5df802a574
Reuses the analysis backend unchanged. metrics.py already split compute() from build_spec(), and plotspec.PlotSpec is backend-agnostic, so the web UI reimplements only the renderer: uPlot for curves/bands, a canvas for the spectrogram heatmap. No PyQt5, pyqtgraph or matplotlib on the web path. Uploaded audio is never persisted on the host. The browser copies each file into Origin Private File System (sandboxed browser storage) and streams the bytes to the server per request; the server spools each body to a temp file, decodes, computes, and unlinks it in a finally before responding. There is no upload directory, no cache of audio, and no session state keyed on a path: file_id is the SHA-256 of the audio, so re-sending a master for another metric reuses the first decode. Verified: a spool is observable mid-request and gone after the response. Being precise: the bytes do have to reach the server, since librosa decodes from a path and the analysis is CPU-bound numpy/scipy. The claim is that running this does not accumulate masters on the host, not that audio is never on the machine mid-request. New: metrics_json.py PlotSpec/metric data -> JSON (the renderer seam) web_session.py headless analysis session, content-addressed tracks webapp.py FastAPI routes, raw-body analysis, ujm-web entry point static/ browser front end + test suite scripts/webapi_smoke.py 61 end-to-end assertions against a running server Also fixes a bug the direct-uvicorn dev loop had hidden: the CLI advertises logger_setup's WARN level but passed it straight to uvicorn, which only knows 'warning' -- `ujm-web --log-level WARN` died with KeyError: 'warn'. Removes an earlier /api/collect debug route that served every source module over HTTP. pyproject: 'web' extra (fastapi, uvicorn, python-multipart), package-data for static/, Apache-2.0 licence.
324 lines
16 KiB
Markdown
324 lines
16 KiB
Markdown
# uj-mastering-master
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A custom mastering toolkit that provides metrics to evaluate audio masterings through visual analysis.
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## Current implementation
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### Core features
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- **Audio Analysis**: Uses librosa to analyze audio files (MP3/WAV/FLAC support) at native sample rate (no resampling)
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- **Pluggable Metrics**: Switchable visualizations (RMS Power, Waveform, LUFS, Crest Factor, PSR, True Peak, Spectrogram; DR next) via a `Metric` ABC
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- **Metadata Extraction**: Reads ID3 tags from MP3 files for better file identification
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- **Modular GUI Architecture**: Complete PyQt5 interface with drag-and-drop and file dialog support
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- **Font Management**: CJK-capable, fixed UI font (M PLUS 1 Code @ 10pt) with system fallback
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- **Threading & Logging**: Robust background processing with detailed logging system
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### Technical stack
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- **Audio Processing**: librosa, numpy
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- **Visualization**: pyqtgraph — persistent, interactive (mouse zoom/pan, lin/log
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toggle, multi-dataset overlay). matplotlib remains only for its colormaps
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(consumed by pyqtgraph) and as a librosa dependency
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- **GUI Framework**: PyQt5 with modular widget architecture
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- **Metadata**: mutagen for audio tag reading
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- **Font Support**: Custom font loading system with CJK fallback
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### Key components
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#### `main.py`
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- Complete GUI application with modular architecture
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- Drag-and-drop and file dialog support for audio files
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- Integrated font control system
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- Real-time analysis display and file management
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#### `analysis_results_manager.py`
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- Background threading for audio analysis (`AudioAnalysisWorker` = load + first
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metric; `MetricComputeWorker` = one metric on an already-loaded file)
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- Caches both the loaded `AudioFile` and per-metric `compute()` output, so
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metric/font switches re-render from cache without reloading librosa
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- **Prefetch** (`PrefetchWorker`): after a file loads, the remaining metrics are
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computed in the background (one at a time, cooperatively cancellable) so the
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first switch to any metric is instant too. Superseded when a new file loads
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- Timing: workers measure compute time; `metricTiming` + phase/duration progress
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messages drive the status slip ("X computed in Ys", "Loaded in Ns — computing…")
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- `shutdown()` stops all threads on window close (`MainWindow.closeEvent`)
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#### `audio_visualization_widget.py`
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- Persistent pyqtgraph plot — the PlotItem is reused across renders, never torn
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down, so mouse zoom/pan and scale toggles survive every redraw
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- `show_specs([(label, PlotSpec), ...], view)` draws one or more datasets onto
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the shared axes, assigning a distinct colour per dataset for overlay/compare
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- Spectrogram log-frequency is realised by resampling STFT rows onto a log grid
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(`ImageItem` is affine-only and won't follow a log axis) — see `_render_heatmap`
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#### `plotspec.py`
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- Backend-agnostic drawing descriptors: `Curve`, `Band`, `HLine`, `Heatmap`,
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`AxisSpec`, `PlotSpec`, plus the `ViewState` (recompute-free lin/log options)
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- The seam that decouples metrics from the plotting library: metrics emit
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*intent*, the renderer owns colour/layout/library specifics
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#### `font_manager.py`
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- Auto-detection of custom fonts from `fonts/` directory; CJK fallbacks
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- `apply_fixed_font(family, size)` locks the Qt app font (used at startup to pin
