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LEv145
2023-04-05 00:20:20 +02:00
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.gitignore
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# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class
# C extensions
*.so
# Distribution / packaging
.Python
build/
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dist/
downloads/
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lib64/
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var/
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*.egg-info/
.installed.cfg
*.egg
MANIFEST
# PyInstaller
# Usually these files are written by a python script from a template
# before PyInstaller builds the exe, so as to inject date/other infos into it.
*.manifest
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# Unit test / coverage reports
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*.cover
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# Translations
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# Django stuff:
*.log
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#poetry.lock
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#pdm.lock
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# in version control.
# https://pdm.fming.dev/#use-with-ide
.pdm.toml
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README.md
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# XYPlot: Comfy plugin
![Image](./workflows/xy_plot_mini.png)
[Workflows](./workflows/xy_plot_mini.json)
![Image](./workflows/xy_plot_base.png)
[Workflows](./workflows/xy_plot_base.json)
## How to use
### Install
```
cd custom_nodes # From comfy path
git clone https://github.com/LEv145/XY-plot-comfy-plugin XYPlot
```
### Update
```
cd custom_nodes/XYPlot
git pull
```
__init__.py
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from .src import ImageSetAreaNode, FloatImageCombineNode, XYPlotNode
NODE_CLASS_MAPPINGS = {
"ImageSetArea": ImageSetAreaNode,
"FloatImageCombine": FloatImageCombineNode,
"XYPlot": XYPlotNode,
}
src/__init__.py
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from .nodes.image_set_area import ImageSetAreaNode
from .nodes.float_image_combine import FloatImageCombineNode
from .nodes.xy_plot import XYPlotNode
src/base.py
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import typing as t
class BasePlotNode():
CATEGORY: str = "XYPlot"
FUNCTION: str = "execute"
Image = t.Any
FloatImage = list[Image]
src/nodes/float_image_combine.py
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import typing as t
from ..base import BasePlotNode, FloatImage
class FloatImageCombineNode(BasePlotNode):
RETURN_TYPES: t.Tuple[str] = ("FLOAT_IMAGE",)
@classmethod
def INPUT_TYPES(cls) -> t.Dict[str, t.Any]:
return {
"required": {
"float_image_1": ("FLOAT_IMAGE",),
"float_image_2": ("FLOAT_IMAGE",),
},
}
def execute(self, float_image_1: FloatImage, float_image_2: FloatImage) -> tuple[FloatImage]:
return (float_image_1 + float_image_2,)
src/nodes/image_set_area.py
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import typing as t
from ..base import BasePlotNode, FloatImage, Image
class ImageSetAreaNode(BasePlotNode):
RETURN_TYPES: t.Tuple[str] = ("FLOAT_IMAGE",)
def __init__(self):
pass
@classmethod
def INPUT_TYPES(cls) -> t.Dict[str, t.Any]:
return {
"required": {
"image": ("IMAGE",),
},
}
def execute(self, image: Image) -> tuple[FloatImage]:
return ([image],)
src/nodes/xy_plot.py
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import typing as t
from ..base import BasePlotNode, FloatImage, Image
from ..utils import tensor_to_pillow, pillow_to_tensor, create_image_grid
class XYPlotNode(BasePlotNode):
RETURN_TYPES: t.Tuple[str] = ("IMAGE",)
@classmethod
def INPUT_TYPES(cls) -> t.Dict[str, t.Any]:
return {
"required": {
"float_image": ("FLOAT_IMAGE",),
"gap": ("INT", {"default": 0, "min": 0}),
"nrow": ("INT", {"default": 1, "min": 1}),
},
}
def execute(
self,
float_image: FloatImage,
nrow: int,
gap: int
) -> tuple[Image]:
pillow_images = [tensor_to_pillow(i) for i in float_image]
pillow_grid = create_image_grid(pillow_images, nrow=nrow, gap=gap)
tensor_grid = pillow_to_tensor(pillow_grid)
return (tensor_grid,)
src/utils.py
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import typing as t
import torch
import numpy as np
from PIL import Image
def tensor_to_pillow(image):
return Image.fromarray(np.clip(255. * image.cpu().numpy().squeeze(), 0, 255).astype(np.uint8))
def pillow_to_tensor(image):
return torch.from_numpy(np.array(image).astype(np.float32) / 255.0).unsqueeze(0)
def create_image_grid(images, gap, nrow):
"""
Create a grid of images with a specified gap and number of rows.
Args:
images (List[PIL.Image.Image]): List of images to be placed in the grid.
gap (int, optional): Gap between images in pixels. Defaults to 10.
nrow (int, optional): Number of rows in the grid. Defaults to 3.
Returns:
PIL.Image.Image: The merged image grid.
"""
# Calculate number of columns based on number of rows and images
ncol = (len(images) + nrow - 1) // nrow
# Get size of each image in pixels
image_width, image_height = images[0].size
# Create new image to hold the grid
grid_width = ncol * image_width + (ncol - 1) * gap
grid_height = nrow * image_height + (nrow - 1) * gap
grid_image = Image.new("RGB", (grid_width, grid_height), color="white")
# Paste images into grid
for i, image in enumerate(images):
row = i // ncol
col = i % ncol
x = col * (image_width + gap)
y = row * (image_height + gap)
grid_image.paste(image, (x, y))
return grid_image
workflows/xy_plot_base.json
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workflows/xy_plot_mini.json
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{
"last_node_id": 44,
"last_link_id": 75,
"nodes": [
{
"id": 15,
"type": "PreviewImage",
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],
"size": {
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"1": 290.6986999511719
},
"flags": {},
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"mode": 0,
"inputs": [
{
"name": "images",
"type": "IMAGE",
"link": 20
}
],
"properties": {
"Node name for S&R": "PreviewImage"
}
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"1": 26
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}
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"slot_index": 0
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],
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}
],
"outputs": [
{
"name": "FLOAT_IMAGE",
"type": "FLOAT_IMAGE",
"links": [
32
],
"slot_index": 0
}
],
"properties": {
"Node name for S&R": "FloatImageCombine"
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],
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"properties": {
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"Node name for S&R": "ImageSetArea"
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"config": {},
"extra": {},
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}
workflows/xy_plot_mini.png
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