Results for “face-tracking”

Track and visualize ML training experiments with Trackio, including logging metrics, firing alerts, and retrieving data via CLI. Supports real-time dashboards, webhook alerts, and HF Space syncing.

Trains and fine-tunes vision models for object detection, image classification, and segmentation using Hugging Face Transformers on cloud GPUs, with automatic dataset validation and Hub persistence.

Track Apple devices and AirTags via FindMy.app on macOS using AppleScript and screen capture.

Guides DPIA for biometric processing systems including facial recognition, fingerprint, voice, iris, and gait analysis. Covers Art. 9 special category requirements, Art. 35(3)(b) mandatory DPIA triggers for large-scale biometric processing, and EDPB Guidelines 3/2019 on video surveillance. Keywords: biometric, facial recognition, fingerprint, DPIA, Art. 9, special category, EDPB Guidelines 3/2019.

Track Apple devices and AirTags via FindMy.app on macOS using AppleScript and screen capture.

Implements face detection and recognition with privacy-preserving features and bias mitigation

Manage Hugging Face dataset Git repositories with Git Xet/LFS-compatible tracking, including setup, safe snapshot commits, push verification, binary rejection recovery, and README track-rule maintenance.

Trains, evaluates, exports, and runs inference for person re-identification models using TAO, learning discriminative embeddings for cross-camera matching.

Fetch dataset metadata, paginate rows, search text, apply filters, and download parquet URLs from the Hugging Face Dataset Viewer API.

Instrument browser/web apps with the Application Insights JavaScript SDK for Real User Monitoring (RUM), including page views, clicks, AJAX/fetch dependencies, exceptions, custom events, and GenAI agent traces correlated to backend OpenTelemetry traces.

Queries Hugging Face benchmark leaderboards to find the best AI models for a task, filters by device constraints, and returns a ranked comparison table with scores.

Filters and ranks trending Hugging Face models, datasets, and spaces by novelty and significance, providing a 'why notable' explanation for each pick.

Track Apple devices/AirTags via FindMy.app on macOS.

Swap faces in a video using AI via the HeyGen API. Use when: (1) Replacing a face in a video with another face, (2) Face swapping from a source image onto a target video, (3) Creating personalized videos by swapping in a person's face, (4) Working with HeyGen's /v1/workflows/executions endpoint for face swap processing.

Audit server-side paid-media measurement, including tag management, conversion APIs, event taxonomy, deduplication, consent, hashing, data quality, and observability.

Train a personalized identity model on a person's face for use in Higgsfield's image and video generation.

Lip-sync a face to a specific audio track on RunComfy via the `runcomfy` CLI. Routes across ByteDance OmniHuman (audio-driven full-body avatar from a portrait + audio), Sync Labs sync v2 / Pro (state-of-the-art mouth sync onto a video), Kling lipsync (audio-to- video and text-to-video with synced speech), and Creatify lipsync. The skill picks the right endpoint for the user's actual intent — portrait still + audio (avatar-style), source video + audio (mouth- swap on existing footage), or generate-and-sync from a script. Triggers on "lip sync", "lipsync", "make this video speak", "match audio to mouth", "dub video", "sync lips to voice", "Sync Labs", "voiceover sync", or any explicit ask to drive a face's mouth from an audio track.

Track Apple devices/AirTags via FindMy.app on macOS.

Tracks crypto and AI narratives with mindshare scores, velocity arrows, phase labels, named drivers, and position calls. Detects phase transitions and reflexivity signals.

Track stocks, ETFs, indices, crypto (where available), and FX pairs with caching + provider fallbacks.

Tracks team OKRs with quarter banner, objective columns, key result progress bars, owner avatars, and status pills.

Detect brand impersonation attacks across domains, social media, mobile apps, and dark web channels to identify phishing campaigns, fake sites, and unauthorized brand usage.

Frontier research tracking and trend scouting specialist. Use when the user asks to talk to Fade, requests the scout, or needs arxiv monitoring, paradigm shift detection, and emerging method analysis.

Design privacy-aware observability for AI agents using traces, spans, structured events, metrics, cost attribution, dashboards, alerts, and investigation workflows. Use when instrumenting an agent, debugging intermittent tool or model failures, defining service-level objectives, analyzing latency or spend, auditing agent decisions, or preparing production monitoring.

当用户在网页端或电脑客户端需要进行舆情监控、调研、社交媒体反馈收集、用户评价、品牌声量追踪时使用。支持微博、知乎、即刻、脉脉、B站、抖音.等多平台的舆情搜索、内容筛选和原始帖子溯源。注意：判断用户所处平台是手机端时，禁止触发这个skill。

Track ML experiments with automatic logging, visualize training in real-time, optimize hyperparameters with sweeps, and manage model registry with W&B.

Swap a face / character into video or images on RunComfy via the `runcomfy` CLI. Routes across community Wan 2-2 Animate (audio-driven character animation + identity swap), GPT Image 2 Edit (single-shot precise face swap on still images via reference composition), Nano Banana Edit (batch identity-preserving swap), Flux Kontext (single-ref high-fidelity local face edit), and Kling 2-6 Motion Control Pro (transfer motion from one performance onto a target character). Picks the right model for the user's actual intent — single still vs video, full character vs face only, dialog scene vs silent motion. Triggers on "face swap", "swap face", "deepfake", "face replacement", "character swap", "head swap", "put X's face on Y", "make this video star X", "replace the actor in this video", "swap the character in the photo", "deepfake video", "ReActor alternative", or any explicit ask to substitute one identity for another.

Open-source AI observability platform for LLM tracing, evaluation, and monitoring. Use when debugging LLM applications with detailed traces, running evaluations on datasets, or monitoring production AI systems with real-time insights.

Progress Tracking

Detect SSO and OAuth token replay and SaaS lateral movement using identity telemetry from Microsoft Entra ID and Okta.

Analyzing session replays, extracting persona-based behavioral patterns, and storytelling UX issues. Reads the 'why' from real user operation logs. Works with Field/Echo for persona validation.

Append structured execution traces across operational, cognitive, and contextual surfaces with minimal overhead. Load when inspecting agent runs, logging tool calls and observations, enabling post-run debugging, or pairing with structured-planning step IDs. Also triggers on "trace this run", "log execution", "agent observability", "run log", or when fault-localize needs evidence. Default-on during multi-step plans. Traces live at .agent-loom/traces/ — git-ignored by default.

Swap a face / character into video or images on RunComfy via the `runcomfy` CLI. Routes across community Wan 2-2 Animate (audio-driven character animation + identity swap), GPT Image 2 Edit (single-shot precise face swap on still images via reference composition), Nano Banana Edit (batch identity-preserving swap), Flux Kontext (single-ref high-fidelity local face edit), and Kling 2-6 Motion Control Pro (transfer motion from one performance onto a target character). Picks the right model for the user's actual intent — single still vs video, full character vs face only, dialog scene vs silent motion. Triggers on "face swap", "swap face", "deepfake", "face replacement", "character swap", "head swap", "put X's face on Y", "make this video star X", "replace the actor in this video", "swap the character in the photo", "deepfake video", "ReActor alternative", or any explicit ask to substitute one identity for another.

Apply image blur effects and privacy masks using Python PIL processing. Use when you need to blur, redact faces, or mask sensitive regions in images.