Files
media-player-server/media_server/services/audio_analyzer.py
T
alexei.dolgolyov 2a474ea52c fix(player): redesign cleanup pass — sleeve, tonearm, AGC, dead code
Production-readiness pass before merging the Studio Reference redesign
to master.

Audio (backend):
- Reset AGC `_spectrum_ref` envelope on `start()` so a long silent gap
  between sessions doesn't make the first new transients clip at the
  ceiling. Annotated the trade-off (loud transient lifts reference for
  a few seconds afterwards — the price of real loudness).
- Add `tests/test_audio_analyzer.py` with 10 cases: bin-edge layout,
  AGC attack/release asymmetry, lifecycle reset. Skips numpy-dependent
  cases when numpy isn't installed; CI has it.

Vinyl mode dead code removed:
- The toggle button was dropped during the sleeve refactor but the JS
  state, 2 s `setInterval`, `beforeunload` handler, and `applyVinylMode`
  call (commented out in app.js) all stayed. Now properly excised from
  player.js + app.js + window.* exports.
- Stripped the matching `.album-art-container.vinyl*` CSS block and its
  `vinylSpin` keyframes (~95 LoC).

Sleeve + tonearm fixes:
- Removed the duplicate `.now-playing .vinyl-stage` / `.vinyl-label` /
  `.tonearm` block that was overriding the new `.vinyl-stage` rules by
  source order — the uncommitted tonearm geometry never took effect
  because the stale clone won the cascade.
- Tightened tonearm to 36% × 36% at right:-6%, top:26% so the SVG
  bounding box stays right of the sleeve (sleeve right edge ~68%).
  Needle now lands on the visible disc grooves at both rest and
  playing rotations and never overlaps the cover.
- Removed sleeve `transform: rotate(-2.5deg)` + the matching mobile
  `-1.8deg` override; sleeve now sits flat and squared-off.
- Removed the 1px inset hairline on the sleeve and the 1px outline +
  inset highlight on the album art — cleaner, no semitransparent
  border noise.
- Album art inset 5% to expose a cardstock margin around the print
  (using explicit width/height — `inset` shorthand triggered the CSS
  replaced-element rule that uses the image's intrinsic size and blew
  out the grid track).

Mobile + misc:
- Removed mobile tonearm overrides at 720px and 420px — they were
  calibrated for the pre-sleeve geometry and put the needle back over
  the cover on phones; desktop geometry is proportional and works.
- Added `<meta name="mobile-web-app-capable">` alongside the legacy
  Apple variant to silence the deprecation warning in Chromium.
- Replaced the "PRIMARY" badge on display cards with a copper star
  icon (translation key still drives title + aria-label).
- `.gitattributes` with `* text=auto eol=lf` so Windows checkouts stop
  nagging "LF will be replaced by CRLF".

Annotations:
- "REF · 24" record-label catalogue mark marked as intentional non-i18n
  decoration in index.html.

CI: ruff clean, pytest 7 passed + 3 numpy-skipped (all 10 run on CI).

