├── .github └── workflows │ ├── codeql.yml │ ├── pylint.yml │ └── python-publish.yml ├── .gitignore ├── LICENSE ├── README.md ├── setup.py └── subtitle_ai_translator ├── __init__.py └── main.py /.github/workflows/codeql.yml: -------------------------------------------------------------------------------- 1 | # For most projects, this workflow file will not need changing; you simply need 2 | # to commit it to your repository. 3 | # 4 | # You may wish to alter this file to override the set of languages analyzed, 5 | # or to provide custom queries or build logic. 6 | # 7 | # ******** NOTE ******** 8 | # We have attempted to detect the languages in your repository. Please check 9 | # the `language` matrix defined below to confirm you have the correct set of 10 | # supported CodeQL languages. 11 | # 12 | name: "CodeQL" 13 | 14 | on: 15 | push: 16 | branches: [ "main" ] 17 | pull_request: 18 | # The branches below must be a subset of the branches above 19 | branches: [ "main" ] 20 | schedule: 21 | - cron: '18 6 * * 2' 22 | 23 | jobs: 24 | analyze: 25 | name: Analyze 26 | # Runner size impacts CodeQL analysis time. To learn more, please see: 27 | # - https://gh.io/recommended-hardware-resources-for-running-codeql 28 | # - https://gh.io/supported-runners-and-hardware-resources 29 | # - https://gh.io/using-larger-runners 30 | # Consider using larger runners for possible analysis time improvements. 31 | runs-on: ${{ (matrix.language == 'swift' && 'macos-latest') || 'ubuntu-latest' }} 32 | timeout-minutes: ${{ (matrix.language == 'swift' && 120) || 360 }} 33 | permissions: 34 | actions: read 35 | contents: read 36 | security-events: write 37 | 38 | strategy: 39 | fail-fast: false 40 | matrix: 41 | language: [ 'python' ] 42 | # CodeQL supports [ 'c-cpp', 'csharp', 'go', 'java-kotlin', 'javascript-typescript', 'python', 'ruby', 'swift' ] 43 | # Use only 'java-kotlin' to analyze code written in Java, Kotlin or both 44 | # Use only 'javascript-typescript' to analyze code written in JavaScript, TypeScript or both 45 | # Learn more about CodeQL language support at https://aka.ms/codeql-docs/language-support 46 | 47 | steps: 48 | - name: Checkout repository 49 | uses: actions/checkout@v3 50 | 51 | # Initializes the CodeQL tools for scanning. 52 | - name: Initialize CodeQL 53 | uses: github/codeql-action/init@v2 54 | with: 55 | languages: ${{ matrix.language }} 56 | # If you wish to specify custom queries, you can do so here or in a config file. 57 | # By default, queries listed here will override any specified in a config file. 58 | # Prefix the list here with "+" to use these queries and those in the config file. 59 | 60 | # For more details on CodeQL's query packs, refer to: https://docs.github.com/en/code-security/code-scanning/automatically-scanning-your-code-for-vulnerabilities-and-errors/configuring-code-scanning#using-queries-in-ql-packs 61 | # queries: security-extended,security-and-quality 62 | 63 | 64 | # Autobuild attempts to build any compiled languages (C/C++, C#, Go, Java, or Swift). 65 | # If this step fails, then you should remove it and run the build manually (see below) 66 | - name: Autobuild 67 | uses: github/codeql-action/autobuild@v2 68 | 69 | # ℹ️ Command-line programs to run using the OS shell. 70 | # 📚 See https://docs.github.com/en/actions/using-workflows/workflow-syntax-for-github-actions#jobsjob_idstepsrun 71 | 72 | # If the Autobuild fails above, remove it and uncomment the following three lines. 73 | # modify them (or add more) to build your code if your project, please refer to the EXAMPLE below for guidance. 