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RobinKaRobinKa
committedApr 24, 2020
initial
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v0.0.3v0.0.1
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‎.gitignore

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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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# C extensions
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*.so
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# Distribution / packaging
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.Python
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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pip-wheel-metadata/
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share/python-wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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MANIFEST
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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*.spec
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# Installer logs
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pip-log.txt
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pip-delete-this-directory.txt
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# Unit test / coverage reports
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htmlcov/
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.tox/
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.nox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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*.py,cover
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.hypothesis/
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.pytest_cache/
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cover/
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# Translations
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*.mo
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*.pot
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# Django stuff:
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*.log
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local_settings.py
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db.sqlite3
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db.sqlite3-journal
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# Flask stuff:
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instance/
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.webassets-cache
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# Scrapy stuff:
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.scrapy
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# Sphinx documentation
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docs/_build/
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# PyBuilder
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.pybuilder/
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target/
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# Jupyter Notebook
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.ipynb_checkpoints
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# IPython
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profile_default/
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ipython_config.py
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# pyenv
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# For a library or package, you might want to ignore these files since the code is
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# intended to run in multiple environments; otherwise, check them in:
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# .python-version
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# pipenv
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# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
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# However, in case of collaboration, if having platform-specific dependencies or dependencies
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# having no cross-platform support, pipenv may install dependencies that don't work, or not
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# install all needed dependencies.
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#Pipfile.lock
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# PEP 582; used by e.g. github.com/David-OConnor/pyflow
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__pypackages__/
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# Celery stuff
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celerybeat-schedule
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celerybeat.pid
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# SageMath parsed files
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*.sage.py
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# Environments
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.env
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.venv
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env/
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venv/
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ENV/
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env.bak/
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venv.bak/
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# Spyder project settings
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.spyderproject
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.spyproject
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# Rope project settings
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.ropeproject
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# mkdocs documentation
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/site
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# mypy
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.mypy_cache/
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.dmypy.json
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dmypy.json
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# Pyre type checker
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.pyre/
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# pytype static type analyzer
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.pytype/
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# Cython debug symbols
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cython_debug/
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# static files generated from Django application using `collectstatic`
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media
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static

‎README.md

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# Chinese Overlay
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Detects Chinese text and displays an overlay with the corresponding pinyin, phrase translations and optionally a Google translation. Works on videos and anything else that can be visually captured from the screen.
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![](screenshots/douyu.jpg)
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## Usage
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Prebuilt packages are made available for Windows that can be downloaded from the [Releases](/releases) page. Windows 10 1709 and a DirectX 12 compatible GPU will be required to use the DirectML provider (basically a neural network runtime that leverages DirectX12 to run the OCR on all modern GPUs). Alternatively, the much slower CPU backend can be used or any of the other onnxruntime execution providers (eg. CUDA).
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To launch the overlay open any of the .bat files (eg. `overlay-pinyin.bat` or `overlay-google-trans.bat`). By default the overlay can toggled using the `F8` key. The translation overlay will be shown within the displayed window, which can also be resized to fit
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whatever region you want to translated. By default only the pinyin is shown which is obtained from a dictionary.
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The overlay can also be started by executing the program from the command line with the `ui` subcommand ´(`cli.exe ui`) which opens up more options that can be found by typing `cli.exe --help` and `cli.exe ui --help`.
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## Running in Python instead of using prepackaged version
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The [requirements file](/requirements.txt) contains all the necessary requirements and some optional ones. However to use the DirectML interface a modified version is required with [this](https://github.com/microsoft/onnxruntime/pull/3359) PR and [this](https://github.com/microsoft/onnxruntime/issues/3360) fix to make it work with the default Windows DirectML library). The program should work on non-Windows systems but it has not been tested much.
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## Running a translation server
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The project also contains an http server that can run OCR on received images and return the results. It can be started by specifying the `server` argument. This makes it possible to easily make frontends in other languages
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or to use the OCR for any other purpose.

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