59 lines
1.6 KiB
Python
59 lines
1.6 KiB
Python
import torch
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import numpy as np
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from PIL import Image
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import os
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import folder_paths
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import json
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class MetadataStripper:
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def __init__(self):
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self.output_dir = folder_paths.get_output_directory()
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self.type = "output"
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self.prefix_append = ""
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@classmethod
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def INPUT_TYPES(s):
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return {"required": {
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"image": ("IMAGE",),
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"filename_prefix": ("STRING", {"default": "ComfyUI"}),
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}}
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RETURN_NAMES = ()
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RETURN_TYPES = ()
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FUNCTION = "save"
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OUTPUT_NODE = True
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CATEGORY = "Utilities"
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def save(self, image, filename_prefix="ComfyUI"):
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filename_prefix += self.prefix_append
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full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(
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filename_prefix, self.output_dir, image[0].shape[1], image[0].shape[0]
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)
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results = list()
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for batch_number, img_tensor in enumerate(image):
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i = 255. * img_tensor.cpu().numpy()
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img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
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file = f"{filename}_{counter:05}_.png"
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img.save(os.path.join(full_output_folder, file), compress_level=4)
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results.append({
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"filename": file,
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"subfolder": subfolder,
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"type": self.type
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})
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counter += 1
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return { "ui": { "images": results } }
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NODE_CLASS_MAPPINGS = {
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"MetadataStripper": MetadataStripper,
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"MetadataStripper": "Metadata Stripper (Save)",
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} |