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Don't fill the alpha by default

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kijai 2024-08-22 00:47:31 +03:00
parent d7f91f2c65
commit 1bfdb8a1a2
1 changed files with 20 additions and 15 deletions
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35
nodes/image_nodes.py
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@ -1677,7 +1677,7 @@ class LoadAndResizeImage:
"keep_proportion": ("BOOLEAN", { "default": False }), "keep_proportion": ("BOOLEAN", { "default": False }),
"divisible_by": ("INT", { "default": 2, "min": 0, "max": 512, "step": 1, }), "divisible_by": ("INT", { "default": 2, "min": 0, "max": 512, "step": 1, }),
"mask_channel": (s._color_channels, {"tooltip": "Channel to use for the mask output"}), "mask_channel": (s._color_channels, {"tooltip": "Channel to use for the mask output"}),
"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."}), "background_color": ("STRING", { "default": "", "tooltip": "Fills the alpha channel with the specified color."}),
}, },
} }
@ -1687,24 +1687,29 @@ class LoadAndResizeImage:
FUNCTION = "load_image" FUNCTION = "load_image"
def load_image(self, image, resize, width, height, repeat, keep_proportion, divisible_by, mask_channel, background_color): def load_image(self, image, resize, width, height, repeat, keep_proportion, divisible_by, mask_channel, background_color):
from PIL import ImageColor from PIL import ImageColor, Image, ImageOps, ImageSequence
import numpy as np
import torch
image_path = folder_paths.get_annotated_filepath(image) image_path = folder_paths.get_annotated_filepath(image)
import node_helpers import node_helpers
img = node_helpers.pillow(Image.open, image_path) img = node_helpers.pillow(Image.open, image_path)
# Process the background_color # Process the background_color
try: if background_color:
# Try to parse as RGB tuple try:
bg_color_rgba = tuple(int(x.strip()) for x in background_color.split(',')) # Try to parse as RGB tuple
except ValueError: bg_color_rgba = tuple(int(x.strip()) for x in background_color.split(','))
# If parsing fails, it might be a hex color or named color except ValueError:
if background_color.startswith('#') or background_color.lower() in ImageColor.colormap: # If parsing fails, it might be a hex color or named color
bg_color_rgba = ImageColor.getrgb(background_color) if background_color.startswith('#') or background_color.lower() in ImageColor.colormap:
else: bg_color_rgba = ImageColor.getrgb(background_color)
raise ValueError(f"Invalid background color: {background_color}") else:
raise ValueError(f"Invalid background color: {background_color}")
bg_color_rgba += (255,) # Add alpha channel bg_color_rgba += (255,) # Add alpha channel
else:
bg_color_rgba = None # No background color specified
output_images = [] output_images = []
output_masks = [] output_masks = []
@ -1742,7 +1747,7 @@ class LoadAndResizeImage:
frame = frame.convert("RGBA") frame = frame.convert("RGBA")
# Extract alpha channel if it exists # Extract alpha channel if it exists
if 'A' in frame.getbands(): if 'A' in frame.getbands() and bg_color_rgba:
alpha_mask = np.array(frame.getchannel('A')).astype(np.float32) / 255.0 alpha_mask = np.array(frame.getchannel('A')).astype(np.float32) / 255.0
alpha_mask = 1. - torch.from_numpy(alpha_mask) alpha_mask = 1. - torch.from_numpy(alpha_mask)
bg_image = Image.new("RGBA", frame.size, bg_color_rgba) bg_image = Image.new("RGBA", frame.size, bg_color_rgba)
@ -1771,7 +1776,7 @@ class LoadAndResizeImage:
frame = frame.resize((width, height), Image.Resampling.BILINEAR) frame = frame.resize((width, height), Image.Resampling.BILINEAR)
mask = np.array(frame.getchannel(c)).astype(np.float32) / 255.0 mask = np.array(frame.getchannel(c)).astype(np.float32) / 255.0
mask = torch.from_numpy(mask) mask = torch.from_numpy(mask)
if c == 'A': if c == 'A' and bg_color_rgba:
mask = alpha_mask mask = alpha_mask
else: else:
mask = torch.zeros((64, 64), dtype=torch.float32, device="cpu") mask = torch.zeros((64, 64), dtype=torch.float32, device="cpu")
@ -1793,7 +1798,7 @@ class LoadAndResizeImage:
@classmethod @classmethod
def IS_CHANGED(s, image): def IS_CHANGED(s, image, **kwargs):
image_path = folder_paths.get_annotated_filepath(image) image_path = folder_paths.get_annotated_filepath(image)
m = hashlib.sha256() m = hashlib.sha256()
with open(image_path, 'rb') as f: with open(image_path, 'rb') as f: