├── .github └── workflows │ └── ci.yml ├── .gitignore ├── Dockerfile ├── Dockerfile.cuda ├── LICENSE ├── README.md ├── autocut ├── __init__.py ├── __main__.py ├── cut.py ├── daemon.py ├── main.py ├── transcribe.py └── utils.py ├── imgs └── typora.jpg ├── setup.cfg ├── setup.py └── test ├── config.py ├── content ├── test.srt ├── test_md.md └── test_srt.srt ├── media ├── test001.mp4 ├── test001_en.mp4 ├── test002.mov ├── test003.mkv ├── test004.flv └── test005.mp3 ├── test_cut.py └── test_transcribe.py /.github/workflows/ci.yml: -------------------------------------------------------------------------------- 1 | name: Test 2 | 3 | on: 4 | pull_request: 5 | push: 6 | branches: 7 | - main 8 | 9 | jobs: 10 | lint_and_test: 11 | runs-on: ${{ matrix.os }}-latest 12 | strategy: 13 | matrix: 14 | python-version: ['3.9', '3.10'] 15 | # macos did not support m1 for now 16 | os: [ubuntu, windows, macos] 17 | steps: 18 | - uses: actions/checkout@v3 19 | - name: Set up Python ${{ matrix.python-version }} 20 | uses: actions/setup-python@v4 21 | with: 22 | python-version: ${{ matrix.python-version }} 23 | - name: Set Variables 24 | id: set_variables 25 | shell: bash 26 | run: | 27 | echo "PY=$(python -c 'import hashlib, sys;print(hashlib.sha256(sys.version.encode()+sys.executable.encode()).hexdigest())')" >> $GITHUB_OUTPUT 28 | echo "PIP_CACHE=$(pip cache dir)" >> $GITHUB_OUTPUT 29 | - name: Cache PIP 30 | uses: actions/cache@v3 31 | with: 32 | path: ${{ steps.set_variables.outputs.PIP_CACHE }} 33 | key: ${{ runner.os }}-pip-${{ steps.set_variables.outputs.PY }} 34 | 35 | - name: Setup ffmpeg for differnt platforms 36 | uses: FedericoCarboni/setup-ffmpeg@master 37 | 38 | - name: Install dependencies 39 | run: | 40 | python -m pip install --upgrade pip 41 | pip install . 42 | pip install pytest black 43 | - name: Run Test 44 | run: pytest test/ 45 | - name: Run Lint 46 | run: black . --check 47 | -------------------------------------------------------------------------------- /.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 | pip-wheel-metadata/ 24 | share/python-wheels/ 25 | *.egg-info/ 26 | .installed.cfg 27 | *.egg 28 | MANIFEST 29 | 30 | # PyInstaller 31 | # Usually these files are written by a python script from a template 32 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 33 | *.manifest 34 | *.spec 35 | 36 | # Installer logs 37 | pip-log.txt 38 | pip-delete-this-directory.txt 39 | 40 | # Unit test / coverage reports 41 | htmlcov/ 42 | .tox/ 43 | .nox/ 44 | .coverage 45 | .coverage.* 46 | .cache 47 | nosetests.xml 48 | coverage.xml 49 | *.cover 50 | *.py,cover 51 | .hypothesis/ 52 | .pytest_cache/ 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 | target/ 76 | 77 | # Jupyter Notebook 78 | .ipynb_checkpoints 79 | 80 | # IPython 81 | profile_default/ 82 | ipython_config.py 83 | 84 | # pyenv 85 | .python-version 86 | 87 | # pipenv 88 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 89 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 90 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 91 | # install all needed dependencies. 92 | #Pipfile.lock 93 | 94 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow 95 | __pypackages__/ 96 | 97 | # Celery stuff 98 | celerybeat-schedule 99 | celerybeat.pid 100 | 101 | # SageMath parsed files 102 | *.sage.py 103 | 104 | # Environments 105 | .env 106 | .venv 107 | env/ 108 | venv/ 109 | ENV/ 110 | env.bak/ 111 | venv.bak/ 112 | 113 | # Spyder project settings 114 | .spyderproject 115 | .spyproject 116 | 117 | # Rope project settings 118 | .ropeproject 119 | 120 | # mkdocs documentation 121 | /site 122 | 123 | # mypy 124 | .mypy_cache/ 125 | .dmypy.json 126 | dmypy.json 127 | 128 | # Pyre type checker 129 | .pyre/ 130 | log/ 131 | 132 | # IDE 133 | .vscode/ -------------------------------------------------------------------------------- /Dockerfile: -------------------------------------------------------------------------------- 1 | FROM python:3.9-slim as base 2 | 3 | RUN mkdir /autocut 4 | COPY ./ /autocut 5 | WORKDIR /autocut 6 | 7 | RUN apt update && \ 8 | apt install -y git && \ 9 | apt install -y ffmpeg 10 | 11 | RUN pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cpu && \ 12 | pip install . -------------------------------------------------------------------------------- /Dockerfile.cuda: -------------------------------------------------------------------------------- 1 | FROM pytorch/pytorch:1.13.0-cuda11.6-cudnn8-runtime 2 | 3 | RUN mkdir /autocut 4 | COPY ./ /autocut 5 | WORKDIR /autocut 6 | 7 | RUN apt update && \ 8 | apt install -y git && \ 9 | apt install -y ffmpeg 10 | 11 | RUN pip install . -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | Apache License 2 | Version 2.0, January 2004 3 | http://www.apache.org/licenses/ 4 | 5 | TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 6 | 7 | 1. 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使用例子 6 | 7 | 假如你录制的视频放在 `2022-11-04/` 这个文件夹里。那么运行 8 | 9 | ```bash 10 | autocut -d 2022-11-04 11 | ``` 12 | 13 | > 提示：如果你使用 OBS 录屏，可以在 `设置->高级->录像->文件名格式` 中将空格改成 `/`，即 `%CCYY-%MM-%DD/%hh-%mm-%ss`。那么视频文件将放在日期命名的文件夹里。 14 | 15 | AutoCut 将持续对这个文件夹里视频进行字幕抽取和剪切。例如，你刚完成一个视频录制，保存在 `11-28-18.mp4`。AutoCut 将生成 `11-28-18.md`。你在里面选择需要保留的句子后，AutoCut 将剪切出 `11-28-18_cut.mp4`，并生成 `11-28-18_cut.md` 来预览结果。 16 | 17 | 你可以使用任何的 Markdown 编辑器。例如我常用 VS Code 和 Typora。下图是通过 Typora 来对 `11-28-18.md` 编辑。 18 | 19 | ![](imgs/typora.jpg) 20 | 21 | 全部完成后在 `autocut.md` 里选择需要拼接的视频后，AutoCut 将输出 `autocut_merged.mp4` 和对应的字幕文件。 22 | 23 | ## 安装 24 | 25 | 首先安装 Python 包 26 | 27 | ``` 28 | pip install git+https://github.com/mli/autocut.git 29 | ``` 30 | 31 | ## 本地安装测试 32 | 33 | 34 | ``` 35 | git clone https://github.com/mli/autocut 36 | cd autocut 37 | pip install . 38 | ``` 39 | 40 | 41 | > 上面将安装 [pytorch](https://pytorch.org/)。如果你需要 GPU 运行，且默认安装的版本不匹配的话，你可以先安装 Pytorch。如果安装 Whipser 出现问题，请参考[官方文档](https://github.com/openai/whisper#setup)。 