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-04-25 14:39:20 +03:00

362 lines
13 KiB
Python

"""Audio spectrum analyzer service using system loopback capture."""
import logging
import platform
import threading
import time
logger = logging.getLogger(__name__)
_np = None
_sc = None
def _load_numpy():
global _np
if _np is None:
try:
import os
import sys
if sys.platform == 'win32':
# Embedded Python doesn't auto-load DLLs from numpy.libs;
# add the directory explicitly so libopenblas can be found.
try:
import importlib.util
spec = importlib.util.find_spec('numpy')
if spec and spec.submodule_search_locations:
numpy_dir = list(spec.submodule_search_locations)[0]
libs_dir = os.path.join(os.path.dirname(numpy_dir), 'numpy.libs')
if os.path.isdir(libs_dir):
os.add_dll_directory(libs_dir)
except Exception:
pass
import numpy as np
_np = np
except Exception as e:
logger.warning("numpy unavailable - audio visualizer disabled: %s", e)
return _np
def _load_soundcard():
global _sc
if _sc is None:
try:
import soundcard as sc
_sc = sc
except Exception as e:
logger.warning("soundcard unavailable - audio visualizer disabled: %s", e)
return _sc
class AudioAnalyzer:
"""Captures system audio loopback and performs real-time FFT analysis."""
def __init__(
self,
num_bins: int = 32,
sample_rate: int = 44100,
chunk_size: int = 1024,
target_fps: int = 30,
device_name: str | None = None,
):
self.num_bins = num_bins
self.sample_rate = sample_rate
self.chunk_size = chunk_size
self.target_fps = target_fps
self.device_name = device_name
self._running = False
self._thread: threading.Thread | None = None
self._lock = threading.Lock()
self._lifecycle_lock = threading.Lock()
self._data: dict | None = None
self._current_device_name: str | None = None
# Slow AGC envelope so the spectrum reflects real dynamics
# instead of being renormalized to peak=1.0 every frame.
# A loud transient (e.g. notification beep) lifts the reference
# for a few seconds afterwards; this is the price of real loudness.
self._spectrum_ref = 0.01
# Pre-compute logarithmic bin edges
self._bin_edges = self._compute_bin_edges()
def _compute_bin_edges(self) -> list[int]:
"""Compute logarithmic frequency bin boundaries for perceptual grouping."""
np = _load_numpy()
if np is None:
return []
fft_size = self.chunk_size // 2 + 1
min_freq = 20.0
max_freq = min(16000.0, self.sample_rate / 2)
edges = []
for i in range(self.num_bins + 1):
freq = min_freq * (max_freq / min_freq) ** (i / self.num_bins)
bin_idx = int(freq * self.chunk_size / self.sample_rate)
edges.append(min(bin_idx, fft_size - 1))
return edges
@property
def available(self) -> bool:
"""Whether audio capture dependencies are available."""
return _load_numpy() is not None and _load_soundcard() is not None
@property
def running(self) -> bool:
"""Whether capture is currently active."""
return self._running
def start(self) -> bool:
"""Start audio capture in a background thread. Returns False if unavailable."""
with self._lifecycle_lock:
if self._running:
return True
if not self.available:
return False
# Reset AGC envelope so a long silent gap between sessions
# doesn't make the first new transients clip at the ceiling.
self._spectrum_ref = 0.01
self._running = True
self._thread = threading.Thread(target=self._capture_loop, daemon=True)
self._thread.start()
return True
def stop(self) -> None:
"""Stop audio capture and cleanup."""
with self._lifecycle_lock:
self._running = False
if self._thread:
self._thread.join(timeout=3.0)
self._thread = None
with self._lock:
self._data = None
def get_frequency_data(self) -> dict | None:
"""Return latest frequency data (thread-safe). None if not running."""
with self._lock:
return self._data
@staticmethod
def list_loopback_devices() -> list[dict[str, str]]:
"""List all available loopback audio devices."""
sc = _load_soundcard()
if sc is None:
return []
devices = []
try:
# COM may be needed on Windows for WASAPI
if platform.system() == "Windows":
try:
import comtypes
comtypes.CoInitializeEx(comtypes.COINIT_MULTITHREADED)
except Exception:
pass
loopback_mics = sc.all_microphones(include_loopback=True)
for mic in loopback_mics:
if mic.isloopback:
devices.append({"id": mic.id, "name": mic.name})
except Exception as e:
logger.warning("Failed to list loopback devices: %s", e)
return devices
def _find_loopback_device(self):
"""Find a loopback device for system audio capture."""
sc = _load_soundcard()
if sc is None:
return None
try:
loopback_mics = sc.all_microphones(include_loopback=True)
# If a specific device is requested, find it by name (partial match)
if self.device_name:
target = self.device_name.lower()
for mic in loopback_mics:
if mic.isloopback and target in mic.name.lower():
logger.info("Found requested loopback device: %s", mic.name)
self._current_device_name = mic.name