74 | 75 | # - run: | 76 | # echo "Run, Build Application using script" 77 | # ./location_of_script_within_repo/buildscript.sh 78 | 79 | - name: Perform CodeQL Analysis 80 | uses: github/codeql-action/analyze@v2 81 | with: 82 | category: "/language:${{matrix.language}}" 83 | -------------------------------------------------------------------------------- /.github/workflows/pylint.yml: -------------------------------------------------------------------------------- 1 | name: Pylint 2 | 3 | on: [push] 4 | 5 | jobs: 6 | build: 7 | runs-on: ubuntu-latest 8 | strategy: 9 | matrix: 10 | python-version: ["3.8", "3.9", "3.10"] 11 | steps: 12 | - uses: actions/checkout@v3 13 | - name: Set up Python ${{ matrix.python-version }} 14 | uses: actions/setup-python@v3 15 | with: 16 | python-version: ${{ matrix.python-version }} 17 | - name: Install dependencies 18 | run: | 19 | python -m pip install --upgrade pip 20 | pip install . 21 | pip install pylint 22 | - name: Analysing the code with pylint 23 | run: | 24 | pylint $(git ls-files '*.py') 25 | -------------------------------------------------------------------------------- /.github/workflows/python-publish.yml: -------------------------------------------------------------------------------- 1 | # This workflow will upload a Python Package using Twine when a release is created 2 | # For more information see: https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-python#publishing-to-package-registries 3 | 4 | # This workflow uses actions that are not certified by GitHub. 5 | # They are provided by a third-party and are governed by 6 | # separate terms of service, privacy policy, and support 7 | # documentation. 8 | 9 | name: Upload Python Package 10 | 11 | on: 12 | release: 13 | types: [published] 14 | 15 | permissions: 16 | contents: read 17 | 18 | jobs: 19 | deploy: 20 | 21 | runs-on: ubuntu-latest 22 | 23 | steps: 24 | - uses: actions/checkout@v3 25 | - name: Set up Python 26 | uses: actions/setup-python@v3 27 | with: 28 | python-version: '3.x' 29 | - name: Install dependencies 30 | run: | 31 | python -m pip install --upgrade pip 32 | pip install build 33 | - name: Build package 34 | run: python -m build 35 | - name: Publish package 36 | uses: pypa/gh-action-pypi-publish@27b31702a0e7fc50959f5ad993c78deac1bdfc29 37 | with: 38 | user: __token__ 39 | password: ${{ secrets.PYPI_API_TOKEN }} 40 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | share/python-wheels/ 24 | *.egg-info/ 25 | .installed.cfg 26 | *.egg 27 | MANIFEST 28 | 29 | # PyInstaller 30 | # Usually these files are written by a python script from a template 31 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 32 | *.manifest 33 | *.spec 34 | 35 | # Installer logs 36 | pip-log.txt 37 | pip-delete-this-directory.txt 38 | 39 | # Unit test / coverage reports 40 | htmlcov/ 41 | .tox/ 42 | .nox/ 43 | .coverage 44 | .coverage.* 45 | .cache 46 | nosetests.xml 47 | coverage.xml 48 | *.cover 49 | *.py,cover 50 | .hypothesis/ 51 | .pytest_cache/ 52 | cover/ 53 | 54 | # Translations 55 | *.mo 56 | *.pot 57 | 58 | # Django stuff: 59 | *.log 60 | local_settings.py 61 | db.sqlite3 62 | db.sqlite3-journal 63 | 64 | # Flask stuff: 65 | instance/ 66 | .webassets-cache 67 | 68 | # Scrapy stuff: 69 | .scrapy 70 | 71 | # Sphinx documentation 72 | docs/_build/ 73 | 74 | # PyBuilder 75 | .pybuilder/ 76 | target/ 77 | 78 | # Jupyter Notebook 79 | .ipynb_checkpoints 80 | 81 | # IPython 82 | profile_default/ 83 | ipython_config.py 84 | 85 | # pyenv 86 | # For a library or package, you might want to ignore these files since the code is 87 | # intended to run in multiple environments; otherwise, check them in: 88 | # .python-version 89 | 90 | # pipenv 91 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 92 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 93 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 94 | # install all needed dependencies. 95 | #Pipfile.lock 96 | 97 | # poetry 98 | # Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. 99 | # This is especially recommended for binary packages to ensure reproducibility, and is more 100 | # commonly ignored for libraries. 101 | # https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control 102 | #poetry.lock 103 | 104 | # pdm 105 | # Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. 106 | #pdm.lock 107 | # pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it 108 | # in version control. 