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the UI to **M PLUS 1 Code @ 10pt**, falling back to the system default if the
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family isn't found). There is no runtime font picker — the old
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`font_control_widget.py` was removed as wasted panel space
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- pyqtgraph and the Qt widgets both read the app font, so this covers the plot
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too (M PLUS 1 Code has full Japanese coverage, so titles stay CJK-safe)
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#### `plot_control_widget.py`
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- Metric selector dropdown driven by the `metrics.METRICS` registry
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- Log-frequency toggle and a time-axis mode selector — Absolute (seconds) vs
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Relative (% of each track's own length) — both view-state, recompute-free
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- `Refresh Plot` button. Compare/overlay membership is the file-list checkboxes;
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reference lines have their own cluster
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#### `ref_line_widget.py`
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- `RefLineControlWidget`: side-panel list of custom reference lines with
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Add / Edit… / Remove / Clear; a pure view over the `RefLineProps` list the
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main window owns, emitting intents
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- `RefLineDialog`: edits one line's value, colour, line style, and tag
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- The plot draws each line with a triangle drag-handle; dragging writes the new
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value back into the shared `RefLineProps` and refreshes the list
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#### `metrics.py`
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- Pluggable `Metric` ABC: `compute(audio_file) -> data` (heavy, worker thread,
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backend-neutral numpy/scalars) and `build_spec(data, view) -> PlotSpec` (cheap,
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GUI thread, view-aware). Metrics no longer touch the plotting library
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- Compute-time vs view-time split: scale (lin/log) is a `ViewState` argument to
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`build_spec`, so toggling it never recomputes
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- Current registry:
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- `RMSPowerMetric` — 10 s rolling RMS with adaptive colour scale
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- `WaveformMetric` — min/max envelope, fixed ±1.1 y-range
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- `LUFSMetric` — true (ungated) EBU R128 short-term (3 s) via a single
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K-weighting pass (`_kweight`, cached) + a vectorised sliding mean-square.
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Integrated (`_integrated_lufs`) and LRA (`_loudness_range`) are reimplemented
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from the same cached K-weighted signal — validated **bit-equal** to
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pyloudnorm — so nothing re-filters the signal. ~3.8 s → ~0.6 s. pyloudnorm is
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now used only to source the BS.1770 filter coefficients
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- `CrestFactorMetric` — 20·log10(peak/RMS) per 1 s window; peaks via O(N) running max
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- `PSRMetric` — sample-peak minus short-term LUFS (3 s window); reuses
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`LUFSMetric`'s short-term series (memoised on the `AudioFile`), so PSR is
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near-free once LUFS is computed
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- `TruePeakMetric` — 4× oversampled dBTP; the whole signal is oversampled once
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(`scipy.signal.resample_poly`) then an O(N) running max over windows
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- `SpectrogramMetric` — log-frequency STFT heatmap; adaptive hop caps time
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bins at ~4000, `N_FFT=4096`. Log/linear frequency is a view toggle
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- Drop in new ones (DR, spectral balance) by appending an instance to `METRICS`;
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return a `PlotSpec` from `build_spec` (curves overlay automatically; heatmaps
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show one dataset at a time)
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- Note: the old matplotlib `_show_axis_extents` exact-endpoint tick labelling is
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gone with the matplotlib render path. If wanted back, it belongs in the
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renderer, applied uniformly to every metric — not per-metric
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#### `web_session.py`
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- Server-side equivalent of `AnalysisResultsManager`, without Qt: owns the
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per-track metric cache and the overlay set, and mirrors the desktop's
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compute-off-the-request-thread behaviour
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- **No audio is stored.** Tracks are keyed by `file_id` = SHA-256 of the audio,
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and the session keeps only analysis results and metadata. There is no upload
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directory and no cache of bytes
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- Because the key is a content hash, re-sending the same master for a second
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metric reuses the first decode — the client only re-uploads what the server has
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never seen (checked via `metrics_cached`)
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#### `webapp.py`
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- FastAPI routes + static mount + the `ujm-web` entry point (binds loopback by
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default; `--host`/`--port`/`--open` to override)
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- Analysis endpoints take the audio as a **raw request body**, not a multipart
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upload: spool to a temp file, `SESSION.observe(...)`, unlink in `finally`. The
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bytes exist on disk only for the duration of that one request
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- `POST /api/analyse` (analyse + plot data), `POST /api/file` (register without
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plotting), `DELETE /api/file`, `POST /api/overlay`, `GET /api/plot`,
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`GET /api/metadata`, `GET /api/metrics`, `GET /api/session`
