video-to-text

name video-to-text description Tool for extracting speech text from video with timestamps. Use when asked to transcribe video, extract subtitles, generate transcript from video, or convert video speech to text. Video to Text Extracts speech text from video files using OpenAI Whisper and outputs a transcript with timestamps. When to Use This Skill You need to extract spoken words from a video file You want a timestamped transcript for subtitles or analysis You need to convert video speech to text for further processing You have a video file and want to generate a text transcript Prerequisites Python 3.8+ ffmpeg installed and available in PATH Internet connection (for downloading Whisper models on first run) Usage The tool is located at tools/video-to-text/video-to-text.py . Command Line Arguments python video-to-text.py <VIDEO_PATH> <OUTPUT_DIR> VIDEO_PATH : Path to the input video file (supports most formats) OUTPUT_DIR : Directory where the transcript text file will be saved Example python tools/video-to-text/video-to-text.py "path/to/video.mp4" "output/folder" The output file will be named after the video file (e.g., video.txt ) and placed in the output directory. Features Automatically creates output directory if it doesn't exist Extracts audio from video using ffmpeg (mono, 16kHz WAV) Transcribes using OpenAI Whisper (base model by default) Outputs timestamps in HH:mm:ss format Handles various video formats supported by ffmpeg Clean error messages and progress indicators Output Format Each line in the output text file has the format: [HH:mm:ss] Transcribed text here Example: [00:00:00] Hello world [00:00:02] This is a test Troubleshooting Unicode Path Issues on Windows If the video file path contains non-ASCII characters (e.g., Japanese, Chinese), you may encounter encoding issues on Windows command prompt. Consider: Renaming the file to use ASCII characters Using short paths (8.3 format) Running from PowerShell or WSL ffmpeg Not Found Ensure ffmpeg is installed and available in your PATH. You can test with: ffmpeg -version Whisper Model Download Failures The first run downloads the Whisper model (base, ~150MB). Ensure you have internet connectivity and sufficient disk space. Performance Transcription speed depends on video length and CPU. For long videos, consider using a smaller model (edit script to use "tiny" or "small"). Customization You can modify the script to use different Whisper models by changing the line: model = whisper.load_model( "base" ) # Change to "tiny", "small", "medium", "large" References OpenAI Whisper FFmpeg MoviePy