109 | # https://pdm.fming.dev/#use-with-ide 110 | .pdm.toml 111 | 112 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm 113 | __pypackages__/ 114 | 115 | # Celery stuff 116 | celerybeat-schedule 117 | celerybeat.pid 118 | 119 | # SageMath parsed files 120 | *.sage.py 121 | 122 | # Environments 123 | .env 124 | .venv 125 | env/ 126 | venv/ 127 | ENV/ 128 | env.bak/ 129 | venv.bak/ 130 | 131 | # Spyder project settings 132 | .spyderproject 133 | .spyproject 134 | 135 | # Rope project settings 136 | .ropeproject 137 | 138 | # mkdocs documentation 139 | /site 140 | 141 | # mypy 142 | .mypy_cache/ 143 | .dmypy.json 144 | dmypy.json 145 | 146 | # Pyre type checker 147 | .pyre/ 148 | 149 | # pytype static type analyzer 150 | .pytype/ 151 | 152 | # Cython debug symbols 153 | cython_debug/ 154 | 155 | # PyCharm 156 | # JetBrains specific template is maintained in a separate JetBrains.gitignore that can 157 | # be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore 158 | # and can be added to the global gitignore or merged into this file. 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If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | 2 | # Subtitle-AI-Translator 3 | 4 | Subtitle-AI-Translator is an AI-powered application designed to automatically translate video subtitles, making content accessible across different languages and cultures. This tool leverages advanced machine learning models to provide accurate and context-aware translations, ensuring that your video content is enjoyed by a broader audience without language barriers. 5 | 6 | ## Features 7 | 8 | - **Automated Translation**: Quickly translate subtitles from one language to another with support for multiple languages. 9 | - **AI Integration**: Utilizes state-of-the-art AI translation models for high-quality subtitle translation. 10 | - **Customizable**: Easy to tailor the translation process to fit specific needs or preferences. 11 | - **Batch Processing**: Translate entire subtitle files in one go, saving time and effort. 12 | - **User-Friendly**: Designed with simplicity in mind, making it accessible for both technical and non-technical users. 13 | 14 | ## Installation 15 | 16 | There are two main methods to install Subtitle-AI-Translator: using pip, or installing from source. Below are the instructions for both methods. 17 | 18 | ### Installing with pip 19 | 20 | To install Subtitle-AI-Translator using pip, simply run the following command in your terminal: 21 | 22 | ``` 23 | pip install subtitle-ai-translator 24 | ``` 25 | 26 | This will download and install the latest version of Subtitle-AI-Translator along with its dependencies. 27 | 28 | ### Installing from Source 29 | 30 | If you prefer to install from the source, you can clone the repository and install it manually: 31 | 32 | ``` 33 | git clone https://github.com/sutasrof/Subtitle-AI-Translator.git 34 | cd Subtitle-AI-Translator 35 | pip install . 36 | ``` 37 | 38 | This sequence of commands will clone the repository to your local machine, navigate into the project directory, and install the package along with its required dependencies. 39 | 40 | ## Usage 41 | 42 | After installation, you can use Subtitle-AI-Translator from the command line. Here is a basic example of how to use the tool to translate a subtitle file: 43 | 44 | ``` 45 | subtitle_ai_translator source.vtt destination.vtt target_language_code 46 | ``` 47 | 48 | Replace `source.vtt` with the path to your original subtitle file, `destination.vtt` with the path where you want the translated file to be saved, and `target_language_code` with the desired language code (e.g., `en` for English, `es` for Spanish, etc.). 49 | -------------------------------------------------------------------------------- /setup.py: -------------------------------------------------------------------------------- 1 | """ 2 | Setup script for the Subtitle-AI-Translator package. 3 | 4 | This script uses setuptools to package the Subtitle-AI-Translator project, 5 | making it easier to distribute and install. The package is an AI-powered tool 6 | that provides seamless subtitle translation to enable cross-language 7 | accessibility for video content. 