v 1.0.0
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# XYPlot: Comfy plugin
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## How to use
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### Install
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```
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cd custom_nodes # From comfy path
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git clone https://github.com/LEv145/XY-plot-comfy-plugin XYPlot
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```
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### Update
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```
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cd custom_nodes/XYPlot
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git pull
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```
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## Workflows
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[Workflows](./workflows)
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from .src import ImageSetAreaNode, FloatImageCombineNode, XYPlotNode
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NODE_CLASS_MAPPINGS = {
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"ImageSetArea": ImageSetAreaNode,
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"FloatImageCombine": FloatImageCombineNode,
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"XYPlot": XYPlotNode,
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}
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from .nodes.image_set_area import ImageSetAreaNode
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from .nodes.float_image_combine import FloatImageCombineNode
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from .nodes.xy_plot import XYPlotNode
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import typing as t
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class BasePlotNode():
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CATEGORY: str = "XYPlot"
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FUNCTION: str = "execute"
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Image = t.Any
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FloatImage = list[Image]
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import typing as t
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from ..base import BasePlotNode, FloatImage
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class FloatImageCombineNode(BasePlotNode):
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RETURN_TYPES: t.Tuple[str] = ("FLOAT_IMAGE",)
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@classmethod
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def INPUT_TYPES(cls) -> t.Dict[str, t.Any]:
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return {
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"required": {
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"float_image_1": ("FLOAT_IMAGE",),
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"float_image_2": ("FLOAT_IMAGE",),
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},
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}
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def execute(self, float_image_1: FloatImage, float_image_2: FloatImage) -> tuple[FloatImage]:
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return (float_image_1 + float_image_2,)
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@@ -0,0 +1,21 @@
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import typing as t
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from ..base import BasePlotNode, FloatImage, Image
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class ImageSetAreaNode(BasePlotNode):
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RETURN_TYPES: t.Tuple[str] = ("FLOAT_IMAGE",)
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(cls) -> t.Dict[str, t.Any]:
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return {
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"required": {
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"image": ("IMAGE",),
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},
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}
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def execute(self, image: Image) -> tuple[FloatImage]:
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return ([image],)
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import typing as t
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from ..base import BasePlotNode, FloatImage, Image
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from ..utils import tensor_to_pillow, pillow_to_tensor, create_image_grid
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class XYPlotNode(BasePlotNode):
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RETURN_TYPES: t.Tuple[str] = ("IMAGE",)
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@classmethod
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def INPUT_TYPES(cls) -> t.Dict[str, t.Any]:
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return {
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"required": {
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"float_image": ("FLOAT_IMAGE",),
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"gap": ("INT", {"default": 0, "min": 0}),
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"nrow": ("INT", {"default": 1, "min": 1}),
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},
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}
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def execute(
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self,
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float_image: FloatImage,
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nrow: int,
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gap: int
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) -> tuple[Image]:
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pillow_images = [tensor_to_pillow(i) for i in float_image]
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pillow_grid = create_image_grid(pillow_images, nrow=nrow, gap=gap)
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tensor_grid = pillow_to_tensor(pillow_grid)
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return (tensor_grid,)
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import typing as t
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import torch
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import numpy as np
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from PIL import Image
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def tensor_to_pillow(image):
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return Image.fromarray(np.clip(255. * image.cpu().numpy().squeeze(), 0, 255).astype(np.uint8))
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def pillow_to_tensor(image):
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return torch.from_numpy(np.array(image).astype(np.float32) / 255.0).unsqueeze(0)
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def create_image_grid(images, gap, nrow):
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"""
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Create a grid of images with a specified gap and number of rows.
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Args:
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images (List[PIL.Image.Image]): List of images to be placed in the grid.
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gap (int, optional): Gap between images in pixels. Defaults to 10.
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nrow (int, optional): Number of rows in the grid. Defaults to 3.
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Returns:
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PIL.Image.Image: The merged image grid.