42 | 43 | 另外需要安装 [ffmpeg](https://ffmpeg.org/) 44 | 45 | ``` 46 | # on Ubuntu or Debian 47 | sudo apt update && sudo apt install ffmpeg 48 | 49 | # on Arch Linux 50 | sudo pacman -S ffmpeg 51 | 52 | # on MacOS using Homebrew (https://brew.sh/) 53 | brew install ffmpeg 54 | 55 | # on Windows using Scoop (https://scoop.sh/) 56 | scoop install ffmpeg 57 | ``` 58 | 59 | ## Docker 安装 60 | 61 | 首先将项目克隆到本地。 62 | 63 | ```bash 64 | git clone https://github.com/mli/autocut.git 65 | ``` 66 | 67 | ### 安装 CPU 版本 68 | 69 | 进入项目根目录，然后构建 docker 映像。 70 | 71 | ```bash 72 | docker build -t autocut . 73 | ``` 74 | 75 | 运行下面的命令创建 docker 容器，就可以直接使用了。 76 | 77 | ```bash 78 | docker run -it --rm -v E:\autocut:/autocut/video autocut /bin/bash 79 | ``` 80 | 81 | 其中 `-v` 是将主机存放视频的文件夹 `E:\autocut` 映射到虚拟机的 `/autocut/video` 目录。`E:\autocut` 是主机存放视频的目录，需修改为自己主机存放视频的目录。 82 | 83 | ### 安装 GPU 版本 84 | 85 | 使用 GPU 加速需要主机有 Nvidia 的显卡并安装好相应驱动。然后在项目根目录，执行下面的命令构建 docker 映像。 86 | 87 | ```bash 88 | docker build -f ./Dockerfile.cuda -t autocut-gpu . 89 | ``` 90 | 91 | 使用 GPU 加速时，运行 docker 容器需添加参数 `--gpus all`。 92 | 93 | ```bash 94 | docker run --gpus all -it --rm -v E:\autocut:/autocut/video autocut-gpu 95 | ``` 96 | 97 | ## 更多使用选项 98 | 99 | ### 转录某个视频生成 `.srt` 和 `.md` 结果。 100 | 101 | ```bash 102 | autocut -t 22-52-00.mp4 103 | ``` 104 | 105 | 1. 如果对转录质量不满意，可以使用更大的模型，例如 106 | 107 | ```bash 108 | autocut -t 22-52-00.mp4 --whisper-model large 109 | ``` 110 | 111 | 默认是 `small`。更好的模型是 `medium` 和 `large`，但推荐使用 GPU 获得更好的速度。也可以使用更快的 `tiny` 和 `base`，但转录质量会下降。 112 | 113 | 114 | ### 剪切某个视频 115 | 116 | ```bash 117 | autocut -c 22-52-00.mp4 22-52-00.srt 22-52-00.md 118 | ``` 119 | 120 | 1. 默认视频比特率是 `--bitrate 10m`，你可以根据需要调大调小。 121 | 2. 如果不习惯 Markdown 格式文件，你也可以直接在 `srt` 文件里删除不要的句子，在剪切时不传入 `md` 文件名即可。就是 `autocut -c 22-52-00.mp4 22-52-00.srt` 122 | 3. 如果仅有 `srt` 文件，编辑不方便可以使用如下命令生成 `md` 文件，然后编辑 `md` 文件即可，但此时会完全对照 `srt` 生成，不会出现 `no speech` 等提示文本。 123 | 124 | ```bash 125 | autocut -m test.srt test.mp4 126 | autocut -m test.mp4 test.srt # 支持视频和字幕乱序传入 127 | autocut -m test.srt # 也可以只传入字幕文件 128 | ``` 129 | 130 | 131 | ### 一些小提示 132 | 133 | 134 | 1. 讲得流利的视频的转录质量会高一些，这因为是 Whisper 训练数据分布的缘故。对一个视频，你可以先粗选一下句子，然后在剪出来的视频上再剪一次。 135 | 2. ~~最终视频生成的字幕通常还需要做一些小编辑。你可以直接编辑`md`文件（比`srt`文件更紧凑，且嵌入了视频）。然后使用 `autocut -s 22-52-00.md 22-52-00.srt` 来生成更新的字幕 `22-52-00_edited.srt`。注意这里会无视句子是不是被选中，而是全部转换成 `srt`。~~ 136 | 3. 最终视频生成的字幕通常还需要做一些小编辑。但 `srt` 里面空行太多。你可以使用 `autocut -s 22-52-00.srt` 来生成一个紧凑些的版本 `22-52-00_compact.srt` 方便编辑（这个格式不合法，但编辑器，例如 VS Code，还是会进行语法高亮）。编辑完成后，`autocut -s 22-52-00_compact.srt` 转回正常格式。 137 | 4. 用 Typora 和 VS Code 编辑 Markdown 都很方便。他们都有对应的快捷键 mark 一行或者多行。但 VS Code 视频预览似乎有点问题。 138 | 5. 视频是通过 ffmpeg 导出。在 Apple M1 芯片上它用不了 GPU，导致导出速度不如专业视频软件。 139 | 140 | ### 常见问题 141 | 142 | 1. **输出的是乱码？** 143 | 144 | AutoCut 默认输出编码是 `utf-8`. 确保你的编辑器也使用了 `utf-8` 解码。你可以通过 `--encoding` 指定其他编码格式。但是需要注意生成字幕文件和使用字幕文件剪辑时的编码格式需要一致。例如使用 `gbk`。 145 | 146 | ```bash 147 | autocut -t test.mp4 --encoding=gbk 148 | autocut -c test.mp4 test.srt test.md --encoding=gbk 149 | ``` 150 | 151 | 如果使用了其他编码格式（如 `gbk` 等）生成 `md` 文件并用 Typora 打开后，该文件可能会被 Typora 自动转码为其他编码格式，此时再通过生成时指定的编码格式进行剪辑时可能会出现编码不支持等报错。因此可以在使用 Typora 编辑后再通过 VSCode 等修改到你需要的编码格式进行保存后再使用剪辑功能。 152 | 153 | 2. **如何使用 GPU 来转录？** 154 | 155 | 当你有 Nvidia GPU，而且安装了对应版本的 PyTorch 的时候，转录是在 GPU 上进行。你可以通过命令来查看当前是不是支持 GPU。 156 | 157 | ```bash 158 | python -c "import torch; print(torch.cuda.is_available())" 159 | ``` 160 | 161 | 否则你可以在安装 AutoCut 前手动安装对应的 GPU 版本 PyTorch。 162 | 163 | 3. **使用 GPU 时报错显存不够。** 164 | 165 | whisper 的大模型需要一定的 GPU 显存。如果你的显存不够，你可以用小一点的模型，例如 `small`。如果你仍然想用大模型，可以通过 `--device` 来强制使用 CPU。例如 166 | 167 | ```bash 168 | autocut -t 11-28-18.mp4 --whisper-model large --device cpu 169 | ``` 170 | 171 | 4. **能不能使用 `pip` 安装?** 172 | 173 | 因为 AutoCut 的依赖 whisper 没有在 PyPI 发布包，所以目前只能用 `pip install git+https://github.com/mli/autocut.git` 这种方式发布。有需求的同学可以查看 whisper 模型是不是能直接在 huggingface hub 下载，从而摆脱 whisper 包的依赖。 174 | 175 | 176 | ## 如何参与贡献 177 | 178 | [这里有一些想做的 feature](https://github.com/mli/autocut/issues/22)，欢迎贡献。 179 | 180 | ### 代码结构 181 | ```text 182 | autocut 183 | │ .gitignore 184 | │ LICENSE 185 | │ README.md # 一般新增或修改需要让使用者知道就需要对应更新 README.md 内容 186 | │ setup.py 187 | │ 188 | └─autocut # 核心代码位于 autocut 文件夹中，新增功能的实现也一般在这里面进行修改或新增 189 | │ cut.py 190 | │ daemon.py 191 | │ main.py 192 | │ transcribe.py 193 | │ utils.py 194 | └─ __init__.py 195 | 196 | ``` 197 | 198 | ### 安装依赖 199 | 开始安装这个项目的需要的依赖之前，建议先了解一下 Anaconda 或者 venv 的虚拟环境使用，推荐**使用虚拟环境来搭建该项目的开发环境**。 200 | 具体安装方式为在你搭建搭建的虚拟环境之中按照[上方安装步骤](./README.md#安装)进行安装。 201 | 202 | > 为什么推荐使用虚拟环境开发？ 203 | > 204 | > 一方面是保证各种不同的开发环境之间互相不污染。 205 | > 206 | > 更重要的是在于这个项目实际上是一个 Python Package，所以在你安装之后 AutoCut 的代码实际也会变成你的环境依赖。 207 | > **因此在你更新代码之后，你需要让将新代码重新安装到环境中，然后才能调用到新的代码。** 208 | 209 | ### 开发 210 | 211 | 1. 代码风格目前遵循 PEP-8，可以使用相关的自动格式化软件完成。 212 | 2. `utils.py` 主要是全局共用的一些工具方法。 213 | 3. `transcribe.py` 是调用模型生成`srt`和`md`的部分。 214 | 4. `cut.py` 提供根据标记后`md`或`srt`进行视频剪切合并的功能。 215 | 5. `daemon.py` 提供的是监听文件夹生成字幕和剪切视频的功能。 216 | 6. `main.py` 声明命令行参数，根据输入参数调用对应功能。 217 | 218 | 开发过程中请尽量保证修改在正确的地方，以及合理地复用代码， 219 | 同时工具函数请尽可能放在`utils.py`中。 220 | 代码格式目前是遵循 PEP-8，变量命名尽量语义化即可。 221 | 222 | 在开发完成之后，最重要的一点是需要进行**测试**，请保证提交之前对所有**与你修改直接相关的部分**以及**你修改会影响到的部分**都进行了测试，并保证功能的正常。 223 | 目前使用 `GitHub Actions` CI, Lint 使用 black 提交前请运行 `black`。 224 | 225 | ### 提交 226 | 227 | 1. commit 信息用英文描述清楚你做了哪些修改即可，小写字母开头。 228 | 2. 最好可以保证一次的 commit 涉及的修改比较小，可以简短地描述清楚，这样也方便之后有修改时的查找。 229 | 3. PR 的时候 title 简述有哪些修改， contents 可以具体写下修改内容。 230 | 4. run test `pip install pytest` then `pytest test` 231 | 5. run lint `pip install black` then `black .