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Commits, branches and sync with the but CLI
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PointPillars training for LiDAR 3D detection v1.0.0
Use this resource to train and deploy a PointPillars LiDAR detection model with TAO
New
- 555 downloads
- 204 likes
- 122 saves
Free
Install with the CLI
In a terminal, from the folder you want:
npx --yes palatekit@latest install pointpillars-lidar-detection-trainingWith no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.
First time: connect the CLI with
npx --yes palatekit@latest loginThe agent sets up the data conversion, training, evaluation, export and TensorRT engine specs. It resumes training from a checkpoint if you provide one. You get configuration files for 3D detection in autonomous driving or robotics.
Mostly picked by
Updated November 2, 2026
Previews
Details
- Install guides
- Generates with
- Your agent's model
- Licence
- Apache-2.0
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What you get
- references/spec_template_dataset_convert.yaml: dataset conversion
- references/spec_template_export.yaml: export spec
- references/skill_info.yaml: container and action information
Good fit for
- You train a 3D detector on LiDAR point clouds
- You want to resume an interrupted training from a checkpoint
Not for
Tags
- pointpillars
- lidar
- 3d detection
- tao
About
You say
“Resume the PointPillars training from my last checkpoint.”
Skill published by nvidia under the Apache-2.0 license, delivered in its original version.
Show moreShow less
How to use it
- Install the skill in your agent's skills folder
- Ask your agent to train and deploy a PointPillars LiDAR detection model with TAO
- Review and adjust the result
Content preview
Files
- BENCHMARK.md7 KB
- config/skillspector-baseline.yaml0.8 KB
- evals/evals.json0.8 KB
- LICENSE11.3 KB
- NOTICE-PALATEKIT.md0.5 KB
- references/skill_info.yaml5.4 KB
- references/spec_template_dataset_convert.yaml5.9 KB
- references/spec_template_deploy_evaluate.yaml1.8 KB
- references/spec_template_deploy_gen_trt_engine.yaml0.2 KB
- references/spec_template_deploy_inference.yaml1.9 KB
- references/spec_template_evaluate.yaml6 KB
- references/spec_template_export.yaml6 KB
- references/spec_template_gen_trt_engine.yaml6 KB
- references/spec_template_inference.yaml6 KB
- references/spec_template_prune.yaml5.9 KB
- references/spec_template_retrain.yaml5.9 KB
- references/spec_template_train.yaml5.9 KB
- references/tao-deploy-pointpillars.md6.4 KB
- references/tao-deploy-pointpillars.skill_info.yaml2.7 KB
- schemas/dataset_convert.schema.json61.5 KB
- schemas/evaluate.schema.json62.9 KB
- schemas/export.schema.json64.2 KB
- schemas/gen_trt_engine.schema.json64.3 KB
- schemas/inference.schema.json63.5 KB
- schemas/manifest.json14.1 KB
- schemas/prune.schema.json62.2 KB
- schemas/retrain.schema.json61.5 KB
- schemas/train.schema.json61.5 KB
- skill-card.md4.9 KB
- SKILL.md15.8 KB
- skill.oms.sig10.4 KB
Origin and licence
Listed unmodified
- Author
- nvidia
- Source
- github.com/nvidia/skills/tree/ca116d60beafe1b4459f0ab790b7b450912c56b0/skills/tao-train-pointpillars
- Licence
- Apache-2.0
Notice
« tao-train-pointpillars » (nvidia, Apache-2.0) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.
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