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https://git.datalinker.icu/kijai/ComfyUI-KJNodes.git
synced 2026-01-24 13:14:32 +08:00
Don't fill the alpha by default
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d7f91f2c65
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@ -1677,7 +1677,7 @@ class LoadAndResizeImage:
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"keep_proportion": ("BOOLEAN", { "default": False }),
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"divisible_by": ("INT", { "default": 2, "min": 0, "max": 512, "step": 1, }),
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"mask_channel": (s._color_channels, {"tooltip": "Channel to use for the mask output"}),
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"background_color": ("STRING", { "default": "white", "tooltip": "Color to fill the alpha channel with. Enter a comma-separated RGB value. E.g. 255, 255, 255 for white."}),
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"background_color": ("STRING", { "default": "", "tooltip": "Fills the alpha channel with the specified color."}),
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},
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}
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@ -1687,24 +1687,29 @@ class LoadAndResizeImage:
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FUNCTION = "load_image"
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def load_image(self, image, resize, width, height, repeat, keep_proportion, divisible_by, mask_channel, background_color):
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from PIL import ImageColor
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from PIL import ImageColor, Image, ImageOps, ImageSequence
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import numpy as np
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import torch
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image_path = folder_paths.get_annotated_filepath(image)
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import node_helpers
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img = node_helpers.pillow(Image.open, image_path)
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# Process the background_color
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try:
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# Try to parse as RGB tuple
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bg_color_rgba = tuple(int(x.strip()) for x in background_color.split(','))
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except ValueError:
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# If parsing fails, it might be a hex color or named color
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if background_color.startswith('#') or background_color.lower() in ImageColor.colormap:
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bg_color_rgba = ImageColor.getrgb(background_color)
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else:
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raise ValueError(f"Invalid background color: {background_color}")
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if background_color:
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try:
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# Try to parse as RGB tuple
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bg_color_rgba = tuple(int(x.strip()) for x in background_color.split(','))
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except ValueError:
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# If parsing fails, it might be a hex color or named color
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if background_color.startswith('#') or background_color.lower() in ImageColor.colormap:
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bg_color_rgba = ImageColor.getrgb(background_color)
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else:
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raise ValueError(f"Invalid background color: {background_color}")
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bg_color_rgba += (255,) # Add alpha channel
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bg_color_rgba += (255,) # Add alpha channel
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else:
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bg_color_rgba = None # No background color specified
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output_images = []
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output_masks = []
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@ -1742,7 +1747,7 @@ class LoadAndResizeImage:
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frame = frame.convert("RGBA")
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# Extract alpha channel if it exists
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if 'A' in frame.getbands():
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if 'A' in frame.getbands() and bg_color_rgba:
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alpha_mask = np.array(frame.getchannel('A')).astype(np.float32) / 255.0
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alpha_mask = 1. - torch.from_numpy(alpha_mask)
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bg_image = Image.new("RGBA", frame.size, bg_color_rgba)
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@ -1771,7 +1776,7 @@ class LoadAndResizeImage:
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frame = frame.resize((width, height), Image.Resampling.BILINEAR)
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mask = np.array(frame.getchannel(c)).astype(np.float32) / 255.0
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mask = torch.from_numpy(mask)
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if c == 'A':
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if c == 'A' and bg_color_rgba:
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mask = alpha_mask
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else:
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mask = torch.zeros((64, 64), dtype=torch.float32, device="cpu")
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@ -1793,7 +1798,7 @@ class LoadAndResizeImage:
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@classmethod
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def IS_CHANGED(s, image):
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def IS_CHANGED(s, image, **kwargs):
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image_path = folder_paths.get_annotated_filepath(image)
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m = hashlib.sha256()
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with open(image_path, 'rb') as f:
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