` 232 | -------------------------------------------------------------------------------- /autocut/__init__.py: -------------------------------------------------------------------------------- 1 | __version__ = "0.0.3" 2 | -------------------------------------------------------------------------------- /autocut/__main__.py: -------------------------------------------------------------------------------- 1 | from .main import main 2 | 3 | if __name__ == "__main__": 4 | main() 5 | -------------------------------------------------------------------------------- /autocut/cut.py: -------------------------------------------------------------------------------- 1 | import logging 2 | import os 3 | import re 4 | 5 | import srt 6 | from moviepy import editor 7 | 8 | from . import utils 9 | 10 | 11 | # Merge videos 12 | class Merger: 13 | def __init__(self, args): 14 | self.args = args 15 | 16 | def write_md(self, videos): 17 | md = utils.MD(self.args.inputs[0], self.args.encoding) 18 | num_tasks = len(md.tasks()) 19 | # Not overwrite if already marked as down or no new videos 20 | if md.done_editing() or num_tasks == len(videos) + 1: 21 | return 22 | 23 | md.clear() 24 | md.add_done_editing(False) 25 | md.add("\nSelect the files that will be used to generate `autocut_final.mp4`\n") 26 | base = lambda fn: os.path.basename(fn) 27 | for f in videos: 28 | md_fn = utils.change_ext(f, "md") 29 | video_md = utils.MD(md_fn, self.args.encoding) 30 | # select a few words to scribe the video 31 | desc = "" 32 | if len(video_md.tasks()) > 1: 33 | for _, t in video_md.tasks()[1:]: 34 | m = re.findall(r"\] (.*)", t) 35 | if m and "no speech" not in m[0].lower(): 36 | desc += m[0] + " " 37 | if len(desc) > 50: 38 | break 39 | md.add_task( 40 | False, 41 | f'[{base(f)}]({base(md_fn)}) {"[Edited]" if video_md.done_editing() else ""} {desc}', 42 | ) 43 | md.write() 44 | 45 | def run(self): 46 | md_fn = self.args.inputs[0] 47 | md = utils.MD(md_fn, self.args.encoding) 48 | if not md.done_editing(): 49 | return 50 | 51 | videos = [] 52 | for m, t in md.tasks(): 53 | if not m: 54 | continue 55 | m = re.findall(r"\[(.*)\]", t) 56 | if not m: 57 | continue 58 | fn = os.path.join(os.path.dirname(md_fn), m[0]) 59 | logging.info(f"Loading {fn}") 60 | videos.append(editor.VideoFileClip(fn)) 61 | 62 | dur = sum([v.duration for v in videos]) 63 | logging.info(f"Merging into a video with {dur / 60:.1f} min length") 64 | 65 | merged = editor.concatenate_videoclips(videos) 66 | fn = os.path.splitext(md_fn)[0] + "_merged.mp4" 67 | merged.write_videofile( 68 | fn, audio_codec="aac", bitrate=self.args.bitrate 69 | ) # logger=None, 70 | logging.info(f"Saved merged video to {fn}") 71 | 72 | 73 | # Cut media 74 | class Cutter: 75 | def __init__(self, args): 76 | self.args = args 77 | 78 | def run(self): 79 | fns = {"srt": None, "media": None, "md": None} 80 | for fn in self.args.inputs: 81 | ext = os.path.splitext(fn)[1][1:] 82 | fns[ext if ext in fns else "media"] = fn 83 | 84 | assert fns["media"], "must provide a media filename" 85 | assert fns["srt"], "must provide a srt filename" 86 | 87 | is_video_file = utils.is_video(fns["media"]) 88 | outext = "mp4" if is_video_file else "mp3" 89 | output_fn = utils.change_ext(utils.add_cut(fns["media"]), outext) 90 | if utils.check_exists(output_fn, self.args.force): 91 | return 92 | 93 | with open(fns["srt"], encoding=self.args.encoding) as f: 94 | subs = list(srt.parse(f.read())) 95 | 96 | if fns["md"]: 97 | md = utils.MD(fns["md"], self.args.encoding) 98 | if not md.done_editing(): 99 | return 100 | index = [] 101 | for mark, sent in md.tasks(): 102 | if not mark: 103 | continue 104 | m = re.match(r"\[(\d+)", sent.strip()) 105 | if m: 106 | index.append(int(m.groups()[0])) 107 | subs = [s for s in subs if s.index in index] 108 | logging.info(f'Cut {fns["media"]} based on {fns["srt"]} and {fns["md"]}') 109 | else: 110 | logging.info(f'Cut {fns["media"]} based on {fns["srt"]}') 111 | 112 | segments = [] 113 | # Avoid disordered subtitles 114 | subs.sort(key=lambda x: x.start) 115 | for x in subs: 116 | if len(segments) == 0: 117 | segments.append( 118 | {"start": x.start.total_seconds(), "end": x.end.total_seconds()} 119 | ) 120 | else: 121 | if x.start.total_seconds() - segments[-1]["end"] < 0.5: 122 | segments[-1]["end"] = x.end.total_seconds() 123 | else: 124 | segments.append( 125 | {"start": x.start.total_seconds(), "end": x.end.total_seconds()} 126 | ) 127 | 128 | if is_video_file: 129 | media = editor.VideoFileClip(fns["media"]) 130 | else: 131 | media = editor.AudioFileClip(fns["media"]) 132 | 133 | # Add a fade between two clips. Not quite necessary. keep code here for reference 134 | # fade = 0 135 | # segments = _expand_segments(segments, fade, 0, video.duration) 136 | # clips = [video.subclip( 137 | # s['start'], s['end']).crossfadein(fade) for s in segments] 138 | # final_clip = editor.concatenate_videoclips(clips, padding = -fade) 139 | 140 | clips = [media.subclip(s["start"], s["end"]) for s in segments] 141 | if is_video_file: 142 | final_clip: editor.VideoClip = editor.concatenate_videoclips(clips) 143 | logging.info( 144 | f"Reduced duration from {media.duration:.1f} to {final_clip.duration:.1f}" 145 | ) 146 | 147 | aud = final_clip.audio.set_fps(44100) 148 | final_clip = final_clip.without_audio().set_audio(aud) 149 | final_clip = final_clip.fx(editor.afx.audio_normalize) 150 | 151 | # an alternative to birate is use crf, e.g. ffmpeg_params=['-crf', '18'] 152 | final_clip.write_videofile( 153 | output_fn, audio_codec="aac", bitrate=self.args.bitrate 154 | ) 155 | else: 156 | final_clip: editor.AudioClip = editor.concatenate_audioclips(clips) 157 | logging.info( 158 | f"Reduced duration from {media.duration:.1f} to {final_clip.duration:.1f}" 159 | ) 160 | 161 | final_clip = final_clip.fx(editor.afx.audio_normalize) 162 | final_clip.write_audiofile( 163 | output_fn, codec="libmp3lame", fps=44100, bitrate=self.args.bitrate 164 | ) 165 | 166 | media.close() 167 | logging.info(f"Saved media to {output_fn}") 168 | -------------------------------------------------------------------------------- /autocut/daemon.py: -------------------------------------------------------------------------------- 1 | import copy 2 | import glob 3 | import