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.
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Enable MIPI/GMSL camera sensors on a Jetson Thor or Orin custom carrier by rendering a kernel-DT overlay from the in-tree sensor DTSI. Do NOT use for UPHY lane allocation or ODMDATA edits.
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설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Tegra264 (Thor) and Tegra234 (Orin) expose a single tegra-capture-vi
controller fronted by NVCSI and a fixed set of CSI ports. Camera
bring-up is:
.dtsi references for on the active platform.tegra<soc>-camera-<sensor>*.dtsi when one exists (the DTSI IS
the wiring source of truth); captured per-sensor from the user
when the sensor is custom.fragment@N body, append into the composite custom overlay
.dts for the active target (per
../../references/bsp-customization-kernel-dtb.md),
verify the composite with fdtoverlay.
/jetson-build-source compiles the composite and owns the
carrier conf's OVERLAY_DTB_FILE+= registration.Agentic, not table-driven — sensor list is built at runtime by
globbing in-tree per-sensor dtbos. No _THOR_CAMERAS dict, no
questions.json, no Python renderer in the question path.
No ODMDATA edit — cameras don't consume UPHY lanes (CSI is a separate PHY pool). The skill emits only a kernel-DT overlay; the ODMDATA line in the carrier conf is untouched by this skill.
The output is one commit:
fragment@N block (plus jetson-header-name on the
composite root if not already present) appended to the composite
custom overlay .dts per
../../references/bsp-customization-kernel-dtb.md
→ committed to the bsp_sources/ hardware repo.
/jetson-build-source compiles the composite to .dtbo and
owns its Makefile + flash-conf registration.tegra-capture-vi / NVCSI on a custom carrier.v4l2-ctl --list-devices shows no
tegra-capture-vi channels, OR sensor enumeration on a fresh
daughter-card needs to be confirmed.Prerequisites:
reference_devkit: + custom_carrier: blocks.<source.root_path>/Linux_for_Tegra/.git exists
(/jetson-init-source)./jetson-derive-carrier has run — the carrier flash-conf fork is
in the overlay tracker.<source.root_path>/bsp_sources/hardware/nvidia/<chip-dir>/nv-public/overlay/
exists and contains the in-tree per-sensor .dtsi files (sourced
by /jetson-init-source's Branch A archive extract).<source.root_path>/bsp_sources/kernel/kernel-noble/include/dt-bindings/
contains the macro headers cpp needs (source_sync.sh may need to
run if Branch B was used — see Step 5a.i below).bsp_developer_guide mirror or
separate path), Adaptation Guide §Camera, carrier schematic, SoC
TRM, Module Design Guide.dtc, cpp, fdtoverlay on PATH.Detailed step-by-step procedure (Steps 1–7, with all tables, code
blocks, and gates) lives in
references/procedure.md. Summary:
/* custom-bsp: camera:<sensor> */
fragment to the composite custom overlay .dts (see
../../references/bsp-customization-kernel-dtb.md).
Clone path cpp-expands the in-tree DTSI; custom path splices Step-4
answers + mode tables in-place. Idempotently set
jetson-header-name on the composite root. Verify with
dtc + fdtoverlay (pre-compile single-fragment gate;
post-compile deep-tree uniqueness gate). Commit via the
workflow's commit-message preview gate.cam_i2c_*,
extperiph<m>_clk, reset/PWDN/PWR_EN GPIOs) via
pin_verifier.py; route mismatches to /jetson-customize-pinmux.<workspace>/target-platform/<profile-stem>.jetson-customize-camera.json
and emit the headline, then drive the downstream next-step chain via
sequential AskUserQuestion prompts per references/procedure.md
Step 7. The chain is a documented workflow gate, not a clarifying
question — auto-mode does NOT exempt it. Never substitute a
printed "Next step: …" line for the prompts.fragment@N to the composite. A second one carrying status
overrides triggers dtc deep-merge → duplicate sibling subtrees
(e.g. two tca9546@70) → runtime first-match drops the dtsi-
supplied deep tree → camera silently doesn't enumerate. Gate on
this skill's marker only (Step 5c).compatible is owned globally, not by this
skill. Don't widen from any in-tree per-sensor dtbo's
compatible (devkit-SKU-gated). Fix the composite root if needed.jetson-header-name from any in-tree per-sensor dtbo. Fixed,
carrier-agnostic; read once, paste onto the metadata root.OVERLAY_DTB_FILE. Registering both your rendered overlay AND
the in-tree tegra<soc>-p3971-camera-<sensor>-overlay.dtbo
produces a phantom subdev bind that bricks camera enumeration.tegra-capture-vi { status="okay"; num-channels=<N>; } with no
ports / sensor / nvcsi body bricks the camera (all channel init failed). Splice the FULL sensor body via cpp + dtc.mode<N>, sensor_modes, pixel_phase — copy verbatim from the
closest in-tree DTSI.camera_common_regulator_get (null) ERR: -EINVAL = missing
avdd-reg / iovdd-reg / dvdd-reg strings — splice the FULL
sensor body; always-on rails fall back to dummy regulator.&label refs must exist in base DTB's __symbols__.
Use target-path = "/tegra-capture-vi" when the label is absent;
fdtoverlay exits non-zero with FDT_ERR_NOTFOUND otherwise.cpp failure on dt-bindings/gpio/gpio.h: No such file =
L4T source tree isn't staged. Re-run /jetson-init-source (Branch
B's source_sync.sh fetches the headers). Never fabricate the
macro expansion.ODMDATA="..." is untouched.
OVERLAY_DTB_FILE+= is owned by /jetson-build-source Step
5.0a — this skill never touches the carrier flash conf.<bsp_image.root_path>. All
edits land in <source.root_path>/Linux_for_Tegra/ (overlay
tracker) and <source.root_path>/bsp_sources/ (overlay .dts)
under the pristine + customization commit pattern.references/procedure.md — full
step-by-step Steps 1–7 procedure (extracted from this SKILL.md).references/csi-dt-bindings.md —
CSI / nvcsi / vi DT binding reference notes.references/overlay-template.md —
guidance on the metadata-root + clone-body overlay shape.references/camera-overlay-templates/
— starter .dts.tmpl templates: dphy-direct.dts.tmpl,
gmsl-serdes.dts.tmpl.../../scripts/pin_verifier.py
— shared HSIO pin verifier (Step 6).../../references/platform_template.yaml
— documents: block consumed by Step 1.../../context/bsp-customization-workflow.md
— overlay edit protocol.../jetson-customize-pinmux/SKILL.md —
sibling skill auto-invoked by Step 6 to fix HSIO pin SFIO
mismatches (CAM I²C, MCLK, reset GPIOs).../jetson-derive-carrier/SKILL.md
— must run first; produces the carrier base overlay (the
*-dynamic.dtbo) this skill's composite stacks after.../jetson-init-source/SKILL.md —
produces the overlay tracker + bsp_sources repo (with the
hardware/nvidia/<chip-dir>/ per-sensor DTSI tree) this skill
reads and commits into.아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
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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.
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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.
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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.
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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'.
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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`.
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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.
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