Metadata-Version: 2.4
Name: signwriting
Version: 0.1.2
Summary: Python utilities for SignWriting.
Author-email: Amit Moryossef <amitmoryossef@gmail.com>
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: Pillow
Provides-Extra: dev
Requires-Dist: pytest; extra == "dev"
Requires-Dist: pylint; extra == "dev"
Requires-Dist: numpy; extra == "dev"
Provides-Extra: mouthing
Requires-Dist: epitran; extra == "mouthing"
Requires-Dist: g2pk; extra == "mouthing"
Provides-Extra: server
Requires-Dist: Flask; extra == "server"
Requires-Dist: Flask-RESTful; extra == "server"
Requires-Dist: Flask-Cors; extra == "server"
Requires-Dist: gunicorn; extra == "server"
Dynamic: license-file

# SignWriting

Python utilities for SignWriting.

## Installation

```bash
pip install git+https://github.com/sign-language-processing/signwriting
```

Or with Docker:
```shell
docker build --platform linux/amd64 --tag signwriting:python .
docker run --platform linux/amd64 --rm -p 9090:8080 -e PORT=8080 signwriting:python
```

## Utilities

### `signwriting.formats`

This module provides utilities for converting between different formats of SignWriting.
We include a few examples:

1. To parse an FSW string into a [`Sign`](signwriting/types.py) object, representing the sign as a dictionary:

```python
from signwriting.formats.fsw_to_sign import fsw_to_sign

fsw_to_sign("M123x456S1f720487x492")
# {'box': {'symbol': 'M', 'position': (123, 456)}, 'symbols': [{'symbol': 'S1f720', 'position': (487, 492)}]}
```

2. To convert a SignWriting string in SWU format to FSW format:

```python
from signwriting.formats.swu_to_fsw import swu2fsw

swu2fsw('𝠃𝤟𝤩񋛩𝣵𝤐񀀒𝤇𝣤񋚥𝤐𝤆񀀚𝣮𝣭')
# M525x535S2e748483x510S10011501x466S2e704510x500S10019476x475
```

### `signwriting.tokenizer`

This module provides utilities for tokenizing SignWriting strings for use in NLP tasks[^1].
We include a few usage non-exhaustive examples:

1. To tokenize a SignWriting string into a list of tokens:

```python
from signwriting.tokenizer import SignWritingTokenizer

tokenizer = SignWritingTokenizer()

fsw = 'M123x456S1f720487x492S1f720487x492'
tokens = list(tokenizer.text_to_tokens(fsw, box_position=True))
# ['M', 'p123', 'p456', 'S1f7', 'c2', 'r0', 'p487', 'p492', 'S1f7', 'c2', 'r0', 'p487', 'p492'])
```

2. To convert a list of tokens back to a SignWriting string:

```python
tokenizer.tokens_to_text(tokens)
# M123x456S1f720487x492S1f720487x492
```

3. For machine learning purposes, we can convert the tokens to a list of integers:

```python
tokenizer.tokenize(fsw, bos=False, eos=False)
# [6, 932, 932, 255, 678, 660, 919, 924, 255, 678, 660, 919, 924]
```

4. Or to remove 'A' information, and separate signs by spaces, we can use:

```python
from signwriting.tokenizer import normalize_signwriting

normalize_signwriting(fsw)
```

### `signwriting.visualizer`

This module is used to visualize SignWriting strings as images.
Unlike [sutton-signwriting/font-db](https://github.com/sutton-signwriting/font-db/) which it is based on, this module
does not support custom styling. Benchmarks show that this module is ~5000x faster than the original implementation.

```python
from signwriting.visualizer.visualize import signwriting_to_image

fsw = "AS10011S10019S2e704S2e748M525x535S2e748483x510S10011501x466S20544510x500S10019476x475"
signwriting_to_image(fsw)
```

![AS10011S10019S2e704S2e748M525x535S2e748483x510S10011501x466S20544510x500S10019476x475](signwriting/visualizer/test_assets/AS10011S10019S2e704S2e748M525x535S2e748483x510S10011501x466S20544510x500S10019476x475.png)

To use the visualizer with the server, you can hit:
https://signwriting-sxie2r74ua-uc.a.run.app/visualizer?fsw=M525x535S2e748483x510S10011501x466S2e704510x500S10019476x475

### `signwriting.utils`

This module includes general utilities that were not covered in the other modules.

1. `join_signs` joins a list of signs into a single sign.
   This is useful for example for fingerspelling words out of individual character signs.

```python
from signwriting.utils.join_signs import join_signs_vertical

char_a = 'M507x507S1f720487x492'
char_b = 'M507x507S14720493x485'
result_sign = join_signs_vertical(char_a, char_b)
# M510x518S1f720490x481S14720496x496
```


### `signwriting.fingerspelling`

This module is used to generate spelling data from a list of characters.

```python
from signwriting.fingerspelling.fingerspelling import spell

word = "Hello"  # any string of characters
language = "en-us-ase-asl"  # long language code, as defined in the fingerspelling README
spell(word, language)
# M515x563S11502477x437S14a20492x457S1dc20484x477S1dc20484x512S17620492x547
```

To use the fingerspelling with the server, you can hit:
https://signwriting-sxie2r74ua-uc.a.run.app/fingerspelling?text=hello&signed_language=ase

### `signwriting.mouthing`

This module is used to generate SpeechWriting from spoken words.

```python
from signwriting.mouthing.mouthing import mouth

word = "Hello"  # any string of characters, preferably valid words
language = "eng-Latn"  # supported languages under "Language Support" at https://pypi.org/project/epitran/
mouth(word, language)
# M557x518S34700443x482S35c00469x482S34400495x482S34d00521x482
```

Note: Installing English support for `epitran` requires extra steps, 
see "Install flite" at [mouthing/README.md](signwriting/mouthing/README.md).

To use the mouthing with the server, you can hit:
https://signwriting-sxie2r74ua-uc.a.run.app/mouthing?text=hello&spoken_language=eng-Latn


## Cite

```bibtex
@misc{moryossef2024-signwriting, 
    title={Utilities for SignWriting},
    author={Moryossef, Amit},
    howpublished={\url{https://github.com/sign-language-processing/signwriting}},
    year={2024}
}
```

## References

[^1]: Amit Moryossef, Zifan Jiang.

2023. [SignBank+: Preparing a Multilingual Sign Language Dataset for Machine Translation Using Large Language Models](https://arxiv.org/abs/2309.11566).