logging 4 | import os 5 | import time 6 | 7 | from . import cut, transcribe, utils 8 | 9 | 10 | class Daemon: 11 | def __init__(self, args): 12 | self.args = args 13 | self.sleep = 1 14 | 15 | def run(self): 16 | assert len(self.args.inputs) == 1, "Must provide a single folder" 17 | while True: 18 | self._iter() 19 | time.sleep(self.sleep) 20 | self.sleep = min(60, self.sleep + 1) 21 | 22 | def _iter(self): 23 | folder = self.args.inputs[0] 24 | files = sorted(list(glob.glob(os.path.join(folder, "*")))) 25 | media_files = [f for f in files if utils.is_video(f) or utils.is_audio(f)] 26 | args = copy.deepcopy(self.args) 27 | for f in media_files: 28 | srt_fn = utils.change_ext(f, "srt") 29 | md_fn = utils.change_ext(f, "md") 30 | is_video_file = utils.is_video(f) 31 | if srt_fn not in files or md_fn not in files: 32 | args.inputs = [f] 33 | try: 34 | transcribe.Transcribe(args).run() 35 | self.sleep = 1 36 | break 37 | except RuntimeError as e: 38 | logging.warn( 39 | "Failed, may be due to the video is still on recording" 40 | ) 41 | pass 42 | if md_fn in files: 43 | if utils.add_cut(md_fn) in files: 44 | continue 45 | md = utils.MD(md_fn, self.args.encoding) 46 | ext = "mp4" if is_video_file else "mp3" 47 | if not md.done_editing() or os.path.exists( 48 | utils.change_ext(utils.add_cut(f), ext) 49 | ): 50 | continue 51 | args.inputs = [f, md_fn, srt_fn] 52 | cut.Cutter(args).run() 53 | self.sleep = 1 54 | 55 | args.inputs = [os.path.join(folder, "autocut.md")] 56 | merger = cut.Merger(args) 57 | merger.write_md(media_files) 58 | merger.run() 59 | -------------------------------------------------------------------------------- /autocut/main.py: -------------------------------------------------------------------------------- 1 | import argparse 2 | import logging 3 | import os 4 | 5 | from . import utils 6 | 7 | 8 | def main(): 9 | parser = argparse.ArgumentParser( 10 | description="Edit videos based on transcribed subtitles", 11 | formatter_class=argparse.RawDescriptionHelpFormatter, 12 | ) 13 | 14 | logging.basicConfig( 15 | format="[autocut:%(filename)s:L%(lineno)d] %(levelname)-6s %(message)s" 16 | ) 17 | logging.getLogger().setLevel(logging.INFO) 18 | 19 | parser.add_argument("inputs", type=str, nargs="+", help="Inputs filenames/folders") 20 | parser.add_argument( 21 | "-t", 22 | "--transcribe", 23 | help="Transcribe videos/audio into subtitles", 24 | action=argparse.BooleanOptionalAction, 25 | ) 26 | parser.add_argument( 27 | "-c", 28 | "--cut", 29 | help="Cut a video based on subtitles", 30 | action=argparse.BooleanOptionalAction, 31 | ) 32 | parser.add_argument( 33 | "-d", 34 | "--daemon", 35 | help="Monitor a folder to transcribe and cut", 36 | action=argparse.BooleanOptionalAction, 37 | ) 38 | parser.add_argument( 39 | "-s", 40 | help="Convert .srt to a compact format for easier editing", 41 | action=argparse.BooleanOptionalAction, 42 | ) 43 | parser.add_argument( 44 | "-m", 45 | "--to-md", 46 | help="Convert .srt to .md for easier editing", 47 | action=argparse.BooleanOptionalAction, 48 | ) 49 | parser.add_argument( 50 | "--lang", 51 | type=str, 52 | default="zh", 53 | choices=["zh", "en"], 54 | help="The output language of transcription", 55 | ) 56 | parser.add_argument( 57 | "--prompt", type=str, default="", help="initial prompt feed into whisper" 58 | ) 59 | parser.add_argument( 60 | "--whisper-model", 61 | type=str, 62 | default="small", 63 | choices=["tiny", "base", "small", "medium", "large", "large-v2"], 64 | help="The whisper model used to transcribe.", 65 | ) 66 | parser.add_argument( 67 | "--bitrate", 68 | type=str, 69 | default="10m", 70 | help="The bitrate to export the cutted video, such as 10m, 1m, or 500k", 71 | ) 72 | parser.add_argument( 73 | "--vad", help="If or not use VAD", choices=["1", "0", "auto"], default="auto" 74 | ) 75 | parser.add_argument( 76 | "--force", 77 | help="Force write even if files exist", 78 | action=argparse.BooleanOptionalAction, 79 | ) 80 | parser.add_argument( 81 | "--encoding", type=str, default="utf-8", help="Document encoding format" 82 | ) 83 | parser.add_argument( 84 | "--device", 85 | type=str, 86 | default="cpu", 87 | choices=["cpu", "cuda"], 88 | help="Force to CPU or GPU for transcribing. In default automatically use GPU if available.", 89 | ) 90 | 91 | args = parser.parse_args() 92 | 93 | if args.transcribe: 94 | from .transcribe import Transcribe 95 | 96 | Transcribe(args).run() 97 | elif args.to_md: 98 | from .utils import trans_srt_to_md 99 | 100 | if len(args.inputs) == 2: 101 | [input_1, input_2] = args.inputs 102 | base, ext = os.path.splitext(input_1) 103 | if ext != ".srt": 104 | input_1, input_2 = input_2, input_1 105 | trans_srt_to_md(args.encoding, args.force, input_1, input_2) 106 | elif len(args.inputs) == 1: 107 | trans_srt_to_md(args.encoding, args.force, args.inputs[0]) 108 | else: 109 | logging.warn( 110 | "Wrong number of files, please pass in a .srt file or an additional video file" 111 | ) 112 | elif args.cut: 113 | from .cut import Cutter 114 | 115 | Cutter(args).run() 116 | elif args.daemon: 117 | from .daemon import Daemon 118 | 119 | Daemon(args).run() 120 | elif args.s: 121 | utils.compact_rst(args.inputs[0], args.encoding) 122 | else: 123 | logging.warn("No action, use -c, -t or -d") 124 | 125 | 126 | if __name__ == "__main__": 127 | main() 128 | -------------------------------------------------------------------------------- /autocut/transcribe.py: -------------------------------------------------------------------------------- 1 | import datetime 2 | import logging 3 | import os 4 | import time 5 | 6 | import opencc 7 | import srt 8 | import torch 9 | from faster_whisper import WhisperModel, decode_audio as load_audio 10 | 11 | from . import utils 12 | 13 | 14 | class Transcribe: 15 | def __init__(self, args): 16 | self.args = args 17 | self.sampling_rate = 16000 18 | self.whisper_model = None 19 | self.vad_model = None 