Metadata-Version: 2.4
Name: DocSafe
Version: 0.1.0
Summary: DocFace: deep-learning-based document/image watermark encoder-decoder with a full training pipeline
Author-email: farhadsh1992 <farhadsh1992@gmail.com>
License: MIT License
        
        Copyright (c) 2026 farhadsh1992
        
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Project-URL: Repository, https://github.com/farhadsh1992/DocSafe
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Image Processing
Requires-Python: <3.13,>=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.25
Requires-Dist: scipy
Requires-Dist: pandas
Requires-Dist: matplotlib
Requires-Dist: torch>=2.0.1
Requires-Dist: torchvision>=0.15.2
Requires-Dist: tensorflow==2.18
Requires-Dist: keras==3.5
Requires-Dist: kornia
Requires-Dist: torcheval
Requires-Dist: torchgeometry
Requires-Dist: opencv-python
Requires-Dist: pillow
Requires-Dist: PyWavelets
Requires-Dist: scikit-image
Requires-Dist: scikit-learn
Requires-Dist: bchlib
Requires-Dist: reedsolo
Requires-Dist: requests
Requires-Dist: pendulum
Requires-Dist: psutil
Requires-Dist: beautifulsoup4
Requires-Dist: dominate
Requires-Dist: seaborn
Requires-Dist: packaging
Requires-Dist: setuptools
Provides-Extra: stylegan2
Requires-Dist: ninja; extra == "stylegan2"
Provides-Extra: detr-extras
Requires-Dist: panopticapi; extra == "detr-extras"
Dynamic: license-file

# DocSafe (DocFace)

Deep-learning-based watermark encoder/decoder for images and documents, with a full
training pipeline (M1/M2/M3 model variants).

## Install

```bash
pip install DocSafe
```

Or from source:

```bash
git clone https://github.com/farhadsh1992/DocSafe.git
cd DocSafe
pip install .
```

## Pretrained weights

Model weights are **not** bundled in the PyPI package (they're hundreds of MB, well past
PyPI's practical size limits). Download `pre_trained_models/` separately and point
`path_model=` at it — see the release/host you're distributing weights from.

## Quickstart: encode / decode a watermark

```python
from DocSafe import encoder, decoder

encoder_router = encoder(model="M1", path_model="pre_trained_models/", secret_size=100)
encoder_router.load_network(device="cpu")

images = encoder_router.read_image(path=["test_images/original_images.jpg"])
image_batch = encoder_router.preprocess_images(images)
encoded = encoder_router(original_images=image_batch, messages="viste", mask=None)
encoder_router.save_encoded_image("encoded.png")

decoder_router = decoder(model="M1", path_model="pre_trained_models/", secret_size=100)
decoder_router.load_network(device="cpu")

encoded_images = decoder_router.read_image(path=["encoded.png"])
encoded_batch = decoder_router.preprocess_images(encoded_images)
messages = decoder_router(encoded_images=encoded_batch, mask=None)
print(messages)
```

See `test_main.py` for a complete runnable example.

## Training

`train_main.py` shows the intended `DocSafe.Trainer` API. Two things to know before running it:

- `configs/paths_config.py` hardcodes paths from the original training machine
  (`pretrained_models/...`, dataset directories) — edit it for your own environment.
- `Trainer.train()` and `Trainer.load_network()` are still under active development
  (see the inline `NOTE:` comments in `train_main.py`).

## Known limitations

- `DocSafe.loss_functions_lib.models.stylegan2` (and everything that depends on it —
  `hyperstyle`, `psp`, `e4e`, `restyle_e4e_encoders`, `w_encoder`, the hypernetworks) JIT-compiles
  CUDA/C++ extensions on import via `torch.utils.cpp_extension.load()`. It requires an actual
  CUDA GPU + `nvcc` + `ninja` (`pip install DocSafe[stylegan2]`) and will not import on
  CPU-only machines.
- `DocSafe.networks.net_StampOne` is superseded/legacy — it isn't used by `encoder`/`decoder`/
  `Trainer` (which all use `DocSafe.networks.networks_M1/M2/M3`) and has an unresolved
  `Deformable_Conv2D` dependency in one file.
- `DocSafe.networks.DETR_NET.segmentation`'s panoptic-segmentation helpers need
  `pip install DocSafe[detr-extras]`.

## License

MIT — see `LICENSE`.