human-emotion-recognition-analysis

What problem does it solve?

It helps you automatically detect and understand a person’s emotional state from front-facing images or videos, turning subjective “how does the user feel?” questions into structured, actionable emotion reports.

Core Features & Use Cases

• Real-time multi-dimensional emotion recognition: Detects happiness, sadness, depression, calmness, anger, surprise, and fear from frontal face visual input, suitable for interactive feedback and monitoring.
• Emotion intensity quantification & anomaly marking: Produces emotion probabilities, computes the dominant emotion, and flags abnormal emotions when they exceed a configurable threshold.
• Historical report listing from the cloud: Supports querying recognition history via an API-backed list mode and outputs a Markdown table with report links.
• Use Case: In a mental-health or human-computer interaction scenario, process uploaded face media to surface abnormal emotional patterns and provide evidence for follow-up guidance.

Quick Start

Provide a frontal face video or image URL (or upload the file) and your open-id, then ask the skill to generate an emotion recognition report with the default anomaly threshold.