20 | self.detect_speech = None 21 | 22 | def run(self): 23 | for input in self.args.inputs: 24 | logging.info(f"Transcribing {input}") 25 | name, _ = os.path.splitext(input) 26 | if utils.check_exists(name + ".md", self.args.force): 27 | continue 28 | 29 | # audio = whisper.load_audio(input, sr=self.sampling_rate) 30 | audio = load_audio(input, sampling_rate=self.sampling_rate) 31 | if ( 32 | self.args.vad == "1" 33 | or self.args.vad == "auto" 34 | and not name.endswith("_cut") 35 | ): 36 | speech_timestamps = self._detect_voice_activity(audio) 37 | else: 38 | speech_timestamps = [{"start": 0, "end": len(audio)}] 39 | transcribe_results = self._transcribe(audio, speech_timestamps) 40 | 41 | output = name + ".srt" 42 | self._save_srt(output, transcribe_results) 43 | logging.info(f"Transcribed {input} to {output}") 44 | self._save_md(name + ".md", output, input) 45 | logging.info(f'Saved texts to {name + ".md"} to mark sentences') 46 | 47 | def _detect_voice_activity(self, audio): 48 | """Detect segments that have voice activities""" 49 | tic = time.time() 50 | if self.vad_model is None or self.detect_speech is None: 51 | # torch load limit https://github.com/pytorch/vision/issues/4156 52 | torch.hub._validate_not_a_forked_repo = lambda a, b, c: True 53 | self.vad_model, funcs = torch.hub.load( 54 | repo_or_dir="snakers4/silero-vad", model="silero_vad", trust_repo=True 55 | ) 56 | 57 | self.detect_speech = funcs[0] 58 | 59 | speeches = self.detect_speech( 60 | audio, self.vad_model, sampling_rate=self.sampling_rate 61 | ) 62 | 63 | # Remove too short segments 64 | speeches = utils.remove_short_segments(speeches, 1.0 * self.sampling_rate) 65 | 66 | # Expand to avoid to tight cut. You can tune the pad length 67 | speeches = utils.expand_segments( 68 | speeches, 0.2 * self.sampling_rate, 0.0 * self.sampling_rate, audio.shape[0] 69 | ) 70 | 71 | # Merge very closed segments 72 | speeches = utils.merge_adjacent_segments(speeches, 0.5 * self.sampling_rate) 73 | 74 | logging.info(f"Done voice activity detection in {time.time() - tic:.1f} sec") 75 | return speeches if len(speeches) > 1 else [{"start": 0, "end": len(audio)}] 76 | 77 | def _transcribe(self, audio, speech_timestamps): 78 | tic = time.time() 79 | if self.whisper_model is None: 80 | self.whisper_model = WhisperModel( 81 | self.args.whisper_model, self.args.device 82 | ) 83 | 84 | res = [] 85 | for seg in speech_timestamps: 86 | segments, info = self.whisper_model.transcribe( 87 | audio[int(seg["start"]): int(seg["end"])], 88 | task="transcribe", 89 | language=self.args.lang, 90 | initial_prompt=self.args.prompt, 91 | # verbose=False if len(speech_timestamps) == 1 else None, 92 | ) 93 | r = {} 94 | r["origin_timestamp"] = seg 95 | r["segments"] = segments 96 | r["info"] = info 97 | res.append(r) 98 | logging.info(f"Done transcription in {time.time() - tic:.1f} sec") 99 | return res 100 | 101 | def _save_srt(self, output, transcribe_results): 102 | subs = [] 103 | # whisper sometimes generate traditional chinese, explicitly convert 104 | cc = opencc.OpenCC("t2s") 105 | 106 | def _add_sub(start, end, text): 107 | subs.append( 108 | srt.Subtitle( 109 | index=0, 110 | start=datetime.timedelta(seconds=start), 111 | end=datetime.timedelta(seconds=end), 112 | content=cc.convert(text.strip()), 113 | ) 114 | ) 115 | 116 | prev_end = 0 117 | for r in transcribe_results: 118 | origin = r["origin_timestamp"] 119 | for seg in r["segments"]: 120 | s = dict(start=seg.start, end=seg.end, text=seg.text) 121 | start = s["start"] + origin["start"] / self.sampling_rate 122 | end = min( 123 | s["end"] + origin["start"] / self.sampling_rate, 124 | origin["end"] / self.sampling_rate, 125 | ) 126 | if start > end: 127 | continue 128 | # mark any empty segment that is not very short 129 | if start > prev_end + 1.0: 130 | _add_sub(prev_end, start, "< No Speech >") 131 | _add_sub(start, end, s["text"]) 132 | prev_end = end 133 | 134 | with open(output, "wb") as f: 135 | f.write(srt.compose(subs).encode(self.args.encoding, "replace")) 136 | 137 | def _save_md(self, md_fn, srt_fn, video_fn): 138 | with open(srt_fn, encoding=self.args.encoding) as f: 139 | subs = srt.parse(f.read()) 140 | 141 | md = utils.MD(md_fn, self.args.encoding) 142 | md.clear() 143 | md.add_done_editing(False) 144 | md.add_video(os.path.basename(video_fn)) 145 | md.add( 146 | f"\nTexts generated from [{os.path.basename(srt_fn)}]({os.path.basename(srt_fn)})." 147 | "Mark the sentences to keep for autocut.\n" 148 | "The format is [subtitle_index,duration_in_second] subtitle context.\n\n" 149 | ) 150 | 151 | for s in subs: 152 | sec = s.start.seconds 153 | pre = f"[{s.index},{sec // 60:02d}:{sec % 60:02d}]" 154 | md.add_task(False, f"{pre:11} {s.content.strip()}") 155 | md.write() 156 | -------------------------------------------------------------------------------- /autocut/utils.py: -------------------------------------------------------------------------------- 1 | import logging 2 | import os 3 | import re 4 | 5 | import srt 6 | import opencc 7 | 8 | 9 | def is_video(filename): 10 | _, ext = os.path.splitext(filename) 11 | return ext in [".mp4", ".mov", ".mkv", ".avi", ".flv", ".f4v", ".webm"] 12 | 13 | 14 | def is_audio(filename): 15 | _, ext = os.path.splitext(filename) 16 | return ext in [".ogg", ".wav", ".mp3", ".flac", ".m4a"] 17 | 18 | 19 | def change_ext(filename, new_ext): 20 | # Change the extension of filename to new_ext 21 | base, _ = os.path.splitext(filename) 22 | if not new_ext.startswith("."): 23 | new_ext = "." + new_ext 24 | return base + new_ext 25 | 26 | 27 | def add_cut(filename): 28 | # Add cut mark to the filename 29 | base, ext = os.path.splitext(filename) 30 | if base.endswith("_cut"): 31 | base = base[:-4] + "_" + base[-4:] 32 | else: 33 | base += "_cut" 34 | return base + ext 35 | 36 | 37 | # a very simple markdown parser 38 | class MD: 39 | def __init__(self, filename, encoding): 40 | self.lines = [] 41 | self.EDIT_DONE_MAKR = "<-- Mark if you are done editing." 