Watermark Detection SigLIP2 Watermark Detection SigLIP2 is a vision language encoder model fine tuned from google/siglip2 base patch16 224 for binary image classification . It is trained to detect whether an image contains a watermark or not , using the SiglipForImageClassification architecture. [!note] Watermark detection works best with crisp and high quality images. Noisy images are not recommended for validation. [!note] SigLIP 2: Multilingual Vision Language Encoders with Improved Semantic Understanding, Localization, and Dense Features https://arxiv.org/pdf/2502.14786 Label Space: 2 Classes The model classifies an image as either: Install dependencies Inference Code Demo Inference [!Warning] Watermark [!Warning] No Watermark Intended Use Watermark Detection SigLIP2 is useful in scenarios such as: Content Moderation – Automatically detect watermarked content on image sharing platforms. Dataset Cleaning – Filter out watermarked images from training datasets. Copyright Enforcement – Monitor and flag usage of watermarked media. Digital Forensics – Support analysis of tampered or protected media assets.
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