65 lines
1.8 KiB
Python
65 lines
1.8 KiB
Python
from PIL import Image
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import torch
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import numpy as np
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import io
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from .core import generate_watermark
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import os
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class InvisibleWatermarkEncode:
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"images": ("IMAGE",),
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"watermark": ("STRING", {
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"multiline": False,
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"default": "Hello World!"
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}),
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},
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}
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RETURN_TYPES = ("IMAGE",)
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OUTPUT_IS_LIST = (True, )
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FUNCTION = "encode"
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CATEGORY = "WATERMARK"
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def encode(self, images, watermark):
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results = []
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for image in images:
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i = 255. * image.cpu().numpy()
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image_pil = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
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image_pil = image_pil.resize((512, 512))
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image_np_array = np.array(image_pil)
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current_file_path = os.path.abspath(__file__)
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font_path = os.path.join(os.path.dirname(current_file_path), "font/ZiTiQuanWeiJunHei-W1-2.ttf")
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result_image_pil = generate_watermark(
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image_np_array, watermark,
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font=font_path
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)
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result_image_pil = result_image_pil.convert("RGB")
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result_image_np = np.array(result_image_pil).astype(np.float32) / 255.0
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result_image_tensor = torch.from_numpy(result_image_np)[None,]
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results.append(result_image_tensor)
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return (results, )
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# A dictionary that contains all nodes you want to export with their names
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# NOTE: names should be globally unique
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NODE_CLASS_MAPPINGS = {
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"InvisibleWatermarkEncode": InvisibleWatermarkEncode,
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}
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# A dictionary that contains the friendly/humanly readable titles for the nodes
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NODE_DISPLAY_NAME_MAPPINGS = {
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"InvisibleWatermarkEncode": "Invisible Watermark Encode",
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}
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