42 | self.encoding = encoding 43 | self.filename = filename 44 | if filename: 45 | self.load_file() 46 | 47 | def load_file(self): 48 | if os.path.exists(self.filename): 49 | with open(self.filename, encoding=self.encoding) as f: 50 | self.lines = f.readlines() 51 | 52 | def clear(self): 53 | self.lines = [] 54 | 55 | def write(self): 56 | with open(self.filename, "wb") as f: 57 | f.write("\n".join(self.lines).encode(self.encoding, "replace")) 58 | 59 | def tasks(self): 60 | # get all tasks with their status 61 | ret = [] 62 | for l in self.lines: 63 | mark, task = self._parse_task_status(l) 64 | if mark is not None: 65 | ret.append((mark, task)) 66 | return ret 67 | 68 | def done_editing(self): 69 | for m, t in self.tasks(): 70 | if m and self.EDIT_DONE_MAKR in t: 71 | return True 72 | return False 73 | 74 | def add(self, line): 75 | self.lines.append(line) 76 | 77 | def add_task(self, mark, contents): 78 | self.add(f'- [{"x" if mark else " "}] {contents.strip()}') 79 | 80 | def add_done_editing(self, mark): 81 | self.add_task(mark, self.EDIT_DONE_MAKR) 82 | 83 | def add_video(self, video_fn): 84 | ext = os.path.splitext(video_fn)[1][1:] 85 | self.add( 86 | f'\n\n' 87 | ) 88 | 89 | def _parse_task_status(self, line): 90 | # return (is_marked, rest) or (None, line) if not a task 91 | m = re.match(r"- +\[([ x])\] +(.*)", line) 92 | if not m: 93 | return None, line 94 | return m.groups()[0].lower() == "x", m.groups()[1] 95 | 96 | 97 | def check_exists(output, force): 98 | if os.path.exists(output): 99 | if force: 100 | logging.info(f"{output} exists. Will overwrite it") 101 | else: 102 | logging.info( 103 | f"{output} exists, skipping... Use the --force flag to overwrite" 104 | ) 105 | return True 106 | return False 107 | 108 | 109 | def expand_segments(segments, expand_head, expand_tail, total_length): 110 | # Pad head and tail for each time segment 111 | results = [] 112 | for i in range(len(segments)): 113 | t = segments[i] 114 | start = max(t["start"] - expand_head, segments[i - 1]["end"] if i > 0 else 0) 115 | end = min( 116 | t["end"] + expand_tail, 117 | segments[i + 1]["start"] if i < len(segments) - 1 else total_length, 118 | ) 119 | results.append({"start": start, "end": end}) 120 | return results 121 | 122 | 123 | def remove_short_segments(segments, threshold): 124 | # Remove segments whose length < threshold 125 | return [s for s in segments if s["end"] - s["start"] > threshold] 126 | 127 | 128 | def merge_adjacent_segments(segments, threshold): 129 | # Merge two adjacent segments if their distance < threshold 130 | results = [] 131 | i = 0 132 | while i < len(segments): 133 | s = segments[i] 134 | for j in range(i + 1, len(segments)): 135 | if segments[j]["start"] < s["end"] + threshold: 136 | s["end"] = segments[j]["end"] 137 | i = j 138 | else: 139 | break 140 | i += 1 141 | results.append(s) 142 | return results 143 | 144 | 145 | def compact_rst(sub_fn, encoding): 146 | cc = opencc.OpenCC("t2s") 147 | 148 | base, ext = os.path.splitext(sub_fn) 149 | COMPACT = "_compact" 150 | if ext != ".srt": 151 | logging.fatal("only .srt file is supported") 152 | 153 | if base.endswith(COMPACT): 154 | # to original rst 155 | with open(sub_fn, encoding=encoding) as f: 156 | lines = f.readlines() 157 | subs = [] 158 | for l in lines: 159 | items = l.split(" ") 160 | if len(items) < 4: 161 | continue 162 | subs.append( 163 | srt.Subtitle( 164 | index=0, 165 | start=srt.srt_timestamp_to_timedelta(items[0]), 166 | end=srt.srt_timestamp_to_timedelta(items[2]), 167 | content=" ".join(items[3:]).strip(), 168 | ) 169 | ) 170 | with open(base[: -len(COMPACT)] + ext, "wb") as f: 171 | f.write(srt.compose(subs).encode(encoding, "replace")) 172 | else: 173 | # to a compact version 174 | with open(sub_fn, encoding=encoding) as f: 175 | subs = srt.parse(f.read()) 176 | with open(base + COMPACT + ext, "wb") as f: 177 | for s in subs: 178 | f.write( 179 | f"{srt.timedelta_to_srt_timestamp(s.start)} --> {srt.timedelta_to_srt_timestamp(s.end)} " 180 | f"{cc.convert(s.content.strip())}\n".encode(encoding, "replace") 181 | ) 182 | 183 | 184 | def trans_srt_to_md(encoding, force, srt_fn, video_fn=None): 185 | base, ext = os.path.splitext(srt_fn) 186 | if ext != ".srt": 187 | logging.fatal("only .srt file is supported") 188 | md_fn = base + ext.split(".")[0] + ".md" 189 | 190 | check_exists(md_fn, force) 191 | 192 | with open(srt_fn, encoding=encoding) as f: 193 | subs = srt.parse(f.read()) 194 | 195 | md = MD(md_fn, encoding) 196 | md.clear() 197 | md.add_done_editing(False) 198 | if video_fn: 199 | if not is_video(video_fn): 200 | logging.fatal(f"{video_fn} may not be a video") 201 | md.add_video(os.path.basename(video_fn)) 202 | md.add( 203 | f"\nTexts generated from [{os.path.basename(srt_fn)}]({os.path.basename(srt_fn)})." 204 | "Mark the sentences to keep for autocut.\n" 205 | "The format is [subtitle_index,duration_in_second] subtitle context.\n\n" 206 | ) 207 | 208 | for s in subs: 209 | sec = s.start.seconds 210 | pre = f"[{s.index},{sec // 60:02d}:{sec % 60:02d}]" 211 | md.add_task(False, f"{pre:11} {s.content.strip()}") 212 | md.write() 213 | -------------------------------------------------------------------------------- /imgs/typora.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/lewangdev/autocut/e631c342d61004309ca6f7ab30aee5c30d25e354/imgs/typora.jpg -------------------------------------------------------------------------------- /setup.cfg: -------------------------------------------------------------------------------- 1 | [metadata] 2 | name = autocut 3 | version = attr: autocut.