8 | 9 | When this script is run, it will package the project according to the 10 | configurations specified in the `setup()` function. This includes metadata 11 | about the project such as its name, version, description, and more. 12 | 13 | The packaged project can then be uploaded to PyPI or installed directly 14 | using pip. The script specifies the package's dependencies, which will be 15 | automatically installed when the package is installed. It also defines entry 16 | points for any command-line scripts included in the package. 17 | 18 | Package: 19 | Subtitle-AI-Translator 20 | 21 | Version: 22 | 1.0 23 | 24 | Author: 25 | sutasrof (mario.chauvet@icloud.com) 26 | 27 | Repository: 28 | https://github.com/sutasrof/Subtitle-AI-Translator 29 | 30 | Requirements: 31 | Python 3.6 and above 32 | 33 | Usage: 34 | The `setup.py` script should be run using Python's setuptools module: 35 | `python setup.py sdist bdist_wheel` 36 | This will generate distribution packages in the `dist` directory. 37 | 38 | The package can then be installed using pip: 39 | `pip install .` 40 | This will install the package along with its dependencies. 41 | """ 42 | from setuptools import setup, find_packages 43 | 44 | # Read the contents of your README file 45 | with open('README.md', encoding='utf-8') as f: 46 | long_description = f.read() 47 | 48 | setup( 49 | name='subtitle-ai-translator', 50 | version='1.0', 51 | packages=find_packages(), 52 | description=('AI-powered tool for seamless subtitle translation, enabling ' 53 | 'cross-language accessibility for video content.'), 54 | long_description=long_description, 55 | long_description_content_type='text/markdown', 56 | author='sutasrof', 57 | author_email='mario.chauvet@icloud.com', 58 | url='https://github.com/sutasrof/Subtitle-AI-Translator', 59 | install_requires=[ 60 | 'transformers[torch]>=4.34.1', 61 | 'sentencepiece>=0.1.99' 62 | ], 63 | classifiers=[ 64 | 'Programming Language :: Python :: 3', 65 | 'License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)', 66 | 'Operating System :: OS Independent', 67 | ], 68 | python_requires='>=3.6', 69 | entry_points={ 70 | 'console_scripts': [ 71 | 'subtitle_ai_translator=subtitle_ai_translator.main:main', 72 | ], 73 | }, 74 | ) 75 | -------------------------------------------------------------------------------- /subtitle_ai_translator/__init__.py: -------------------------------------------------------------------------------- 1 |  -------------------------------------------------------------------------------- /subtitle_ai_translator/main.py: -------------------------------------------------------------------------------- 1 | """ 2 | This script is designed to translate subtitle files in the VTT (WebVTT) format 3 | using AI-powered translation. 4 | 5 | Utilizing the M2M100 model from Hugging Face's transformers library, the script 6 | is capable of translating subtitle text from the source language to a specified 7 | target language. The script supports batch processing to enhance the efficiency 8 | of translation by processing multiple subtitle lines simultaneously. 9 | 10 | Subtitle lines that contain timestamps or are empty are preserved as is, while 11 | subtitle text is translated and reinserted with the appropriate timestamps. 12 | 13 | The script is intended to be called from the command line with the following 14 | arguments: 15 | - source: the path to the source subtitle file to be translated. 16 | - destination: the path to the subtitle file where the translation should be 17 | saved. 18 | - language: the target language code for the translation. 19 | 20 | A pre-trained model and tokenizer are used to perform the translation, which 21 | are specified within the script. The user has the option to change the model by 22 | altering the `model_name` variable. 