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docs(readme): 更新说明并添加终端使用指南
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@@ -130,3 +130,175 @@ The software provides two default caption engines. If you need other caption eng
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Note that when using a custom caption engine, all previous caption engine settings will be ineffective, and the configuration of the custom caption engine is entirely done through the engine command.
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If you are a developer and want to develop a custom caption engine, please refer to the [Caption Engine Explanation Document](../engine-manual/en.md).
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## Using Caption Engine Standalone
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### Runtime Parameter Description
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> The following content assumes users have some knowledge of running programs via terminal.
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The complete set of runtime parameters available for the caption engine is shown below:
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However, when used standalone, some parameters may not need to be used or should not be modified.
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The following parameter descriptions only include necessary parameters.
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#### `-e , --caption_engine`
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The caption engine model to select, currently three options are available: `gummy, vosk, sosv`.
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The default value is `gummy`.
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This applies to all models.
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#### `-a, --audio_type`
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The audio type to recognize, where `0` represents system audio output and `1` represents microphone audio input.
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The default value is `0`.
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This applies to all models.
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#### `-d, --display_caption`
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Whether to display captions in the console, `0` means do not display, `1` means display.
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The default value is `0`, but it's recommended to choose `1` when using only the caption engine.
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This applies to all models.
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#### `-t, --target_language`
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> Note that Vosk and SOSV models have poor sentence segmentation, which can make translated content difficult to understand. It's not recommended to use translation with these two models.
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Target language for translation. All models support the following translation languages:
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- `none` No translation
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- `zh` Simplified Chinese
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- `en` English
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- `ja` Japanese
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- `ko` Korean
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Additionally, `vosk` and `sosv` models also support the following translations:
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- `de` German
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- `fr` French
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- `ru` Russian
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- `es` Spanish
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- `it` Italian
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The default value is `none`.
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This applies to all models.
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#### `-s, --source_language`
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Source language for recognition. Default value is `auto`, meaning no specific source language.
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Specifying the source language can improve recognition accuracy to some extent. You can specify the source language using the language codes above.
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This only applies to Gummy and SOSV models.
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The Gummy model can use all the languages mentioned above, plus Cantonese (`yue`).
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The SOSV model supports specifying the following languages: English, Chinese, Japanese, Korean, and Cantonese.
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#### `-k, --api_key`
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Specify the Alibaba Cloud API KEY required for the `Gummy` model.
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Default value is empty.
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This only applies to the Gummy model.
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#### `-tm, --translation_model`
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Specify the translation method for Vosk and SOSV models. Default is `ollama`.
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Supported values are:
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- `ollama` Use local Ollama model for translation. Users need to install Ollama software and corresponding models
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- `google` Use Google Translate API for translation. No additional configuration needed, but requires network access to Google
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This only applies to Vosk and SOSV models.
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#### `-omn, --ollama_name`
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Specify the Ollama model to call for translation. Default value is empty.
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It's recommended to use models with less than 1B parameters, such as: `qwen2.5:0.5b`, `qwen3:0.6b`.
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Users need to download the corresponding model in Ollama to use it properly.
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This only applies to Vosk and SOSV models.
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#### `-vosk, --vosk_model`
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Specify the path to the local folder of the Vosk model to call. Default value is empty.
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This only applies to the Vosk model.
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#### `-sosv, --sosv_model`
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Specify the path to the local folder of the SOSV model to call. Default value is empty.
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This only applies to the SOSV model.
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### Running Caption Engine Using Source Code
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> The following content assumes users who use this method have knowledge of Python environment configuration and usage.
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First, download the project source code locally. The caption engine source code is located in the `engine` directory of the project. Then configure the Python environment, where the project dependencies are listed in the `requirements.txt` file in the `engine` directory.
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After configuration, enter the `engine` directory and execute commands to run the caption engine.
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For example, to use the Gummy model, specify audio type as system audio output, source language as English, and target language as Chinese, execute the following command:
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> Note: For better visualization, the commands below are written on multiple lines. If execution fails, try removing backslashes and executing as a single line command.
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```bash
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python main.py \
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-e gummy \
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-k sk-******************************** \
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-a 0 \
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-d 1 \
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-s en \
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-t zh
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```
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To specify the Vosk model, audio type as system audio output, translate to English, and use Ollama `qwen3:0.6b` model for translation:
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```bash
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python main.py \
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-e vosk \
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-vosk D:\Projects\auto-caption\engine\models\vosk-model-small-cn-0.22 \
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-a 0 \
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-d 1 \
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-t en \
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```
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To specify the SOSV model, audio type as microphone, automatically select source language, and no translation:
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```bash
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python main.py \
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-e sosv \
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-sosv D:\\Projects\\auto-caption\\engine\\models\\sosv-int8 \
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-a 1 \
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-d 1 \
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-s auto \
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-t none
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```
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Running result using the Gummy model is shown below:
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### Running Subtitle Engine Executable File
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First, download the executable file for your platform from [GitHub Releases](https://github.com/HiMeditator/auto-caption/releases/tag/engine) (currently only Windows and Linux platform executable files are provided).
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Then open a terminal in the directory containing the caption engine executable file and execute commands to run the caption engine.
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Simply replace `python main.py` in the above commands with the executable file name (for example: `engine-win.exe`).
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