__version__ 4 | license = Apache Software License 5 | description = Cut video by subtitles 6 | long_description = file: README.md 7 | classifiers = 8 | License :: OSI Approved :: Apache Software License 9 | Operating System :: OS Independent 10 | Programming Language :: Python :: 3 11 | 12 | [options] 13 | packages = find: 14 | include_package_data = True 15 | python_requires = >= 3.9 16 | -------------------------------------------------------------------------------- /setup.py: -------------------------------------------------------------------------------- 1 | from setuptools import setup, find_packages 2 | 3 | requirements = [ 4 | "srt", 5 | "moviepy", 6 | "opencc-python-reimplemented", 7 | "torchaudio", 8 | "parameterized", 9 | "faster-whisper", 10 | "tqdm", 11 | ] 12 | 13 | 14 | setup( 15 | name="autocut", 16 | install_requires=requirements, 17 | packages=find_packages(), 18 | entry_points={ 19 | "console_scripts": [ 20 | "autocut = autocut.main:main", 21 | ] 22 | }, 23 | ) 24 | -------------------------------------------------------------------------------- /test/config.py: -------------------------------------------------------------------------------- 1 | import logging 2 | import os 3 | 4 | # 定义一个日志收集器 5 | logger = logging.getLogger() 6 | # 设置收集器的级别，不设定的话，默认收集warning及以上级别的日志 7 | logger.setLevel("DEBUG") 8 | # 设置日志格式 9 | fmt = logging.Formatter("%(filename)s-%(lineno)d-%(asctime)s-%(levelname)s-%(message)s") 10 | # 设置日志处理器-输出到文件,并且设置编码格式 11 | if not os.path.exists("./log"): 12 | os.makedirs("./log") 13 | file_handler = logging.FileHandler("./log/log.txt", encoding="utf-8") 14 | # 设置日志处理器级别 15 | file_handler.setLevel("DEBUG") 16 | # 处理器按指定格式输出日志 17 | file_handler.setFormatter(fmt) 18 | # 输出到控制台 19 | ch = logging.StreamHandler() 20 | # 设置日志处理器级别 21 | ch.setLevel("DEBUG") 22 | # 处理器按指定格式输出日志 23 | ch.setFormatter(fmt) 24 | # 收集器和处理器对接，指定输出渠道 25 | # 日志输出到文件 26 | logger.addHandler(file_handler) 27 | # 日志输出到控制台 28 | logger.addHandler(ch) 29 | 30 | TEST_MEDIA_PATH = "./test/media/" 31 | TEST_CONTENT_PATH = "./test/content/" 32 | TEST_MEDIA_FILE = [ 33 | "test001.mp4", 34 | "test002.mov", 35 | "test003.mkv", 36 | "test004.flv", 37 | "test005.mp3", 38 | ] 39 | 40 | TEST_MEDIA_FILE_LANG = ["test001_en.mp4"] 41 | TEST_MEDIA_FILE_SIMPLE = ["test001.mp4", "test005.mp3"] 42 | 43 | 44 | class TestArgs: 45 | def __init__( 46 | self, 47 | encoding="utf-8", 48 | sampling_rate=16000, 49 | bitrate="10m", 50 | lang="zh", 51 | prompt="", 52 | whisper_model="tiny", 53 | device='cpu', 54 | vad=False, 55 | force=False, 56 | ): 57 | self.inputs = [] 58 | self.bitrate = bitrate 59 | self.encoding = encoding 60 | self.sampling_rate = sampling_rate 61 | self.lang = lang 62 | self.prompt = prompt 63 | self.whisper_model = whisper_model 64 | self.device = device 65 | self.vad = vad 66 | self.force = force 67 | -------------------------------------------------------------------------------- /test/content/test.srt: -------------------------------------------------------------------------------- 1 | 1 2 | 00:00:00,000 --> 00:00:05,000 3 | 大家好,我的名字是AutoCut.这是一条用于测试的视频。 4 | 5 | 2 6 | 00:00:05,000 --> 00:00:10,260 7 | Hello, my name is AutoCut. This is a video for testing. 8 | 9 | -------------------------------------------------------------------------------- /test/content/test_md.md: -------------------------------------------------------------------------------- 1 | - [x] <-- Mark if you are done editing. 2 | 3 | 4 | 5 | Texts generated from [test001.srt](test001.srt).Mark the sentences to keep for autocut. 6 | The format is [subtitle_index,duration_in_second] subtitle context. 7 | 8 | - [ ] [1,00:00] 大家好,我的名字是AutoCut.这是一条用于测试的视频。 9 | - [x] [2,00:05] Hello, my name is AutoCut. This is a video for testing. 10 | -------------------------------------------------------------------------------- /test/content/test_srt.srt: -------------------------------------------------------------------------------- 1 | 1 2 | 00:00:00,000 --> 00:00:05,000 3 | 大家好,我的名字是AutoCut.这是一条用于测试的视频。 4 | 5 | -------------------------------------------------------------------------------- /test/media/test001.mp4: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/lewangdev/autocut/e631c342d61004309ca6f7ab30aee5c30d25e354/test/media/test001.mp4 -------------------------------------------------------------------------------- /test/media/test001_en.mp4: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/lewangdev/autocut/e631c342d61004309ca6f7ab30aee5c30d25e354/test/media/test001_en.mp4 -------------------------------------------------------------------------------- /test/media/test002.mov: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/lewangdev/autocut/e631c342d61004309ca6f7ab30aee5c30d25e354/test/media/test002.mov -------------------------------------------------------------------------------- /test/media/test003.mkv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/lewangdev/autocut/e631c342d61004309ca6f7ab30aee5c30d25e354/test/media/test003.mkv -------------------------------------------------------------------------------- /test/media/test004.flv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/lewangdev/autocut/e631c342d61004309ca6f7ab30aee5c30d25e354/test/media/test004.flv -------------------------------------------------------------------------------- /test/media/test005.mp3: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/lewangdev/autocut/e631c342d61004309ca6f7ab30aee5c30d25e354/test/media/test005.mp3 -------------------------------------------------------------------------------- /test/test_cut.py: -------------------------------------------------------------------------------- 1 | import logging 2 | import os 3 | import unittest 4 | 5 | from parameterized import parameterized, param 6 | 7 | from autocut.cut import Cutter 8 | from config import TestArgs, TEST_MEDIA_PATH, TEST_MEDIA_FILE_SIMPLE, TEST_CONTENT_PATH 9 | 10 | 11 | class TestCut(unittest.TestCase): 12 | @classmethod 13 | def setUpClass(cls): 14 | logging.info("检查测试文件是否正常存在") 15 | scan_file = os.listdir(TEST_MEDIA_PATH) 16 | logging.info( 17 | "应存在文件列表：" + str(TEST_MEDIA_FILE_SIMPLE) + " 扫描到文件列表：" + str(scan_file) 18 | ) 19 | for file in