Clean Python and C Integration
Simple setup via context managers and configuration objects or by invoking through a Docker container, so your team deploys in hours, not weeks.
Run our Emotion Analysis AI on your own hardware, completely offline!
Multimodal emotion intelligence that never leaves your network.
Bring facial, vocal, and text emotion recognition directly onto your own hardware. Built for teams that can't send sensitive media to the cloud, our offline Linux SDK processes video, voice, and text entirely on-premise, with real-time performance and full data ownership.
APPLICATIONS OF THE LINUX SDK
Air-Gapped & Local Privacy
Sensitive media never leaves your network. Processing runs 100% locally with zero external API calls, built for teams that can't route data through a third party. Choose to never record or save your customers' video.
Real-Time Frame-by-Frame Streaming
Process live webcam streams, RTSP feeds, or archived files with immediate frame-by-frame JSONL output - no waiting for full files to render.
Multilingual Coverage
Supports English, Chinese, Japanese, and more.
Unified Multimodal Pipeline
Combine facial tracking, vocal tone, and text transcripts into a single synchronized intelligence pipeline, rather than stitching together separate tools.
CORE CAPABILITIES & EMOTIONAL GRANULARITY
| Capability | Scope & Processing | Emotional States Detected |
|---|---|---|
| Face Tracking & Emotion | Multi-face detection, continuous tracking, and frame-by-frame expression mapping. | 8 Core Expressions: Angry, Contempt, Disgust, Fear, Happy, Neutral, Sad, Surprise |
| Voice & Speech Emotion | Direct acoustic and tonal analysis from speech audio streams or recordings. | 8 Tonal States: Happy, Neutral, Sad, Boredom, Surprise, Fear, Disgust, Angry |
| Transcript & Text Emotion | Deep semantic emotion mapping from transcribed dialogue and spoken text. | 28 Nuanced States: Excitement, Joy, Desire, Approval, Love, Relief, Optimism, Curiosity, Gratitude, Surprise, Realization, Pride, Neutral, Amusement, Admiration, Caring, Fear, Annoyance, Nervousness, Anger, Disgust, Remorse, Disappointment, Disapproval, Sadness, Grief, Embarrassment, and Confusion. |
DEVELOPER-FRIENDLY ARCHITECTURE
Structured Data Output
JSON/JSONL output with timestamps, bounding boxes, speaker tracks, and emotion score distributions built in.
Flexible Input Sources
Native support for live webcam hardware, networked IP feeds, and standard pre-recorded video/audio containers.
Ready to deploy local emotion intelligence?
Bring private, low-latency emotion recognition to your products today.