| --- |
| 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](https://github.com/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** |
|
|
| ```python |
| 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: |
|
|
| ```bibtex |
| @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} |
| } |
| ``` |
|
|
|
|
