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tiktok-whisper: tiktok-whisper-video-to-text-go

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About tiktok-whisper-video-to-text-go

demo_download_xiaoyuzhou

Batch convert videos to text using OpenAI's Whisper or the local coreML whisper.cpp.

The tiktok-whisper tool allows batch conversion of videos to text using either OpenAI's cloud-based Whisper API or local coreML's Whisper.cpp. It includes features such as exporting copies to Excel, saving conversion results to SQLite or PostgreSQL, video duration statistics, and keyword search to locate videos. It addresses the original whisper's limitations by offering solutions for macOS compatibility and speed enhancement.

Features

  • Input Xiaoyuzhou podcast links for batch audio downloading
  • Batch recognize audio or video, outputting text with timestamps
  • Save recognition results to SQLite or PostgreSQL
  • Use whisper_cpp + coreML for local transcription on macOS
  • Export historical recognition results

Quick Start

macOS

Tiktok-whipser is based on two whisper engines: local whisper_cpp and remote openai whisper API.

For local conversion using coreML on macOS, you need to modify binaryPath and modelPath direct to your local whisper_cpp.

If you have an API KEY, you can use OpenAI's cloud API for conversion; skip step 1,2,3 to step 4 for compilation.

  1. Generate coreML's model:
mkdir -p ~/workspace/cpp/ && cd ~/workspace/cpp/
git clone [email protected]:ggerganov/whisper.cpp.git
cd whisper.cpp
bash ./models/download-ggml-model.sh large
conda create -n whisper-cpp python=3.10 -y
conda activate whisper-cpp 
pip install -U ane_transformers openai-whisper coremltools
bash ./models/generate-coreml-model.sh large
make clean
WHISPER_COREML=1 make -j
  1. for using local whisper_cpp, you should modify the binaryPath and modelPath in tiktok-whisper/internal/app/wire.go manually.
func provideLocalTranscriber() api.Transcriber {
    // Modify binaryPath and modelPath to your paths here!
    binaryPath := "~/workspace/cpp/whisper.cpp/main"
    modelPath := "~/workspace/cpp/whisper.cpp/models/ggml-large-v2.bin"
    return whisper_cpp.NewLocalTranscriber(binaryPath, modelPath)
}
  1. Generate wire configuration and compile the executable:
cd ./internal/app
go install github.com/google/wire/cmd/wire@latest
wire
  1. Compile tiktok-whisper with CGO_ENABLED
cd tiktok-whisper
CGO_ENABLED=1 go build -o v2t ./cmd/v2t/main.go
./v2t help

Windows

The procedure is similar to macOS.

cd tiktok-whisper
go build -o v2t.exe .\cmd\v2t\main.go
.\v2t.exe help

Usage

Download audio from Xiaoyuzhou or video from TikTok

# Download Xiaoyuzhou audio using a single episode URL
./v2t download xiaoyuzhou -e "https://www.xiaoyuzhoufm.com/episode/6398c6ae3a2b7eba5ceb462f"

# Or using multiple episode URLs
./v2t download xiaoyuzhou -e "https://www.xiaoyuzhoufm.com/episode/6398c6ae3a2b7eba5ceb462f,https://www.xiaoyuzhoufm.com/episode/6445559d420fc63f0b9e5747"

# Download all episodes from a Xiaoyuzhou podcast URL
./v2t download xiaoyuzhou -p "https://www.xiaoyuzhoufm.com/podcast/61e389402454b42a2b06177c"

After downloading, you can find the files in the data directory:

$ tree data/
data/
└── xiaoyuzhou
    └── 硬地骇客
        └── EP21 程序员的职场晋升究竟与什么有关？漂亮的代码？.mp3

Use yt-dlp to download YouTube videos

To download only audio without video, use the following command:

yt-dlp --extract-audio --audio-format mp3 "https://www.youtube.com/watch?v=tWmNN87VvcE"

Convert videos/audios to text

On macOS, you can use whisper.cpp for audio conversion, ensuring the correct setup of binaryPath and modelPath in wire.go:

# Convert an

 audio file
./v2t convert -audio --input ./test/data/test.mp3

# Convert all files in a directory with a specified file extension
./v2t convert -audio --directory ./test/data --type m4a

# Convert all mp4 files in a specified directory to text, -n specifies the maximum number of files to convert, default n=1
./v2t convert --video --directory "./test/data/mp4" --userNickname "testUser" -n 100

# Export all recognition history of a specified user as excel
./v2t export --userNickname "testUser" --outputFilePath ./data/testUser.xlsx

To use OpenAI's API KEY for audio conversion, ensure OPENAI_API_KEY is set correctly in your environment variables and modify wire.go to use provideRemoteTranscriber:

func InitializeConverter() *converter.Converter {
-   wire.Build(converter.NewConverter, provideLocalTranscriber, provideTranscriptionDAO)
+   wire.Build(converter.NewConverter, provideRemoteTranscriber, provideTranscriptionDAO)
    return &converter.Converter{}
}

Using Python scripts for faster-whisper

If you are on Windows and have a dedicated GPU, you can use Python's faster-whisper for CUDA processing. There are two Python scripts for batch audio transcription:

  • whisperToText.py: Transcribes a single file or all files in a single directory.
  • whisperToTextParallel.py: Transcribes files in multiple subdirectories in parallel.

Before running the scripts, install the required Python packages:

pip install -r requirements.txt

For single file or directory transcription, and parallel transcription of multiple subdirectories, follow the provided commands in the documentation.

TODO

  • Video duration statistics
  • Keyword search to locate videos
  • Original video jump link
  • Like, share, and comment statistics
  • Use pgvector for vectorized search