jonathan/ISR
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

feat: move analysis cache to recordings/analyses/, prune orphans on startup

Browse Source 
- Cache files now live in recordings/analyses/<filename>.analysis.json
  (mirroring the relative path for files in subdirectories) rather than
  alongside each audio file.
- _api_delete now removes the corresponding cache file after deleting audio.
- prune_orphan_analyses() runs at startup and removes any .analysis.json
  whose audio file no longer exists (handles files deleted outside the UI).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
jonathan
2026-06-02 22:33:26 +02:00
parent e22c0059f6
commit eb774a0876
2 changed files with 38 additions and 2 deletions
Download Patch File Download Diff File Expand all files Collapse all files
README.md
+1 -1
View File
@@ -159,7 +159,7 @@ Shows recordings grouped by day with collapsible sections. Features:
- **Day groups** — recordings are grouped under a collapsible day heading showing date, file count, total duration, and total size. The most recent day is expanded by default; older days start collapsed. Expanded state is preserved across filter changes.
- **Day highlights** — click **★ Highlights** on any day heading to run loudness analysis across all WAV/FLAC files in that day and display a combined activity timeline SVG. Orange segments show when loud sections occurred relative to the day's time span; blue shows the file extents. Labels show the start, midpoint, and end times.
- **Inline playback** — collapsible `▶ Play` button per row; audio loads lazily via a seekable `/stream/` endpoint with HTTP Range support. Metadata is fetched immediately so the duration is visible without pressing play.
- **Waveform analysis** — on demand per file; computes RMS per 100 ms window and highlights loud sections. Supported for WAV and FLAC (FLAC requires `numpy` + `soundfile`). Pure-Python fallback for WAV when numpy is absent. Results are cached alongside the audio file as `<filename>.analysis.json`; subsequent requests at the same threshold and min-gap settings return instantly without re-reading the audio.
- **Waveform analysis** — on demand per file; computes RMS per 100 ms window and highlights loud sections. Supported for WAV and FLAC (FLAC requires `numpy` + `soundfile`). Pure-Python fallback for WAV when numpy is absent. Results are cached in `recordings/analyses/<filename>.analysis.json`; subsequent requests at the same threshold and min-gap settings return instantly without re-reading the audio. The cache file is deleted automatically when the audio file is deleted. Orphaned cache files (audio deleted outside the UI) are pruned on startup.
- **Grace period** — configurable in the controls bar (default 2 s). Loud sections separated by less than this gap are merged into one. Raise this (e.g. to 15–30 s) when a single event generates many timestamps due to brief quiet gaps within it.
- **Timestamp jump** — after analysis, click any loud-section chip to seek the player to that position and pre-fill the cut panel. Use **J** / **K** keyboard shortcuts to jump to the previous / next section while audio is playing.
- **Cut & download** — `✂ Cut` button opens the player row and reveals a cut panel. Enter start and end times in `m:ss` or `h:mm:ss` format and click **↓ Download cut** to receive an ffmpeg-trimmed copy without re-encoding. Requires ffmpeg (included in the Docker image).