Results for “crossframe”

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

Train, evaluate, export, quantize, and run inference for a TAO OneFormer model that performs panoptic, instance, and semantic segmentation using task-conditioned queries.

Compares two or more band-tagged frameworks and produces a framework-neutral topic matrix showing coverage and gaps across all inputs, plus an optional reference-centric PLC crosswalk document when a reference framework is supplied.

Kling 3.0 video generation on RunComfy. Kling 3.0 (also called Kling V3.0) is Kuaishou Technology's third-generation multi-shot video model with native synchronized audio and consistent character identity across shots. This skill covers all six Kling 3.0 endpoints, spanning three rendering tiers (Standard, Pro, 4K) and two modes (text-to-video, image-to-video). Calls runcomfy run kling/kling-3.0/<tier>/<mode> through the local RunComfy CLI. Triggers on "kling", "kling 3.0", "kling v3", "kling pro", "kling 4k", "kling text to video", "kling image to video", or any explicit ask to generate or animate with Kling 3.0.

Kling 3.0 video generation on RunComfy. Kling 3.0 (also called Kling V3.0) is Kuaishou Technology's third-generation multi-shot video model with native synchronized audio and consistent character identity across shots. This skill covers all six Kling 3.0 endpoints, spanning three rendering tiers (Standard, Pro, 4K) and two modes (text-to-video, image-to-video). Calls runcomfy run kling/kling-3.0/<tier>/<mode> through the local RunComfy CLI. Triggers on "kling", "kling 3.0", "kling v3", "kling pro", "kling 4k", "kling text to video", "kling image to video", or any explicit ask to generate or animate with Kling 3.0.

Perform fast genomic interval operations (overlap, nearest, merge, coverage, cluster, complement, subtract, count-overlaps), multi-format bioinformatics I/O, DataFusion SQL, and pileup on Polars DataFrames via the polars-bio library, serving as a scalable alternative to bioframe and bedtools.

Route goalflow (wanmol/goal-flow) work — a LangGraph framework that combines workflow graphs with agent loops — into exactly one mode: fit check, transpiling a Dify DSL export into runnable LangGraph Python, authoring workflow nodes and edges, building an `agent_kit` loop with middleware and a harness, wiring the serving layer (data adapters, SSE streaming, HITL, Redis/MySQL, API-key registration), or running the pre-publish security gate. Use when the user wants Dify's visual design without Dify's runtime, a graph node that hosts an agent loop, an OpenAI-compatible wire protocol over their own workflows, or prompt-injected `SKILL.md` capabilities. Triggers on: goalflow, goal-flow, dify to langgraph, dify transpiler, dify DSL export, BaseWorkflow, agent_kit, AgentBaseNode, DataAdapter, chunk processor, HITL interrupt, dify2langgraph. Route plain graph-API questions to `langgraph-fundamentals` and `langgraph-workflow`.