Watermark-Detection-SigLIP2：Detecting Digital Watermarks with AI

🧠 What is Watermark-Detection-SigLIP2?

Watermark-Detection-SigLIP2 is a vision-language encoder model fine-tuned from Google’s SigLIP2-base-patch16-224, specifically developed for binary image classification. Its primary function is to determine whether an image contains a watermark, using the SiglipForImageClassification architecture for training and inference.

🔧 Key Features

• Binary Classification: The model classifies images into two categories:

  • Class 0: No Watermark

  • Class 1: Watermark

• High Accuracy: Achieves an overall accuracy of 94.27% on the test dataset, with strong precision and recall scores.

• Optimized for High-Quality Images: Performs best with clear, high-resolution images; noisy images are not recommended for validation.

• Easy Integration: Inference code is provided using Python libraries such as Transformers, Torch, Pillow, and Gradio, making it easy to integrate into various applications.

⚙️ Technical Principles

• Model Architecture: Based on the SiglipForImageClassification architecture, fine-tuned specifically for watermark detection.

• Training Dataset: Trained on the qwertyforce/scenery_watermarks dataset, which contains images labeled with the presence or absence of watermarks.

• Performance Metrics:

  • Precision:

    • No Watermark: 92.90%

    • Watermark: 96.22%

  • Recall:

    • No Watermark: 97.22%

    • Watermark: 90.48%

  • F1 Score:

    • No Watermark: 95.01%

    • Watermark: 93.26%

  • Overall Accuracy: 94.27%

• Model Size: Approximately 92.9 million parameters.

📍 Project Repository

• Hugging Face Model Page:
  https://huggingface.co/prithivMLmods/Watermark-Detection-SigLIP2

🚀 Application Scenarios

• Content Moderation: Automatically detect and flag watermarked images to improve moderation on image-sharing platforms.

• Dataset Cleaning: Filter out watermarked images from training datasets to improve data quality and model performance.

• Copyright Protection: Monitor and detect unauthorized use of watermarked content, aiding in intellectual property enforcement.

• Digital Forensics: Assist in identifying altered or protected media in support of legal and investigative processes.