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#### `metrics_json.py`
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- The renderer seam: `PlotSpec`/metric data → JSON, so a non-pyqtgraph renderer
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consumes the identical spec (curves, bands, hlines, heatmap, axis specs) that
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the desktop widget draws. `hlines` carry the integrated LUFS reference line —
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it is not an annotation
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#### `static/` (web front end)
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- `audio-store.js` — OPFS store. Copies each picked/dropped `File` into Origin
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Private File System (browser-sandboxed, not the host's filesystem), hashes it
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with WebCrypto in chunks while streaming (never loads a whole master into
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memory), and re-sends bytes to the server per metric
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- `app.js` — the web renderer, an ES module importing the store. Draws the same
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`PlotSpec` the desktop does: uPlot for curves/bands, a plain canvas for the
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spectrogram heatmap (a canvas can map rows through an arbitrary function, so it
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draws native linear rows and maps them, unlike pyqtgraph's affine-only
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`ImageItem`). Mirrors the desktop's per-metric colour cycle, lin/log toggles,
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absolute/relative time, and draggable reference lines
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- `vendor/` — uPlot 1.6.32 (IIFE + CSS), vendored so nothing is fetched from a
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CDN at runtime
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- Boot rehydrates: the server still has the last session's analysis, so it
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re-offers audio only for metric/track combinations the server reports as
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uncached, and reports unavailable combinations rather than faking them
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#### `master_core.py`
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- Defines the `AudioFile` class: librosa loading, rolling RMS power. BPM detection
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was **removed** — `librosa.beat.beat_track` cost ~3.7 s on every load for a
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number no better than tapping by hand
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- Loads at **native sample rate** (`librosa.load(..., sr=None)`) so the full
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band is preserved — analysis runs ~2× heavier on 44.1/48 kHz files than the
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old 22050 Hz default, by design
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- No batch / CLI mode — all analysis is driven from `main.py` via `AnalysisResultsManager`
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### Current analysis features
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- **Native-rate loading**: full-band analysis up to the file's own nyquist
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- **RMS power analysis**: 10-second rolling window with 2-second hops
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- **Adaptive colour mapping**: Automatically adjusts scale based on detected headroom
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- High dynamic range: 0-0.6 scale for loud masters
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- Conservative mastering: 0-0.3 scale for quiet masters
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- **Loudness metrics**: LUFS (ungated short-term + gated integrated + LRA), PSR, Crest Factor
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- **Peak analysis**: True Peak (4× oversampled dBTP)
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- **Spectral view**: log-frequency spectrogram heatmap over time
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- **Metadata display**: Artist and title from audio tags
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- **Real-time visualization**: Embedded matplotlib plots with font-aware rendering
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### GUI features
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- **File management**: Drag-and-drop and file dialog for audio selection
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- **Compare/overlay**: each analysed file has a checkbox; the ticked set is
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overlaid on one graph for the current metric (curve metrics overlay; the
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spectrogram shows one track at a time). Highlighting a row drives the metadata
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panel, independent of the overlay set
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- **Interactive plot**: mouse drag-zoom, scroll-wheel zoom, pan, right-click menu
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(pyqtgraph ViewBox); log/linear frequency toggle. Scroll zooms both axes;
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**Ctrl+scroll** zooms time only, **Shift+scroll** zooms the value axis only
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(`_AxisZoomViewBox`); scrolling over an axis also zooms just that axis
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- **Time-axis mode**: a Relative-time toggle — off = seconds, on = 0-100% of each
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track's own length, so tracks of very different durations line up by position
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- **Custom reference lines**: side-panel list (Add/Edit/Remove/Clear) of draggable
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horizontal markers with value/colour/style/tag; dragged via a triangle handle.
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Kept **per metric** (so switching metrics doesn't lose them) and expressed in
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the metric's own units — on the spectrogram they read and edit in **Hz** (the
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renderer converts Hz<->row index, since the heatmap y-axis is a row index)
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- **Plot control**: Metric selector + log-frequency toggle + relative-time toggle
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+ refresh-plot button
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- **Analysis display**: Real-time visualization with metadata panels
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- **Modular architecture**: Self-contained widgets for easy layout management
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## Future development plans
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### Short-term (urgent)
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1. **Plot control widget cluster** *(metric selector + Refresh Plot done; still TODO)*
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- Plot style controller (colormap, line vs bar, etc.)
