metadata
tags:
- model_hub_mixin
- pytorch_model_hub_mixin
- watermarking
- latent-diffusion
- stable-signature
- watermark-extraction
- computer-vision
- research
- non-commercial
- pytorch
license: cc-by-nc-4.0
MsgExtractor - Stable Signature Decoder
A version of the Stable Signature decoder from the Meta AI project “Stable Signature: Rooting Watermarks in Latent Diffusion Models.”
Model Summary
Model Type: Custom PyTorch Model
Task: Watermark extraction from watermarked images
Source: Derived from facebookresearch/stable_signature
License: CC-BY-NC 4.0 (Attribution + Non-Commercial)
Framework: PyTorch
Weights: Ported from the original TorchScript decoder
Architecture:
HiddenDecoder(num_blocks, num_bits, channels, redundancy)MsgExtractor(hidden_decoder, in_features, out_features)
Status: Research-only, non-commercial
Load the model
from modeling_msg_extractor import MsgExtractor
import torch
model = MsgExtractor.from_pretrained("ESmike/StableSignatureDecoder")
model.eval()
img = torch.randn(1, 3, 256, 256) # example input
bits = model(img)
print(bits.shape)
Citation
If you use this model, you must cite the original Stable Signature paper:
@inproceedings{Fernandez2023StableSignature,
title={The Stable Signature Rooting Watermarks in Latent Diffusion Models},
author={Fernandez, Pierre and Chappelier, Vivien and Nguyen-Hong, Son},
year={2023},
institution={Meta AI},
note={Original implementation at https://github.com/facebookresearch/stable_signature}
}