
kieransimkin/stemlab
Developer toolsこのページは AI により自動翻訳されています。技術的な詳細は原文をご確認ください。 原文を見る
Local music analysis for stems, timing, beats, harmony, lyrics, MIDI and loopable sections for Shorts. https://kieransimkin.co.uk/
概要
Local music analysis for stems, timing, beats, harmony, lyrics, MIDI and loopable sections for Shorts. https://kieransimkin.co.uk/ The real-song reference timeline preserves its explicitly hash-pinned public detector JSON byte for byte, including newlines, on Windows and Linux. Generic exports still remove private paths. Container model weights and model-specific caches live under the owning project's ignored /opt/stemlab/models/ directory; they are excluded from the build context and source/package artifacts. the canonical project name is . StemLab is part of the project. The PyPI distribution is named danceflow-stemlab solely because Python package-registry names are globally unique. The Python import, CLI, GitHub repository and container image remain stemlab. Agents using StemLab should inspect its available capabilities, use them fully where they fit the task, and look for useful improvements wherever possible.
README
以下は原文 README の抜粋です。原文を見る。
StemLab
By Kieran Simkin · DanceFlow ecosystem · Vector logo and usage guide.
Local music analysis for stems, timing, beats, harmony, lyrics, MIDI and loopable sections for Shorts. https://kieransimkin.co.uk/
Canonical song example — Star Lights Glow (Mystery Liquid Kick)
examples/star-lights-glow-mystery-liquid-kick/ holds Bass Ben & Friends’
Star Lights Glow (Mystery Liquid Kick) as a verified 192 kbps CBR MP3
listening/analysis reference with the original supplied front-cover JPEG and ID3
metadata. The original lossless WAV remains the canonical source master,
identified by SHA-256 in evidence.json rather than redistributed as a second
large binary. The mix is separate from Star Lights Glow (Anthem); BPM, phase,
release date and ISRC are unconfirmed. Verify with
python scripts/verify_star_lights_reference.py and consult the example’s
README. The MIT code
licence does not license the music or artwork.
Independent beat finding and counting (experimental)
Tempo precision update: Classical autocorrelation and comb-filter lag peaks now retain their original 100 Hz integer-bin BPM while also reporting a bounded sub-frame estimate. Local tempo windows use the same refinement, and tempo families expose source-wide observed-onset-path coverage as a review diagnostic, not as calibrated confidence or automatic BPM approval. Predicted beats, observed onset candidates and inferred ordinal gaps remain distinct. See beat-evidence documentation.
stemlab compare-beats now compares model-free audio, N-dimensional
DanceRudiments recordings, rig captures and verified motion-package accents.
Five complementary classical rhythm decoders produce reviewable BPM, beat count,
phase, accent-cycle and local-tempo hypotheses. It can also import existing
Beat This!/BeatNet/Beat Transformer/All-In-One model result JSON without
re-running models; no model weights are downloaded. Cross-source phase scores
require explicit clock offsets. No inferred downbeat or predicted grid is
silently accepted as a real detection or canonical timeline. See
usage and evidence schema and the
model and implementation research roadmap.
The review now groups half/double tempo families rather than majority-voting
correlated algorithms, scores DP coverage across the original source, and fits
original saved model timestamps with robust residual/drift guards. Optional
--annotation NAME=FILE evaluates beat timing only against a matching,
human-reviewed, SHA-bound annotation; separately-held-out reliability calibration
推奨ツール
別のキーワードを試すか、フィルタを外してください。
インストール
npx skillfish add kieransimkin/stemlab