TEST_MEDIA_FILE_SIMPLE: 20 | assert file in scan_file 21 | 22 | def tearDown(self): 23 | for file in TEST_MEDIA_FILE_SIMPLE: 24 | namepart = os.path.join( 25 | TEST_MEDIA_PATH, os.path.splitext(file)[0] + "_cut." 26 | ) 27 | if os.path.exists(namepart + "mp4"): 28 | os.remove(namepart + "mp4") 29 | if os.path.exists(namepart + "mp3"): 30 | os.remove(namepart + "mp3") 31 | 32 | @parameterized.expand([param(file) for file in TEST_MEDIA_FILE_SIMPLE]) 33 | def test_srt_cut(self, file_name): 34 | args = TestArgs() 35 | args.inputs = [ 36 | os.path.join(TEST_MEDIA_PATH, file_name), 37 | os.path.join(TEST_CONTENT_PATH, "test_srt.srt"), 38 | ] 39 | cut = Cutter(args) 40 | cut.run() 41 | namepart = os.path.join( 42 | TEST_MEDIA_PATH, os.path.splitext(file_name)[0] + "_cut." 43 | ) 44 | self.assertTrue( 45 | os.path.exists(namepart + "mp4") or os.path.exists(namepart + "mp3") 46 | ) 47 | 48 | @parameterized.expand([param(file) for file in TEST_MEDIA_FILE_SIMPLE]) 49 | def test_md_cut(self, file_name): 50 | args = TestArgs() 51 | args.inputs = [ 52 | TEST_MEDIA_PATH + file_name, 53 | os.path.join(TEST_CONTENT_PATH, "test.srt"), 54 | os.path.join(TEST_CONTENT_PATH, "test_md.md"), 55 | ] 56 | cut = Cutter(args) 57 | cut.run() 58 | namepart = os.path.join( 59 | TEST_MEDIA_PATH, os.path.splitext(file_name)[0] + "_cut." 60 | ) 61 | self.assertTrue( 62 | os.path.exists(namepart + "mp4") or os.path.exists(namepart + "mp3") 63 | ) 64 | -------------------------------------------------------------------------------- /test/test_transcribe.py: -------------------------------------------------------------------------------- 1 | import logging 2 | import os 3 | import unittest 4 | 5 | from parameterized import parameterized, param 6 | 7 | from autocut.utils import MD 8 | from config import ( 9 | TEST_MEDIA_FILE, 10 | TestArgs, 11 | TEST_MEDIA_FILE_SIMPLE, 12 | TEST_MEDIA_FILE_LANG, 13 | TEST_MEDIA_PATH, 14 | ) 15 | from autocut.transcribe import Transcribe 16 | 17 | 18 | class TestTranscribe(unittest.TestCase): 19 | @classmethod 20 | def setUpClass(cls): 21 | logging.info("检查测试文件是否正常存在") 22 | scan_file = os.listdir(TEST_MEDIA_PATH) 23 | logging.info( 24 | "应存在文件列表：" 25 | + str(TEST_MEDIA_FILE) 26 | + str(TEST_MEDIA_FILE_LANG) 27 | + str(TEST_MEDIA_FILE_SIMPLE) 28 | + " 扫描到文件列表：" 29 | + str(scan_file) 30 | ) 31 | for file in TEST_MEDIA_FILE: 32 | assert file in scan_file 33 | for file in TEST_MEDIA_FILE_LANG: 34 | assert file in scan_file 35 | for file in TEST_MEDIA_FILE_SIMPLE: 36 | assert file in scan_file 37 | 38 | @classmethod 39 | def tearDownClass(cls): 40 | for file in os.listdir(TEST_MEDIA_PATH): 41 | if file.endswith("md") or file.endswith("srt"): 42 | os.remove(TEST_MEDIA_PATH + file) 43 | 44 | def tearDown(self): 45 | for file in TEST_MEDIA_FILE_SIMPLE: 46 | if os.path.exists(TEST_MEDIA_PATH + file.split(".")[0] + ".md"): 47 | os.remove(TEST_MEDIA_PATH + file.split(".")[0] + ".md") 48 | if os.path.exists(TEST_MEDIA_PATH + file.split(".")[0] + ".srt"): 49 | os.remove(TEST_MEDIA_PATH + file.split(".")[0] + ".srt") 50 | 51 | @parameterized.expand([param(file) for file in TEST_MEDIA_FILE]) 52 | def test_default_transcribe(self, file_name): 53 | logging.info("检查默认参数生成字幕") 54 | args = TestArgs() 55 | args.inputs = [TEST_MEDIA_PATH + file_name] 56 | transcribe = Transcribe(args) 57 | transcribe.run() 58 | self.assertTrue( 59 | os.path.exists(TEST_MEDIA_PATH + file_name.split(".")[0] + ".md") 60 | ) 61 | 62 | @parameterized.expand([param(file) for file in TEST_MEDIA_FILE]) 63 | def test_jump_done_transcribe(self, file_name): 64 | logging.info("检查默认参数跳过生成字幕") 65 | args = TestArgs() 66 | args.inputs = [TEST_MEDIA_PATH + file_name] 67 | transcribe = Transcribe(args) 68 | transcribe.run() 69 | self.assertTrue( 70 | os.path.exists(TEST_MEDIA_PATH + file_name.split(".")[0] + ".md") 71 | ) 72 | 73 | @parameterized.expand([param(file) for file in TEST_MEDIA_FILE_LANG]) 74 | def test_en_transcribe(self, file_name): 75 | logging.info("检查--lang='en'参数生成字幕") 76 | args = TestArgs() 77 | args.lang = "en" 78 | args.inputs = [TEST_MEDIA_PATH + file_name] 79 | transcribe = Transcribe(args) 80 | transcribe.run() 81 | self.assertTrue( 82 | os.path.exists(TEST_MEDIA_PATH + file_name.split(".")[0] + ".md") 83 | ) 84 | 85 | @parameterized.expand([param(file) for file in TEST_MEDIA_FILE_LANG]) 86 | def test_force_transcribe(self, file_name): 87 | logging.info("检查--force参数生成字幕") 88 | args = TestArgs() 89 | args.force = True 90 | args.inputs = [TEST_MEDIA_PATH + file_name] 91 | md0_lens = len( 92 | "".join( 93 | MD( 94 | TEST_MEDIA_PATH + file_name.split(".")[0] + ".md", args.encoding 95 | ).lines 96 | ) 97 | ) 98 | transcribe = Transcribe(args) 99 | transcribe.run() 100 | md1_lens = len( 101 | "".join( 102 | MD( 103 | TEST_MEDIA_PATH + file_name.split(".")[0] + ".md", args.encoding 104 | ).lines 105 | ) 106 | ) 107 | self.assertLessEqual(md1_lens, md0_lens) 108 | 109 | @parameterized.expand([param(file) for file in TEST_MEDIA_FILE_SIMPLE]) 110 | def test_encoding_transcribe(self, file_name): 111 | logging.info("检查--encoding参数生成字幕") 112 | args = TestArgs() 113 | args.encoding = "gbk" 114 | args.inputs = [TEST_MEDIA_PATH + file_name] 115 | transcribe = Transcribe(args) 116 | transcribe.run() 117 | with open( 118 | os.path.join(TEST_MEDIA_PATH + file_name.split(".")[0] + ".md"), 119 | encoding="gbk", 120 | ): 121 | self.assertTrue(True) 122 | 123 | @parameterized.expand([param(file) for file in TEST_MEDIA_FILE_SIMPLE]) 124 | def test_vad_transcribe(self, file_name): 125 | logging.info("检查--vad参数生成字幕") 126 | args = TestArgs() 127 | args.force = True 128 | args.vad = True 129 | args.inputs = [TEST_MEDIA_PATH + file_name] 130 | transcribe = Transcribe(args) 131 | transcribe.run() 132 | self.assertTrue( 133 | os.path.exists(TEST_MEDIA_PATH + file_name.split(".")[0] + ".md") 134 | ) 135 | --------------------------------------------------------------------------------