Py-feat Live v0.8.11

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     Install + first-run docs: https://py-feat.org/pages/pyfeat_live/ -->

Py-feat Live v0.8.10

Installation

Requires macOS on Apple Silicon (M-series).

• macOS Apple Silicon: Py-feat.Live_*_aarch64.dmg

First launch downloads ~1.5GB of Python dependencies and
~1GB of model weights into your user data directory.
Plan for ~10 minutes on a typical broadband connection.
Subsequent launches are instant.

Py-feat Live v0.8.9

Installation

Requires macOS on Apple Silicon (M-series).

• macOS Apple Silicon: Py-feat.Live_*_aarch64.dmg

First launch downloads ~1.5GB of Python dependencies and
~1GB of model weights into your user data directory.
Plan for ~10 minutes on a typical broadband connection.
Subsequent launches are instant.

v0.8.8

Stability + robustness release ahead of going public.

Detectors

• Tracks py-feat v0.7-dev (3855e07): the modular detector is now Detectorv1 (renamed from Detector); old sessions/presets that recorded "Detector" still work via a compatibility alias.

Fixes (from the pre-public review)

• Analyze: a detection/decode error no longer leaks the recorder (writer thread + CSV handle) or orphans a session dir; a corrupt video.mp4 is no longer left behind; one bad frame no longer fails a whole job.
• Analyze WebSocket: guarded JSON parsing + auto-reconnect (the queue no longer silently freezes on a dropped connection).
• Serving: session video/CSV stream instead of buffering the whole file into memory; malformed Analyze input returns 422 (not 500); uploaded files are cleaned up on "clear done".
• Viewer / Live: resilient session load + update-check (no unhandled rejections); overlay guards; the timeseries last-frame off-by-one is fixed.

Cleanup

• Removed dead Streamlit-era files/config/env and stale references.

This is also the first release to verify the corrected Info.plist (no longer requests local-network access).

v0.8.7

Fixes a launch crash in v0.8.5 / v0.8.6. Those packaged builds aborted on startup (a webview with label 'main' already exists) — a duplicate window definition. This release restores normal launch.

Same app features as v0.8.5/v0.8.6 (Detectorv2 v2.5, adaptive Live overlay, Viewer panels, grouped timeseries, Detectorv2-default extraction).

Fixed

• A label-less window in tauri.conf.json defaulted to the main label and collided with the window the app builds in code, crashing launch. Removed the duplicate.

v0.8.6

Hotfix release. Same app features as v0.8.5 (Detectorv2 v2.5, adaptive Live overlay, Viewer panels, grouped timeseries, Detectorv2-default extraction) — this corrects the release pipeline so the auto-updater manifest (latest.json) publishes.

Fixed

• The macOS updater-signature step searched a tripled bundle path (target/<triple>/release/bundle/macos) while the native build outputs to target/release/bundle/macos, which failed the deploy and skipped the latest.json publish in v0.8.5. Corrected.

v0.8.5

Upgrades to Detectorv2 v2.5 and brings the Viewer in line with Live.

Highlights

• Detectorv2 v2.5 — 52 MediaPipe/ARKit blendshape coefficients, safetensors weights, corrected 478-mesh decode, and head-pose pitch now reads +up (matching the classic Detector / Detectorv1).
• Live — the overlay pipeline is resolution/aspect-adaptive; it tracks correctly on any camera (no more mesh/overlay distortion on non-16:9 webcams).
• Viewer — emotion, valence/arousal, and pose panels now match Live and sit beside each face; the timeseries variable picker is grouped into collapsible sets (Emotions, V/A, Pose, Gaze, AUs, Blendshapes).
• Analyze — extraction defaults to Detectorv2 · standard; the classic detector is relabeled Detectorv1.

Fixes

• Mesh overlay no longer collapses/distorts under the v2.5 model.
• Head-pose pitch sign corrected to the canonical +up convention.
• index.html served with no-store to prevent stale app bundles.

Py-feat Live v0.8.4

Installation

Requires macOS on Apple Silicon (M-series).

• macOS Apple Silicon: Py-feat.Live_*_aarch64.dmg

First launch downloads ~1.5GB of Python dependencies and
~1GB of model weights into your user data directory.
Plan for ~10 minutes on a typical broadband connection.
Subsequent launches are instant.

Py-feat Live v0.8.3

Installation

Requires macOS on Apple Silicon (M-series).

• macOS Apple Silicon: Py-feat.Live_*_aarch64.dmg

First launch downloads ~1.5GB of Python dependencies and
~1GB of model weights into your user data directory.
Plan for ~10 minutes on a typical broadband connection.
Subsequent launches are instant.

Py-feat Live v0.8.2

Installation

Requires macOS on Apple Silicon (M-series).

• macOS Apple Silicon: Py-feat.Live_*_aarch64.dmg

First launch downloads ~1.5GB of Python dependencies and
~1GB of model weights into your user data directory.
Plan for ~10 minutes on a typical broadband connection.
Subsequent launches are instant.