate"
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DESCRIPTION = """
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Creates a mask or batch of masks with the specified shape.
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Locations are center locations.
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Grow value is the amount to grow the shape on each frame, creating animated masks.
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"""
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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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"shape": (
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[ 'circle',
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'square',
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'triangle',
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],
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{
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"default": 'circle'
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}),
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"coordinates": ("STRING", {"forceInput": True}),
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"grow": ("INT", {"default": 0, "min": -512, "max": 512, "step": 1}),
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"frame_width": ("INT", {"default": 512,"min": 16, "max": 4096, "step": 1}),
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"frame_height": ("INT", {"default": 512,"min": 16, "max": 4096, "step": 1}),
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"shape_width": ("INT", {"default": 128,"min": 8, "max": 4096, "step": 1}),
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"shape_height": ("INT", {"default": 128,"min": 8, "max": 4096, "step": 1}),
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},
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}
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def createshapemask(self, coordinates, frame_width, frame_height, shape_width, shape_height, grow, shape):
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# Define the number of images in the batch
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coordinates = coordinates.replace("'", '"')
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coordinates = json.loads(coordinates)
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batch_size = len(coordinates)
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out = []
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color = "white"
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for i, coord in enumerate(coordinates):
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image = Image.new("RGB", (frame_width, frame_height), "black")
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draw = ImageDraw.Draw(image)
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# Calculate the size for this frame and ensure it's not less than 0
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current_width = max(0, shape_width + i*grow)
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current_height = max(0, shape_height + i*grow)
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location_x = coord['x']
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location_y = coord['y']
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if shape == 'circle' or shape == 'square':
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# Define the bounding box for the shape
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left_up_point = (location_x - current_width // 2, location_y - current_height // 2)
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right_down_point = (location_x + current_width // 2, location_y + current_height // 2)
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two_points = [left_up_point, right_down_point]
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if shape == 'circle':
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draw.ellipse(two_points, fill=color)
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elif shape == 'square':
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draw.rectangle(two_points, fill=color)
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elif shape == 'triangle':
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# Define the points for the triangle
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left_up_point = (location_x - current_width // 2, location_y + current_height // 2) # bottom left
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right_down_point = (location_x + current_width // 2, location_y + current_height // 2) # bottom right
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top_point = (location_x, location_y - current_height // 2) # top point
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draw.polygon([top_point, left_up_point, right_down_point], fill=color)
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image = pil2tensor(image)
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mask = image[:, :, :, 0]
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out.append(mask)
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outstack = torch.cat(out, dim=0)
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return (outstack, 1.0 - outstack,)
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```
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