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image_watermark_filter

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图像水印过滤器。过滤器以保持其图像没有水印的样本具有高概率。 本SKILL使用依赖data_juicer,请在调用前安装好python环境并安装data_juicer,你可用以下指令进行安装: pip install py-data-juicer 当用户提到图像水印检测、图片无水印过滤、水印去除、检测图片水印等需求时使用此skill。

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Source SKILL.md: https://github.com/cas-bigdatalab/piflow/blob/HEAD/workspace/skills/image_watermark_filter/SKILL.md

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功能概述

该算子使用水印检测模型判断图像是否包含水印,过滤掉水印概率超过阈值的图像,保留无水印的样本。支持多种过滤策略:

  • any: 任意一张图像符合条件即保留
  • all: 所有图像都符合条件才保留

核心参数

参数类型必填默认值说明
input_pathstring是-输入数据文件路径 (JSON/JSONL格式)
output_pathstring是-输出数据文件路径 (JSONL格式)
hf_watermark_modelstring否'amrul-hzz/watermark_detector'HuggingFace上的水印检测模型
prob_thresholdfloat否0.8水印概率阈值(0-1之间,低于此值保留)
any_or_allstring否'any'过滤策略:'any' 或 'all'
num_procint否1并行处理的进程数

输入数据格式

输入文件应为 JSON 或 JSONL 格式,每行包含一个样本,样本需包含 images 字段:

{"images": ["/path/to/image1.jpg", "/path/to/image2.jpg"]}

输出数据格式

输出为 JSONL 格式,每行一个符合条件的样本。

使用示例

命令行调用

python scripts/run_image_watermark_filter.py \
  --input_path /path/to/input.jsonl \
  --output_path /path/to/output.jsonl \
  --prob_threshold 0.8 \
  --any_or_all any

参数说明

  • --input_path: 输入文件路径
  • --output_path: 输出文件路径
  • --hf_watermark_model: 水印检测模型(默认:amrul-hzz/watermark_detector)
  • --prob_threshold: 水印概率阈值(默认0.8,值越低越严格)
  • --any_or_all: 过滤策略,默认any
  • --num_proc: 并行进程数,默认1

注意事项

  1. 输入文件中的图像路径应为有效且可访问的文件路径
  2. 该算子需要加载HuggingFace水印检测模型,首次运行会下载模型
  3. 依赖 torch,请确保已安装
  4. 处理大量数据时可适当增加 num_proc 提高效率