mirror of
https://github.com/SHOGGOTH-SECTOR/sica-fondt.git
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24f816b6a3
Place useful parts of the surrounding repos into sica-fondt by layer, per the
body model (Ada = membrane; brain/endocrine/capabilities/knowledge non-Ada):
- brain/ LLM reasoning + providers (dapr, hermes, MoMoA)
- capabilities/ REPRAG sidecars: hermes tools/skills, dapr tools, parallel
dispatch, A51 channels, and the OSINT cluster
- knowledge/ LORAG corpus: 754 cyber-skills, agency personas, secure-coding,
MITRE ATT&CK data
- reference/ defensive threat-reference (C3, shhbruh doc) + AdaYaml parser
License handling: AGPL sources (worldosint, advanced_evolution, mercury,
Reticulum) and GPL DeTTECT are SPEC-only clean-room/port descriptions — no
copyleft code copied. MIT/Apache/data parts copied as working trees.
Safety: shhbruh escape/persistence material and C3 covert-C2 kept as reference
only, not wired into the running organism. See CONSOLIDATION.md.
https://claude.ai/code/session_01UehUqEXXJJCsHoA4voCU5c
2.2 KiB
2.2 KiB
| name | description | version | author | license | metadata | prerequisites | ||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| songsee | Audio spectrograms/features (mel, chroma, MFCC) via CLI. | 1.0.0 | community | MIT |
|
|
songsee
Generate spectrograms and multi-panel audio feature visualizations from audio files.
Prerequisites
Requires Go:
go install github.com/steipete/songsee/cmd/songsee@latest
Optional: ffmpeg for formats beyond WAV/MP3.
Quick Start
# 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
Visualization Types
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.
Common Flags
| 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 |
Notes
- WAV and MP3 are decoded natively; other formats require
ffmpeg - Output images can be inspected with
vision_analyzefor automated audio analysis - Useful for comparing audio outputs, debugging synthesis, or documenting audio processing pipelines