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- Foundation for mastering comparison features
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### Short-term (not urgent)
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1. **Enhanced metrics** *(plug new ones into `metrics.METRICS`)*
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- Dynamic range measurement (DR meter)
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- Long-term average spectrum (LTAS) / tonal-balance curve
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- Stereo metrics (correlation, mid/side) — needs `AudioFile` to retain stereo
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2. **Interactive plot features** *(zoom/pan, axis-range select, lin/log done via
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pyqtgraph)*
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- GUI-controllable plotting styles (colormap, visualization type)
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- Export analysis results to CSV/JSON
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3. **Advanced GUI controls**
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- Plot style customization interface
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- Real-time axis range selection (zooming in/out)
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- Interactive plot manipulation tools
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4. **Better looking UI**
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- Graphical loading bar
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- Graphical logging text box
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### Mid-to-long-term (very not urgent)
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1. **Audio comparison system** *(multi-file overlay done via file-list checkboxes;
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each song has a stable palette colour keyed to its list row)*
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- Per-song colour picker: clickable swatch in the file list (overlay already
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accepts a caller-supplied colour per dataset via `show_specs`, so this is a
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UI + override-map addition, not a render change)
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- Reference vs. comparee designation (vs. flat overlay)
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- Side-by-side track comparison interface (incl. spectrogram, which can't overlay)
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- A/B testing for mastering versions
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2. **Distribution & deployment**
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- Self-contained executable releases
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- Cross-platform packaging
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- Installer creation and distribution
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### Future vision
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1. **Advanced analysis tools**
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- Spectral centroid and bandwidth analysis
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- Stereo width measurements
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- Transient detection and analysis
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- Harmonic distortion detection
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2. **Professional features**
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- EBU R128 compliance checking
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- Custom target curves
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- Professional reporting formats
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- Multi-format export capabilities
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3. **VST plugin development**
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- Real-time analysis during mixing/mastering
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- Integration with DAWs
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- Live feedback during production
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## Development notes
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### Dependencies
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- librosa: Audio analysis and feature extraction
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- numpy: Numerical computations
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- scipy: Signal processing (true-peak polyphase oversampling, K-weighting
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filters, spectrogram log-frequency resample, O(N) running-max via ndimage)
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- pyloudnorm: source of the BS.1770 K-weighting filter coefficients (the LUFS
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short-term / integrated / LRA math is now computed directly, validated against it)
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- pyqtgraph: Interactive plotting (zoom/pan, overlay, lin/log)
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- matplotlib: Colormaps only (consumed by pyqtgraph) + librosa dependency
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- mutagen: Audio metadata extraction
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- PyQt5: GUI framework
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- fastapi / uvicorn: web UI (optional extra; the desktop app does not need them)
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### Architecture considerations
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- Three-stage split: `metrics.compute` (heavy, worker thread, backend-neutral
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data) → `metrics.build_spec` (cheap, GUI thread, view-aware `PlotSpec`) →
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`AudioVisualizationWidget.show_specs` (pyqtgraph rendering, overlay, colours)
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- File path handling needs improvement for cross-platform compatibility
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- Error handling should be enhanced for production use
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- Consider moving from PyQt5 to PyQt6 or PySide for better licensing
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### Testing requirements
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- Unit tests for audio analysis functions
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- GUI component testing
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- File format compatibility testing
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- Performance testing with large audio files
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## Usage
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### Running the app
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```bash
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uv sync # one-time, after cloning
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uv run ujm # launch the GUI
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```
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### Running the web UI
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Branch `feature/web-ui`. Same backend, browser front end.
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```bash
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uv sync --extra web
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uv run ujm-web # http://127.0.0.1:8000
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uv run ujm-web --host 0.0.0.0 --port 8080 # reachable from another machine
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```
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Uploaded audio is held in the browser's Origin Private File System and streamed
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to the server per request; the server spools each body to a temp file and unlinks
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it before responding. Nothing is written to the host beyond that transient spool.
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Verify with `python3 scripts/webapi_smoke.py` against a running server (needs
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`ffmpeg` for the fixtures).
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Optional flags (handled by `logger_setup.parse_log_args`):
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```bash
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uv run ujm --log-level DEBUG # ERROR | WARN | INFO | DEBUG | TRACE
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uv run ujm --log-file # also write audio_analysis.log
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```
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The only entry point is `ujm` (defined in `pyproject.toml` as
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`ujm = "main:main"`). The previous `files.txt` batch mode and the
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`python master_core.py` workflow have been removed.
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### Planned usage enhancements
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1. Interactive plot manipulation and style customization
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2. Audio file comparison features (reference vs. comparee)
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3. Self-contained executable releases |