Skip to content

tgenlis83/dnn-watermark

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

84 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Watermarking Detection - DNN

Authors

  • Bastien Pouëssel
  • Arnaud Baradat
  • Nicolas Fidel
  • Tom Genlis
  • Théo Ripoll
  • Quentin Fisch

PITA Dataset creation

The characteristics of the dataset we generated are the following:

  1. Single watermarked images
  2. Aligned bounding boxes (center, width, height)
  3. 512x512 images
  4. Base images from coco (all classes)
  5. Logos from this dataset: https://hangsu0730.github.io/qmul-openlogo/

The dataset contains subdatasets for:

  • Text watermarks
  • Logo watermarks

We worked on multiple properties of the watermarks:

  • Color
  • Size
  • Position
  • Opacity
  • Font

There two supported formats for the dataset:

  • COCO
  • YOLO (Ultralytics)

Everything related to the PITA dataset is located in the pita_tool folder. We created a CLI tool to generate and download the dataset. You can find help about the CLI tool by simply running the following command:

python pita_tool/pita.py

The dataset is hosted on Hugging Face and is available at the following link: https://huggingface.co/datasets/bastienp/visible-watermark-pita

Model

The following models have been fine-tuned on our dataset, and tested on CLWD dataset (https://drive.google.com/file/d/17y1gkUhIV6rZJg1gMG-gzVMnH27fm4Ij/view)

  • YoloV8 Nano
  • YoloV8 Large
  • DETR w/ ResNet backbone
  • Faster R-CNN

PITA fine-tuned YoloV8 Nano model is available on Hugging Face too at: https://huggingface.co/qfisch/yolov8n-watermark-detection

Results

You can find the results and the paper explaining our work in the report folder. A demo using our fine-tuned YoloV8 Nano model is available on a Hugging Face Space here: https://huggingface.co/spaces/qfisch/watermark-detection

Note: We were enable to correctly benchmark DETR, thus we decided to not include any result for this model.

Weights & Biases

About

Visible Watermark Dataset Research Project

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages