44 lines
1.5 KiB
Python
Executable File
44 lines
1.5 KiB
Python
Executable File
import os
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import torch
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import numpy as np
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from PIL import Image, ImageOps
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import folder_paths
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class EmAySee_LoadImagePlusName:
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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(os.path.join(input_dir, f))]
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return {"required": {"image": (sorted(files), {"image_upload": True})}}
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CATEGORY = "EmAySee"
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RETURN_TYPES = ("IMAGE", "MASK", "STRING")
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RETURN_NAMES = ("image", "mask", "filename_stem")
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FUNCTION = "load_image"
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def load_image(self, image):
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image_path = folder_paths.get_annotated_filepath(image)
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i = Image.open(image_path)
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i = ImageOps.exif_transpose(i)
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image_out = i.convert("RGB")
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image_out = np.array(image_out).astype(np.float32) / 255.0
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image_out = torch.from_numpy(image_out)[None,]
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if 'A' in i.getbands():
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mask = np.array(i.getchannel('A')).astype(np.float32) / 255.0
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mask = 1.0 - mask
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mask = torch.from_numpy(mask)
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else:
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mask = torch.zeros((64,64), dtype=torch.float32, device="cpu")
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filename_stem = os.path.splitext(os.path.basename(image))[0]
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return (image_out, mask.unsqueeze(0), filename_stem)
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NODE_CLASS_MAPPINGS = {
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"EmAySee_LoadImagePlusName": EmAySee_LoadImagePlusName
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"EmAySee_LoadImagePlusName": "EmAySee Load Image + Name"
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} |