Official NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV/Parquet I/O, nullable semantics, and multi-GPU DataFrame workloads.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when Jetson codec, profile, chroma, bit-depth, dimension, engine-count, or operational support must be reconciled from live APIs, authenticated NVIDIA samples, and NVIDIA documentation; also applies the content-DRM scope.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Keep three authorities separate:
Capability work depends on jetson-video-setup for a fresh, read-only
installation check. Invoke that skill through public dispatch and consume its
reported exact native package/Samples root or exact PyNvVideoCodec interpreter,
version, and loaded module path. Do not locate or import setup's files. A
missing or mismatched surface is unknown/not_ready, never codec unsupported;
route repair to setup without mutating anything here.
Engine capability queries belong here, not in setup. For PyNvVideoCodec, use
the exact selected interpreter to call the public GetEncoderCaps and
GetDecoderCaps APIs as described in
capability-queries.md. A broad encoder
catalog covers H.264, HEVC, and AV1; a broad decoder catalog covers all ten
families across four chroma formats and three bit depths (120 exact tuples).
A bounded request queries only named members of the applicable catalog set.
Preserve every scoped record, error, and GPU ordinal. Nonzero-GPU helper results
remain unknown when the public helper selects only GPU 0.
For native reports, reuse authenticated package-owned binaries or build only
the required report target in a fresh user-owned tree, then run
AppEncCuda -ec and/or AppDec -dc using the build, identity, and grammar
rules in the capability reference. A query-only request does not authorize
package installation or an encode/decode operation. If the package, source,
tool, interpreter, or runtime-library identity cannot be established, report
the result unknown and name the missing setup prerequisite.
No as the final unsupported product verdict even if
an API or diagnostic operation is positive; this ends the normal
availability check. Documentation Yes establishes documented support;
live availability additionally needs the matching authenticated operation.
Missing, unretrievable, or conflicting documentation remains unknown.
When documentation is unknown, do not present positive capability fields as
available options: label each affected codec unknown beside them and state
the retrieval failure with the verdict.full-samples profile and carry its exact interpreter into the recipe and
pipeline stages. Do not select the smaller decode-performance/smoke profile.No reports
only operation_verified or operation_failed for that exact tuple and
never changes the unsupported product verdict. A tuple is the exact surface,
GPU, codec, profile, chroma, bit depth, dimensions, input format, and control
set tested. Resolve one recipe with jetson-video-recipe, then use
jetson-video-pipeline for encode followed by independent decode of the
exact output identity. A failed tuple never generalizes to the product.GetEncoderCaps success is capability_reported, supported=null,
operation_status=not_tested.GetDecoderCaps bIsSupported=1/0 records raw API true/false and whether
returned limits apply; neither value is the documentation verdict.-ec/-dc text is official_sample_report; preserve raw values and
never rewrite them as API or product claims.For a Python API query, create a short task-local program from this Markdown and the installed public SDK, run it with the exact selected interpreter, and keep its raw output with the result. Installation belongs to setup and operation validation belongs to pipeline. This skill owns engine queries, classification, documentation reconciliation, and the compact direct report above.
아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
Official NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV/Parquet I/O, nullable semantics, and multi-GPU DataFrame workloads.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Customize NVIDIA Nemotron Voice Agent's Generic Pipecat example for healthcare appointment, five-field patient intake, or custom tool-calling workflows without a separate backend.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Calibrate a new dataset from live RTSP camera streams via the AutoMagicCalib REST API. Use when the user provides RTSP URLs or asks to calibrate live cameras; VIOS records clips, AMC ingests them, then runs calibration.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Run end-to-end calibration on the shipped sample dataset (sdg_08_2_sample_data_010926.zip) against a running AMC microservice. Use when user says 'test sample dataset', 'run sample calibration', 'verify AMC install', or 'launch and test'.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Calibrates pre-recorded `cam_*.mp4` datasets through the AutoMagicCalib REST API. Use for user-supplied local MP4s; route live RTSP streams to `amc-run-rtsp-calibration`.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Launch AutoMagicCalib microservice and web UI from NGC release images via Docker Compose. Use when user says 'deploy auto calibration', 'launch auto calibration', 'launch AMC', 'start MS+UI', or 'set up auto-magic-calib'. Requires NGC API key.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.