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"""
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# Calculate number of columns based on number of rows and images
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ncol = (len(images) + nrow - 1) // nrow
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# Get size of each image in pixels
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image_width, image_height = images[0].size
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# Create new image to hold the grid
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grid_width = ncol * image_width + (ncol - 1) * gap
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grid_height = nrow * image_height + (nrow - 1) * gap
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grid_image = Image.new("RGB", (grid_width, grid_height), color="white")
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# Paste images into grid
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for i, image in enumerate(images):
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row = i // ncol
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col = i % ncol
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x = col * (image_width + gap)
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y = row * (image_height + gap)
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grid_image.paste(image, (x, y))
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return grid_image
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Load Diff
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{
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"last_node_id": 44,
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"last_link_id": 75,
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"nodes": [
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{
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"id": 15,
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"type": "PreviewImage",
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"pos": [
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],
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"size": {
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},
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"order": 9,
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"mode": 0,
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"inputs": [
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{
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"name": "images",
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"type": "IMAGE",
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}
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],
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"properties": {
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"Node name for S&R": "PreviewImage"
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}
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},
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{
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"id": 10,
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"type": "ImageSetArea",
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"type": "IMAGE",
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}
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||||
],
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"outputs": [
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{
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"name": "FLOAT_IMAGE",
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"type": "FLOAT_IMAGE",
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"links": [
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12
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],
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||||
"slot_index": 0
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}
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],
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"properties": {
|
||||
"Node name for S&R": "ImageSetArea"
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||||
}
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},
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{
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"id": 12,
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"type": "FloatImageCombine",
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"pos": [
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||||
],
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||||
"size": {
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"flags": {},
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"mode": 0,
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"inputs": [
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{
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||||
"name": "float_image_1",
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||||
"type": "FLOAT_IMAGE",
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"link": 12
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||||
},
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{
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||||
"name": "float_image_2",
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"type": "FLOAT_IMAGE",
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"link": 13
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}
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||||
],
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||||
"outputs": [
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{
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"name": "FLOAT_IMAGE",
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"type": "FLOAT_IMAGE",
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"links": [
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],
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"slot_index": 0
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}
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],
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"properties": {
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||||
"Node name for S&R": "FloatImageCombine"
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}
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||||
},
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||||
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"type": "FloatImageCombine",
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"name": "float_image_1",
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{
|
||||
"name": "float_image_2",
|
||||
"type": "FLOAT_IMAGE",
|
||||
"link": 22
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||||
}
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|
||||
"outputs": [
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{
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||||
"name": "FLOAT_IMAGE",
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||||
"type": "FLOAT_IMAGE",
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"links": [
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||||
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||||
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||||
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],
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||||
"properties": {
|
||||
"Node name for S&R": "FloatImageCombine"
|
||||
}
|
||||
},
|
||||
{
|
||||
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|
||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
{
|
||||
"name": "MASK",
|
||||
"type": "MASK",
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||||
"links": null
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||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "LoadImage"
|
||||
},
|
||||
"widgets_values": [
|
||||
"ComfyUI_00171_.png",
|
||||
"image"
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 43,
|
||||
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||||
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||||
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||||
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||||
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|
||||
"mode": 0,
|
||||
"outputs": [
|
||||
{
|
||||
"name": "IMAGE",
|
||||
"type": "IMAGE",
|
||||
"links": [
|
||||
75
|
||||
],
|
||||
"slot_index": 0
|
||||
},
|
||||
{
|
||||
"name": "MASK",
|
||||
"type": "MASK",
|
||||
"links": null
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "LoadImage"
|
||||
},
|
||||
"widgets_values": [
|
||||
"ComfyUI_00116_.png",
|
||||
"image"
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 17,
|
||||
"type": "XYPlot",
|
||||
"pos": [
|
||||
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|
||||
326
|
||||
],
|
||||
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|
||||
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||||
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|
||||
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|
||||
"inputs": [
|
||||
{
|
||||
"name": "float_image",
|
||||
"type": "FLOAT_IMAGE",
|
||||
"link": 24
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"name": "IMAGE",
|
||||
"type": "IMAGE",
|
||||
"links": [
|
||||
20
|
||||
],
|
||||
"slot_index": 0
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "XYPlot"
|
||||
},
|
||||
"widgets_values": [
|
||||
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|
||||
2
|
||||
]
|
||||
},
|
||||
{
|
||||
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|
||||
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|
||||
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||||
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"mode": 0,
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"outputs": [
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{
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"name": "IMAGE",
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"type": "IMAGE",
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||||
"links": [
|
||||
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],
|
||||
"slot_index": 0
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},
|
||||
{
|
||||
"name": "MASK",
|
||||
"type": "MASK",
|
||||
"links": null
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "LoadImage"
|
||||
},
|
||||
"widgets_values": [
|
||||
"ComfyUI_00153_.png",
|
||||
"image"
|
||||
]
|
||||
}
|
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],
|
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"links": [
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|
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|
||||
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|
||||
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],
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],
|
||||
[
|
||||
75,
|
||||
43,
|
||||
0,
|
||||
18,
|
||||
0,
|
||||
"IMAGE"
|
||||
]
|
||||
],
|
||||
"groups": [],
|
||||
"config": {},
|
||||
"extra": {},
|
||||
"version": 0.4
|
||||
}
|
||||
Reference in New Issue
Block a user