Data Save Image Pro Added
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import os
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import json
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import numpy as np
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from PIL import Image
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from PIL.PngImagePlugin import PngInfo
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from comfy.cli_args import args
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def save_images_with_metadata(image_tensors, names, destination, img_format='png', quality=95, disable_metadata=True, extra_pnginfo=None, prompt=None, compression=4):
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if not os.path.exists(destination):
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os.makedirs(destination)
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for i, tensor in enumerate(image_tensors):
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image = tensor.cpu().numpy()
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if image.ndim == 4:
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image = image[0]
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if image.ndim == 3 and image.shape[0] == 1:
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image = image[0]
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image = (image * 255).astype(np.uint8)
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img = Image.fromarray(image)
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metadata = None
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if not disable_metadata and img_format.lower() == 'png':
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metadata = PngInfo()
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if prompt is not None:
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metadata.add_text("prompt", json.dumps(prompt))
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if extra_pnginfo is not None and isinstance(extra_pnginfo, dict):
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for key, value in extra_pnginfo.items():
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metadata.add_text(key, json.dumps(value))
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img_name = f"{names[i]}.{img_format}"
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img_path = os.path.join(destination, img_name)
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if img_format.lower() in ['jpeg', 'jpg']:
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img.save(img_path, format='jpeg', quality=quality)
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elif img_format.lower() == 'png':
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img.save(img_path, pnginfo=metadata, compress_level=compression)
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else:
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img.save(img_path, format=img_format.upper())
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class DataSet_SaveImagePro:
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def __init__(self):
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self.compression = 4
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"images": ("IMAGE",),
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"names": ("STRING",),
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"destination": ("STRING", {}),
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"image_format": (['png', 'jpg'],),
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"image_quality": ("INT", {"default": 100, "min": 1, "max": 100}),
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},
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"hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
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}
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INPUT_IS_LIST = True
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RETURN_TYPES = ()
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FUNCTION = "BatchSave"
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OUTPUT_NODE = True
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CATEGORY = "🔶DATASET🔶"
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def BatchSave(self, images, names, destination, image_format, image_quality, prompt=None, extra_pnginfo=None):
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try:
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save_images_with_metadata(images,names,destination[0],image_format[0],image_quality[0],False,extra_pnginfo,prompt,self.compression)
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except Exception as e:
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print(f"Error saving image: {e}")
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return ()
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N_CLASS_MAPPINGS = {
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"DataSet_SaveImagePro": DataSet_SaveImagePro,
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}
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N_DISPLAY_NAME_MAPPINGS = {
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"DataSet_SaveImagePro": "DataSet_SaveImagePro",
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}
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