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Object Detection/Segmentation Skill

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Deep learning based object detection and segmentation for robotics applications

QUICK START

How to use this skill

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  1. Open your project in Codex.
  2. Copy the prompt below and paste it into your agent.
  3. Review the proposed files and risks before you approve installation.
Prompt to paste
I want to install this Agent Skill for this project in Codex.

Source SKILL.md: https://github.com/a5c-ai/babysitter/blob/HEAD/library/specializations/robotics-simulation/skills/object-detection/SKILL.md

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First, summarize what it does, its dependencies, license status if identifiable, and any risks. Show the exact files you propose to add under .agents/skills/object-detection-segmentation-skill/. Do not write files or run scripts until I approve.

After I approve, install the complete skill folder, including required referenced files, into that project location. Verify it is discoverable, then tell me its actual invocation name and how to use it. Do not claim it is installed until you have verified it.

Copying this prompt does not install or run the skill. Review third-party files before use. Codex skill guide

Object Detection/Segmentation Skill

Overview

Expert skill for deploying and optimizing deep learning models for object detection, instance segmentation, and 3D object detection in robotics applications.

Capabilities

  • Configure YOLO (v5, v8) for real-time detection
  • Set up Detectron2 for instance segmentation
  • Implement semantic segmentation models
  • Configure TensorRT optimization for Jetson
  • Set up ONNX runtime deployment
  • Implement 3D object detection (PointPillars, VoxelNet)
  • Configure depth-based object detection
  • Set up ROS vision pipelines with image_pipeline
  • Implement object tracking (SORT, DeepSORT, ByteTrack)
  • Configure multi-camera detection fusion

Target Processes

  • object-detection-pipeline.js
  • synthetic-data-pipeline.js
  • nn-model-optimization.js
  • moveit-manipulation-planning.js

Dependencies

  • YOLO (Ultralytics)
  • Detectron2
  • TensorRT
  • ONNX Runtime
  • vision_msgs

Usage Context

This skill is invoked when processes require object detection model deployment, instance segmentation, 3D detection, or multi-object tracking for robot perception.

Output Artifacts

  • Detection model configurations
  • TensorRT optimized models
  • ROS detection node implementations
  • Tracking pipeline configurations
  • Multi-camera fusion setups
  • Inference optimization scripts