Turn audio files into spectrograms, images showing frequencies over time, and charts of loudness, pitch, tempo, and other features. Combine several views in one image or visualize a selected time segment for comparison.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Audio spectrograms/features (mel, chroma, MFCC) via CLI.
설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Generate spectrograms and multi-panel audio feature visualizations from audio files.
Requires Go:
go install github.com/steipete/songsee/cmd/songsee@latest
Optional: ffmpeg for formats beyond WAV/MP3.
# Basic spectrogram
songsee track.mp3
# Save to specific file
songsee track.mp3 -o spectrogram.png
# Multi-panel visualization grid
songsee track.mp3 --viz spectrogram,mel,chroma,hpss,selfsim,loudness,tempogram,mfcc,flux
# Time slice (start at 12.5s, 8s duration)
songsee track.mp3 --start 12.5 --duration 8 -o slice.jpg
# From stdin
cat track.mp3 | songsee - --format png -o out.png
Use --viz with comma-separated values:
| Type | Description |
|---|---|
spectrogram | Standard frequency spectrogram |
mel | Mel-scaled spectrogram |
chroma | Pitch class distribution |
hpss | Harmonic/percussive separation |
selfsim | Self-similarity matrix |
loudness | Loudness over time |
tempogram | Tempo estimation |
mfcc | Mel-frequency cepstral coefficients |
flux | Spectral flux (onset detection) |
Multiple --viz types render as a grid in a single image.
| Flag | Description |
|---|---|
--viz | Visualization types (comma-separated) |
--style | Color palette: classic, magma, inferno, viridis, gray |
--width / --height | Output image dimensions |
--window / --hop | FFT window and hop size |
--min-freq / --max-freq | Frequency range filter |
--start / --duration | Time slice of the audio |
--format | Output format: jpg or png |
-o | Output file path |
ffmpegvision_analyze for automated audio analysis아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
Set up the 1Password CLI and use stored passwords or API keys in commands and configuration templates. Choose an authentication method, retrieve secret references, and pass credentials to processes through environment variables.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Build an Excel workbook linking the income statement, balance sheet, and cash flow statement. Populate historical figures, create formula-based forecasts, compare scenarios, and check that balances and cash totals agree across all three statements.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Adapt existing PyTorch training scripts to use multiple GPUs or machines with limited code changes. The skill guides configuration, launch commands, mixed precision, which uses lower-precision numbers, and DeepSpeed or FSDP settings for distributing training work and memory.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Configure Hermes to run AI models through Actual Computer on your own hardware. Set up either the hosted relay or a local connection, select models, verify responses, and troubleshoot request errors or empty output.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Test an app from the perspective of a frustrated, less technical user. Find confusing steps and barriers, separate actionable usability problems from personal complaints, and produce screenshots, suggested fixes, and prioritized tickets.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Resolve Git merge conflicts between two agents by comparing both changes and their stated goals. Combine compatible work, explain choices where designs differ, and verify the merged result with project builds or tests.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.