23 | 24 | Usage: 25 | python script_name.py source.vtt destination.vtt target_language_code 26 | 27 | Example: 28 | python script_name.py subtitles.vtt translated_subtitles.vtt es 29 | 30 | The script also includes functions that can be integrated into other Python 31 | modules if subtitle translation capabilities are required elsewhere. 32 | 33 | Note: This script requires the 'transformers' and 'regex' libraries. Ensure 34 | these are installed in your Python environment before running the script. 35 | """ 36 | import argparse 37 | import re 38 | from dataclasses import dataclass 39 | from transformers import AutoTokenizer, M2M100ForConditionalGeneration 40 | 41 | @dataclass 42 | class TranslatorConfig: 43 | """ 44 | Configuration class for subtitle translation tasks. 45 | 46 | Attributes: 47 | model (M2M100ForConditionalGeneration): A pre-trained M2M100 model from 48 | Hugging Face's transformers library for machine translation. 49 | tokenizer (AutoTokenizer): Corresponds to the M2M100 model and is used 50 | for converting input text into a format suitable for the model. 51 | batch_size (int): Number of subtitle entries to process in a batch for 52 | efficient translation, reducing model calls. Default is 10. 53 | 54 | Example: 55 | >>> model = M2M100ForConditionalGeneration.from_pretrained( 56 | ... 'facebook/m2m100_418M') 57 | >>> tokenizer = AutoTokenizer.from_pretrained('facebook/m2m100_418M') 58 | >>> config = TranslatorConfig(model=model, tokenizer=tokenizer, 59 | ... batch_size=10) 60 | """ 61 | 62 | model: M2M100ForConditionalGeneration 63 | tokenizer: AutoTokenizer 64 | batch_size: int = 10 65 | 66 | # Compile the regex pattern once 67 | timestamp_pattern = re.compile( 68 | r'^\d{2}:\d{2}(?::\d{2})?\.\d{3} --> \d{2}:\d{2}(?::\d{2})?\.\d{3}') 69 | 70 | 71 | def translate_batch(text_batch, dest_lang, model, tokenizer): 72 | """ 73 | Translates a batch of text into the specified destination language. 74 | 75 | This function takes a list of text strings and the target language code, and 76 | uses the provided model and tokenizer to generate the translations. It handles 77 | the tokenization of the input text, the generation of translated tokens, and 78 | the decoding of these tokens back into translated strings. 79 | 80 | Args: 81 | text_batch (list of str): A list of text strings to be translated. 82 | dest_lang (str): The target language code to which the text should be 83 | translated. 84 | model (transformers.PreTrainedModel): A pre-trained model from the 85 | `transformers` library. 86 | tokenizer (transformers.PreTrainedTokenizer): A tokenizer that corresponds 87 | to the `model`. 88 | 89 | Returns: 90 | list of str: A list of translated text strings. 91 | 92 | Example: 93 | >>> model_name = 'facebook/m2m100_418M' 94 | >>> model = M2M100ForConditionalGeneration.from_pretrained(model_name) 95 | >>> tokenizer = AutoTokenizer.from_pretrained(model_name) 96 | >>> text_batch = ["Hello, world!", "How are you?"] 97 | >>> dest_lang = 'fr' 98 | >>> translate_batch(text_batch, dest_lang, model, tokenizer) 99 | ['Bonjour, monde !', 'Comment ça va ?'] 100 | """ 101 | 102 | model_inputs = tokenizer( 103 | text_batch, return_tensors="pt", padding=True, truncation=True, max_length=512) 104 | gen_tokens = model.generate( 105 | **model_inputs, forced_bos_token_id=tokenizer.get_lang_id(dest_lang)) 106 | translations = tokenizer.batch_decode(gen_tokens, skip_special_tokens=True) 107 | return translations 108 | 109 | 110 | def extract_and_translate_from_vtt( 111 | file_path: str, 112 | output_path: str, 113 | language: str, 114 | config: TranslatorConfig 115 | ): 116 | """ 117 | Extracts text from a VTT file, translates it, and writes to a new VTT file. 118 | 119 | This function reads a VTT file, extracts dialogue lines while preserving 120 | timestamps and formatting, and uses a model to translate text in batches. 121 | The translated text is then written to an output file, maintaining the 122 | original VTT file's timing and structure. 123 | 124 | Args: 125 | file_path (str): Path for the input VTT subtitle file. 126 | output_path (str): Path where the translated VTT file will be saved. 