return mic
logger.warning("Requested device '%s' not found, falling back to default", self.device_name)
# Default: first loopback device
for mic in loopback_mics:
if mic.isloopback:
logger.info("Found loopback device: %s", mic.name)
self._current_device_name = mic.name
return mic
# Fallback: try to get default speaker's loopback
default_speaker = sc.default_speaker()
if default_speaker:
for mic in loopback_mics:
if default_speaker.name in mic.name:
logger.info("Found speaker loopback: %s", mic.name)
self._current_device_name = mic.name
return mic
except Exception as e:
logger.warning("Failed to find loopback device: %s", e)
return None
def set_device(self, device_name: str | None) -> bool:
"""Change the loopback device. Restarts capture if running. Returns True on success."""
was_running = self._running
if was_running:
self.stop()
self.device_name = device_name
self._current_device_name = None
if was_running:
return self.start()
return True
@property
def current_device(self) -> str | None:
"""Return the name of the currently active loopback device."""
return self._current_device_name
def _capture_loop(self) -> None:
"""Background thread: capture audio and compute FFT continuously."""
# Initialize COM on Windows (required for WASAPI/SoundCard)
if platform.system() == "Windows":
try:
import comtypes
comtypes.CoInitializeEx(comtypes.COINIT_MULTITHREADED)
except Exception:
try:
import ctypes
ctypes.windll.ole32.CoInitializeEx(0, 0)
except Exception as e:
logger.warning("Failed to initialize COM: %s", e)
np = _load_numpy()
sc = _load_soundcard()
if np is None or sc is None:
self._running = False
return
device = self._find_loopback_device()
if device is None:
logger.warning("No loopback audio device found - visualizer disabled")
self._running = False
return
interval = 1.0 / self.target_fps
window = np.hanning(self.chunk_size)
# Pre-compute bin edge pairs for vectorized grouping
edges = self._bin_edges
bin_starts = np.array([edges[i] for i in range(self.num_bins)], dtype=np.intp)
bin_ends = np.array([max(edges[i + 1], edges[i] + 1) for i in range(self.num_bins)], dtype=np.intp)
try:
with device.recorder(
samplerate=self.sample_rate,
channels=1,
blocksize=self.chunk_size,
) as recorder:
logger.info("Audio capture started on: %s", device.name)
while self._running:
t0 = time.monotonic()
try:
data = recorder.record(numframes=self.chunk_size)
except Exception as e:
logger.debug("Audio capture read error: %s", e)
time.sleep(interval)
continue
# Mono mix if needed
if data.ndim > 1:
mono = data.mean(axis=1)
else:
mono = data.ravel()
if len(mono) < self.chunk_size:
time.sleep(interval)
continue
# Apply window and compute FFT
windowed = mono[:self.chunk_size] * window
fft_mag = np.abs(np.fft.rfft(windowed))
# Group into logarithmic bins (vectorized via cumsum)
cumsum = np.concatenate(([0.0], np.cumsum(fft_mag)))
counts = bin_ends - bin_starts
bins = (cumsum[bin_ends] - cumsum[bin_starts]) / counts
# True loudness from time-domain RMS, mapped via dB
# so the VU needle reflects actual program level — not
# the per-frame-normalized spectrum.
rms = float(np.sqrt(np.mean(mono.astype(np.float64) ** 2)))
if rms > 1e-6:
db = 20.0 * np.log10(rms)
# Map -60 dB..-6 dB to 0..1 (typical music range)
level = max(0.0, min(1.0, (db + 60.0) / 54.0))
else:
level = 0.0
# Slow auto-gain: envelope follower with fast attack,
# slow release. Quiet music yields small bars; loud
# passages reach the top; the reference adapts over
# seconds instead of resetting every frame.
current_peak = float(bins.max())
if current_peak > self._spectrum_ref:
self._spectrum_ref += (current_peak - self._spectrum_ref) * 0.05
else:
self._spectrum_ref += (current_peak - self._spectrum_ref) * 0.005
ref = max(self._spectrum_ref, 1e-4)
bins = np.clip(bins / ref, 0.0, 1.5)
# Bass energy: average of first 4 bins (~20-200Hz)
bass = float(bins[:4].mean()) if self.num_bins >= 4 else 0.0
# Round for compact JSON
frequencies = np.round(bins, 3).tolist()
bass = round(bass, 3)
level = round(level, 3)
with self._lock:
self._data = {"frequencies": frequencies, "bass": bass, "level": level}
# Throttle to target FPS
elapsed = time.monotonic() - t0
if elapsed < interval:
time.sleep(interval - elapsed)
except Exception as e:
logger.error("Audio capture loop error: %s", e)
finally:
self._running = False
logger.info("Audio capture stopped")
# Global singleton
_analyzer: AudioAnalyzer | None = None
def get_audio_analyzer(
num_bins: int = 32,
sample_rate: int = 44100,
target_fps: int = 25,
device_name: str | None = None,
) -> AudioAnalyzer:
"""Get or create the global AudioAnalyzer instance."""
global _analyzer
if _analyzer is None:
_analyzer = AudioAnalyzer(
num_bins=num_bins,
sample_rate=sample_rate,
target_fps=target_fps,
device_name=device_name,
)
return _analyzer