Senior Computer Vision
Skill Verified ActiveComputer vision engineering skill for object detection, image segmentation, and visual AI systems. Covers CNN and Vision Transformer architectures, YOLO/Faster R-CNN/DETR detection, Mask R-CNN/SAM segmentation, and production deployment with ONNX/TensorRT. Includes PyTorch, torchvision, Ultralytics, Detectron2, and MMDetection frameworks. Use when building detection pipelines, training custom models, optimizing inference, or deploying vision systems.
To streamline the process of setting up training pipelines and optimizing deployed computer vision models.
Features
- Generate YOLOv8 training configs
- Create Detectron2 configurations
- Generate MMDetection configs
- Analyze model performance and structure
- Provide optimization recommendations
Use Cases
- When building object detection pipelines from scratch
- When optimizing trained models for production deployment
- When selecting the right architecture for specific vision tasks
- When preparing datasets for training
Non-Goals
- Directly training models
- Performing inference
- Managing datasets directly (only config generation)
Code Execution
- info:LoggingThe Python scripts include basic logging for operations and errors.
Installation
First, add the marketplace
/plugin marketplace add alirezarezvani/claude-skills/plugin install engineering-team@claude-code-skillsQuality Score
VerifiedTrust Signals
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