---
license: apache-2.0
datasets:
- qwertyforce/scenery_watermarks
language:
- en
base_model:
- google/siglip2-base-patch16-224
pipeline_tag: image-classification
library_name: transformers
tags:
- Image-Classification
- Watermark-Detection
- SigLIP2
---

# **Watermark-Detection-SigLIP2**

![5.png](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/VXSOLkmcLM1t6XhTcYXUh.png)

**Watermark-Detection-SigLIP2** is a vision-language encoder model fine-tuned from **google/siglip2-base-patch16-224** for **binary image classification**.  
It detects whether an image **contains a watermark or not**, using the `SiglipForImageClassification` architecture.

> ⚠️ Note: Watermark detection works best with high-quality, crisp images. Avoid noisy inputs.

> 📄 Paper: *SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features*  
> https://arxiv.org/pdf/2502.14786

---

## 📊 Classification Report

```text
              precision    recall  f1-score   support

No Watermark     0.9290    0.9722    0.9501     12779
   Watermark     0.9622    0.9048    0.9326      9983

    accuracy                         0.9427     22762
   macro avg     0.9456    0.9385    0.9414     22762
weighted avg     0.9435    0.9427    0.9424     22762