127 | language (str): Target language code for the translation (e.g., 'en'). 128 | model (transformers.PreTrainedModel): Pre-trained model for translation. 129 | tokenizer (transformers.PreTrainedTokenizer): Tokenizer for the model. 130 | batch_size (int, optional): Number of lines to translate at once. 131 | Defaults to 10. 132 | 133 | Example: 134 | >>> file_path = 'subtitles.vtt' 135 | >>> output_path = 'translated_subtitles.vtt' 136 | >>> language = 'es' 137 | >>> model_name = 'facebook/m2m100_418M' 138 | >>> model = M2M100ForConditionalGeneration.from_pretrained(model_name) 139 | >>> tokenizer = AutoTokenizer.from_pretrained(model_name) 140 | >>> extract_and_translate_from_vtt(file_path, output_path, language, 141 | ... model, tokenizer, batch_size=10) 142 | 143 | The resulting file will have translated subtitles with original timestamps. 144 | """ 145 | 146 | subtitle_batch = [] 147 | 148 | with open(file_path, 'r', encoding='utf-8') as vtt_file, \ 149 | open(output_path, 'w', encoding='utf-8') as out_file: 150 | 151 | for line in vtt_file: 152 | if timestamp_pattern.match(line.strip()) or line.strip() == "": 153 | # If we have a batch ready, translate it before writing the timestamp 154 | if subtitle_batch: 155 | translations = translate_batch( 156 | subtitle_batch, language, config.model, config.tokenizer) 157 | for translation in translations: 158 | out_file.write(translation + '\n') 159 | subtitle_batch = [] # Reset the batch 160 | out_file.write(line) 161 | else: 162 | subtitle_batch.append(line.strip()) 163 | if len(subtitle_batch) == config.batch_size: 164 | translations = translate_batch( 165 | subtitle_batch, language, config.model, config.tokenizer) 166 | for translation in translations: 167 | out_file.write(translation + '\n') 168 | subtitle_batch = [] # Reset the batch 169 | 170 | # Handle the last batch 171 | if subtitle_batch: 172 | translations = translate_batch( 173 | subtitle_batch, language, config.model, config.tokenizer) 174 | for translation in translations: 175 | out_file.write(translation + '\n') 176 | 177 | 178 | def main(): 179 | """ 180 | The main entry point for the script when used as a command-line tool. 181 | 182 | Parses command-line arguments for the source VTT file, the destination file 183 | path, and the target language code. Initializes the translation model and 184 | tokenizer, and calls the function to extract and translate text from the VTT 185 | file. 186 | 187 | Command-line arguments: 188 | - source: Path to the source subtitle VTT file to be translated. 189 | - destination: Path where the translated VTT file will be saved. 190 | - language: Target language code for translation (e.g., 'en', 'es'). 191 | 192 | Uses the M2M100 model from the Hugging Face transformers library. 193 | 194 | Usage: 195 | Run the script with the required arguments from the command line. 196 | Example: 197 | python script_name.py source.vtt destination.vtt es 198 | 199 | Translates 'source.vtt' to Spanish and saves it in 'destination.vtt'. 200 | """ 201 | 202 | parser = argparse.ArgumentParser( 203 | description='Translate VTT files using batch processing.') 204 | parser.add_argument( 205 | 'source', help='The source subtitle file to translate.') 206 | parser.add_argument( 207 | 'destination', help='The subtitle file where to save the translation.') 208 | parser.add_argument( 209 | 'language', help='The target language code for the translation.') 210 | args = parser.parse_args() 211 | 212 | model_name = "facebook/m2m100_418M" 213 | model = M2M100ForConditionalGeneration.from_pretrained(model_name) 214 | tokenizer = AutoTokenizer.from_pretrained(model_name) 215 | 216 | ai_config = TranslatorConfig(model=model, tokenizer=tokenizer, batch_size=10) 217 | extract_and_translate_from_vtt(args.source, args.destination, args.language, ai_config) 218 | 219 | 220 | if __name__ == "__main__": 221 | main() 222 | --------------------------------------------------------------------------------