Results for “nvstreamer”

Build video analytics pipelines using NVIDIA DeepStream SDK 9.0 with Python pyservicemaker API, including GStreamer-based video processing, TensorRT inference integration, object detection/tracking, and Kafka/message broker integration.

Finetunes the NV-Generate-CTMR MR-brain diffusion UNet from user-supplied NIfTI training volumes using a wrapper that stages configs and delegates to upstream scripts.

Import object detection models from HuggingFace or NVIDIA NGC into a DeepStream pipeline with automated ONNX download, TensorRT engine build, custom parser, multi-stream benchmark, and PDF report generation.

Builds and validates DeepStream GStreamer pipelines through an interactive questionnaire and a BM25 retrieval engine over 270+ verified pipelines.

Profile a DeepStream pipeline with Nsight Systems and derive its configs from the measurement.

Generates synthetic body MRI volumes using NVIDIA's NV-Generate-CTMR rflow-mr model. Wraps the upstream diffusion inference pipeline with config staging, output validation, and NIfTI volume summarization.

Operate the VSS alert pipeline for real-time monitoring, Alert-Bridge subscriptions, Slack notifications, incident queries, and camera onboarding.

Routes NVIDIA Nemotron Speech (Riva) NIM tasks for ASR, TTS, and NMT, covering cloud-hosted inference, self-hosted Docker deployment, and custom model builds.

Runs NV-Segment-CTMR segmentation on CT or MRI NIfTI volumes and records label-map evidence.

Build, deploy, evaluate, debug, and measure latency for a GPU-accelerated FastAPI service that detects whether operators perform assembly-line steps in order via event boundary detection and VLM classification.

Generates synthetic CT volumes and masks using NVIDIA's rectified-flow pipeline for medical imaging research.

Queries video analytics incidents, alerts, metrics, and sensor data from Elasticsearch via the VA-MCP server.

Finetune the NV-Generate-CTMR MAISI VAE/autoencoder on user-supplied CT or MRI NIfTI volumes using a staged config and datalist workflow.

Live stream as an AI VTuber on Lobster.fun. Control your Live2D avatar with emotions, gestures, GIFs, and YouTube videos while interacting with chat in real-time.

A cascader component for displaying and selecting tree-structured data with support for single/multiple selection, async loading, filtering, and various check strategies

A versatile slider component for selecting values within a range in Naive UI. Supports single value, range selection, marks, vertical mode, and custom handles.

A dual-list transfer component for moving items between source and target lists with filtering, virtual scrolling, and custom rendering capabilities

Provides expert guidance for distributed training with DeepSpeed, covering ZeRO optimization stages, pipeline parallelism, FP16/BF16/FP8, 1-bit Adam, and sparse attention.

Niagara emitter color/curve authoring (tint, hue-shift, ColorFromCurve keys), rapid-iteration parameter tuning, and Custom-HLSL scratch-pad authoring (NiagaraEmitterService + NiagaraScratchPadService). Module/renderer CRUD is owned by the engine NiagaraToolsets. Use when the user asks to recolor or hue-shift particles, edit color curves, tune emitter params, or build a scratch-pad/Custom HLSL module. For system-level lifecycle, load niagara-systems.

Deploy and operate the RTVI-CV-3D microservice for multi-camera 3D detection and tracking, supporting sample datasets, custom videos, and RTSP streams.

Search archived video using natural language, ingest video files or RTSP streams, and manage ingested sources.

Serve LLMs and VLMs on NVIDIA Jetson devices using vLLM or SGLang with optimized Docker containers and quantization presets.

Trains vision transformers via self-distillation without labels for self-supervised visual representation learning, and supports export and inference of NVDINOv2 backbones.

Segments abdominal organs from CT NIfTI volumes using the NV-Segment-CT VISTA3D model, producing label maps and structured evidence JSON.

Call APIs, load data into components, and handle the async lifecycle in Blazor.

Summarize recorded video clips using the LVS microservice with a VLM fallback, producing a narrative summary with timestamped events.

Diagnose and optimize slow-loading, high-memory, or low-FPS USD scenes using a structured workflow with profiling, validation, and mutation phases.

VIPER v2.1 — Range-bound liquidity sniper. Enters at support/resistance when Bollinger Bands are tight, ATR is low, RSI is at extremes within the range, and volume is declining. Works when nothing is trending — the chop predator. USD-weighted OI filtering (min $5M). DSL High Water Mode (mandatory). 5-minute scan interval. Second-best performer in the Senpi zoo at +6.2% ROI.

Use when making raw HTTP, E-utilities, PubChem, datasets, or FTP requests through the low-level EDirect transport wrapper.

Debug and modify agent streaming behavior, covering SSE and plain-text transports, ChatKit events, and session continuity.

A color picker component for selecting colors with support for multiple color modes, alpha channel, swatches, custom triggers, and native color selector integration

Rapid-iteration parameter tuning, diagnostics, and Custom-HLSL scratch-pad authoring for Niagara systems (VibeUE NiagaraService + NiagaraScratchPadService). System/emitter/parameter CRUD is owned by the engine NiagaraToolsets. Use when the user asks to tune emitter rapid-iteration params, compare/diagnose systems, or build scratch-pad/Custom HLSL modules. For emitter color/module work, load niagara-emitters.

Development with Nvdla: tools and best practices

Nuxt 3 patterns including Nitro server, auto-imports, modules, hybrid rendering, and full-stack development.

Performance Profiler