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| import os
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| import numpy as np
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| import torch
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| import folder_paths
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| from nodes import LoadImage
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| from PIL import Image,ImageOps,ImageSequence,ImageDraw,ImageFont
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| from .imagefunc import pil2tensor, log, generate_text_image, get_resource_dir
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| class LoadPSD(LoadImage):
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| @classmethod
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| def INPUT_TYPES(s):
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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(
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| os.path.join(input_dir, f)) and f.endswith(".psd")]
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| fine_layer_method = ["layer_index", "layer_name"]
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| return {"required":{
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| "image": (sorted(files), {"image_upload": True}),
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| "file_path": ("STRING", {"default": ""}),
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| "include_hidden_layer": ("BOOLEAN", {"default": False}),
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| "find_layer_by": (fine_layer_method,),
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| "layer_index": ("INT", {"default": 0, "min": -1, "max": 999, "step": 1}),
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| "layer_name": ("STRING", {"default": ""}),
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| },
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| "optional": {
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| }
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| }
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| RETURN_TYPES = ("IMAGE", "IMAGE", "IMAGE",)
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| RETURN_NAMES = ("flat_image", "layer_image", "all_layers",)
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| FUNCTION = "load_psd"
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| CATEGORY = '😺dzNodes/LayerUtility/SystemIO'
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|
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| def load_psd(self, image, file_path, include_hidden_layer, layer_index, find_layer_by, layer_name,):
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|
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| from psd_tools import PSDImage
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| from psd_tools.api.layers import Layer
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| (LUT_DICT, FONT_DICT) = get_resource_dir()
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|
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| NODE_NAME = 'LoadPSD'
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| number_of_layers = 1
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| layer_image = []
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| all_layers = []
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| if file_path == "":
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| psd_file_path = folder_paths.get_annotated_filepath(image)
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| else:
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| psd_file_path = folder_paths.get_annotated_filepath(file_path)
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| flat_image = Image.open(psd_file_path).convert("RGB")
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| width, height = flat_image.size
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|
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| if image.endswith(".psd"):
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| from psd_tools import PSDImage
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| from psd_tools.api.layers import Layer
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| log(f"{NODE_NAME} -> Loading PSD file: {psd_file_path}")
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| psd_image = PSDImage.open(psd_file_path)
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| layers = []
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| for layer in psd_image:
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| if include_hidden_layer:
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| if not layer.is_visible():
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| layer.visible = True
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| layers.append(layer)
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| else:
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| if layer.is_visible():
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| layers.append(layer)
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|
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| number_of_layers = len(layers)
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| for i in range(number_of_layers):
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| layer_canvas = Image.new("RGBA", (width, height), (0, 0, 0, 0))
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| layer_canvas.paste(layers[i].composite(), layers[i].bbox)
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| all_layers.append(pil2tensor(layer_canvas))
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| if find_layer_by == "layer_name":
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| if layers[i].name == layer_name:
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| layer_image.append(pil2tensor(layer_canvas))
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| log(f"{NODE_NAME} -> Layer {i} : {layer.name} found.")
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| elif find_layer_by == "layer_index":
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| if i == layer_index:
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| layer_image.append(pil2tensor(layer_canvas))
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| log(f"{NODE_NAME} -> Layer {i} : {layer.name} found.")
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|
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| text = "Layer Not Found!"
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| font_file = list(FONT_DICT.values())[0]
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| empty_layer_image = generate_text_image(flat_image.width, flat_image.height, text, font_file, font_color="#F01000")
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| if layer_image == []:
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| if layer_index == -1:
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| layer_image.append(all_layers[-1])
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| elif find_layer_by == "layer_name":
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| log(f'{NODE_NAME} -> Layer "{layer_name}" not found, top layer will be output.', message_type="warning")
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| elif find_layer_by == "layer_index":
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| log(f'{NODE_NAME} -> Layer index {layer_index} not found, top layer will be output.', message_type="warning")
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| layer_image.append(pil2tensor(empty_layer_image))
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| else:
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| layer_image.append(pil2tensor(flat_image))
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| all_layers.append(pil2tensor(flat_image))
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|
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| return (torch.cat([pil2tensor(flat_image),], dim=0), torch.cat(layer_image, dim=0), torch.cat(all_layers, dim=0),)
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| NODE_CLASS_MAPPINGS = {
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| "LayerUtility: LoadPSD": LoadPSD,
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| }
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| NODE_DISPLAY_NAME_MAPPINGS = {
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| "LayerUtility: LoadPSD": "LayerUtility: Load PSD(Advance)",
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| } |
