# Documentation - Class name: CreateShapeMask - Category: KJNodes/masking/generate - Output node: False - Repo Ref: https://github.com/kenjiqq/ComfyUI_KJNodes CreateShapeMask是一个专用于生成特定形状的掩码或多帧掩码批次的节点。它允许通过调整形状在不同帧之间的生长来动态创建动画掩码,为在各种尺寸和形状下生成掩码提供了一个多功能的工具。 # Input types ## Required - shape - 指定要创建的掩码的几何形状。这个选择会影响生成的掩码的视觉外观和边界。 - Comfy dtype: COMBO[STRING] - Python dtype: str - frames - 确定动画掩码的帧数,允许创建一系列逐渐生长的掩码序列。 - Comfy dtype: INT - Python dtype: int - location_x - 形状中心位置的x坐标,定义了形状在帧内水平方向上的位置。 - Comfy dtype: INT - Python dtype: int - location_y - 形状中心位置的y坐标,定义了形状在帧内垂直方向上的位置。 - Comfy dtype: INT - Python dtype: int - grow - 控制每一帧中形状增长的量,使掩码能够产生动画效果。 - Comfy dtype: INT - Python dtype: int - frame_width - 放置形状的帧的宽度,设置掩码的水平边界。 - Comfy dtype: INT - Python dtype: int - frame_height - 放置形状的帧的高度,设置掩码的垂直边界。 - Comfy dtype: INT - Python dtype: int - shape_width - 指定形状的初始宽度,决定了在应用任何增长前的尺寸。 - Comfy dtype: INT - Python dtype: int - shape_height - 指定形状的初始高度,决定了在应用任何增长前的尺寸。 - Comfy dtype: INT - Python dtype: int # Output types - mask - 具有指定形状和尺寸的生成掩码。 - Comfy dtype: MASK - Python dtype: torch.Tensor - mask_inverted - 生成掩码的反转版本,其中形状区域是透明的,其余部分是不透明的。 - Comfy dtype: MASK - Python dtype: torch.Tensor ## Usage tips - Infra type: `CPU` - Common nodes: - [MaskToImage](../../Comfy/Nodes/MaskToImage.md) ## Source code ```python class CreateShapeMask: RETURN_TYPES = ("MASK", "MASK",) RETURN_NAMES = ("mask", "mask_inverted",) FUNCTION = "createshapemask" CATEGORY = "KJNodes/masking/generate" DESCRIPTION = """ Creates a mask or batch of masks with the specified shape. Locations are center locations. Grow value is the amount to grow the shape on each frame, creating animated masks. """ @classmethod def INPUT_TYPES(s): return { "required": { "shape": ( [ 'circle', 'square', 'triangle', ], { "default": 'circle' }), "frames": ("INT", {"default": 1,"min": 1, "max": 4096, "step": 1}), "location_x": ("INT", {"default": 256,"min": 0, "max": 4096, "step": 1}), "location_y": ("INT", {"default": 256,"min": 0, "max": 4096, "step": 1}), "grow": ("INT", {"default": 0, "min": -512, "max": 512, "step": 1}), "frame_width": ("INT", {"default": 512,"min": 16, "max": 4096, "step": 1}), "frame_height": ("INT", {"default": 512,"min": 16, "max": 4096, "step": 1}), "shape_width": ("INT", {"default": 128,"min": 8, "max": 4096, "step": 1}), "shape_height": ("INT", {"default": 128,"min": 8, "max": 4096, "step": 1}), }, } def createshapemask(self, frames, frame_width, frame_height, location_x, location_y, shape_width, shape_height, grow, shape): # Define the number of images in the batch batch_size = frames out = [] color = "white" for i in range(batch_size): image = Image.new("RGB", (frame_width, frame_height), "black") draw = ImageDraw.Draw(image) # Calculate the size for this frame and ensure it's not less than 0 current_width = max(0, shape_width + i*grow) current_height = max(0, shape_height + i*grow) if shape == 'circle' or shape == 'square': # Define the bounding box for the shape left_up_point = (location_x - current_width // 2, location_y - current_height // 2) right_down_point = (location_x + current_width // 2, location_y + current_height // 2) two_points = [left_up_point, right_down_point] if shape == 'circle': draw.ellipse(two_points, fill=color) elif shape == 'square': draw.rectangle(two_points, fill=color) elif shape == 'triangle': # Define the points for the triangle left_up_point = (location_x - current_width // 2, location_y + current_height // 2) # bottom left right_down_point = (location_x + current_width // 2, location_y + current_height // 2) # bottom right top_point = (location_x, location_y - current_height // 2) # top point draw.polygon([top_point, left_up_point, right_down_point], fill=color) image = pil2tensor(image) mask = image[:, :, :, 0] out.append(mask) outstack = torch.cat(out, dim=0) return (outstack, 1.0 - outstack,) ```