61 lines
2.0 KiB
Python
61 lines
2.0 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# Copyright 2025-2026 Raykosan (RaykoStudio)
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import torch
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import numpy as np
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import os
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import folder_paths
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from PIL import Image
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class LoadImageRGBA:
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@classmethod
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def INPUT_TYPES(cls):
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input_dir = folder_paths.get_input_directory()
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files = [f for f in os.listdir(input_dir) if os.path.isfile(os.path.join(input_dir, f))]
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return {
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"required": {
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"image": (sorted(files), {"image_upload": True}),
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}
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}
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RETURN_TYPES = ("IMAGE",)
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RETURN_NAMES = ("rgba",)
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FUNCTION = "load_image"
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CATEGORY = "🦊 RaykoStudio"
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DESCRIPTION = "Loads an image with the alpha channel (RGBA) preserved. Supports PNG, WEBP, TIFF with transparency"
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def load_image(self, image):
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image_path = os.path.join(folder_paths.get_input_directory(), image)
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img = Image.open(image_path)
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if img.mode != 'RGBA':
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img = img.convert('RGBA')
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img_array = np.array(img).astype(np.float32) / 255.0
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tensor = torch.from_numpy(img_array).unsqueeze(0)
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print(f"[rgb2rgba ] Loaded {image}: {img.size}, mode={img.mode}")
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return (tensor,)
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@classmethod
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def IS_CHANGED(cls, image):
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image_path = os.path.join(folder_paths.get_input_directory(), image)
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return os.path.getmtime(image_path)
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NODE_CLASS_MAPPINGS = {"LoadImageRGBA": LoadImageRGBA}
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NODE_DISPLAY_NAME_MAPPINGS = {"LoadImageRGBA": "🦊 RS rgb2rgba"} |