Senior Computer Vision
Specialized skill for building, training, and deploying production computer vision systems including object detection, image segmentation, and visual AI applications. Covers modern architectures (YOLO, Faster R-CNN, DETR, SAM), deep learning frameworks (PyTorch, Detectron2), model optimization (ONNX, TensorRT), and deployment strategies. Use when developing detection pipelines, creating custom models, optimizing inference performance, or deploying vision systems to production.
- skills.sh installs
- 1.2K
- GitHub stars
- 29.5K
- last updated
- Aug 21, 2026
Install
$ npx -y skills add alirezarezvani/claude-skills --skill senior-computer-vision --agent claude-codeInstalls into .claude/skills of the current project.
Files
Senior Computer Vision Engineer
Production computer vision engineering skill for object detection, image segmentation, and visual AI system deployment.
Table of Contents
- Quick Start
- Core Expertise
- Tech Stack
- Workflow 1: Object Detection Pipeline
- Workflow 2: Model Optimization and Deployment
- Workflow 3: Custom Dataset Preparation
- Architecture Selection Guide
- Reference Documentation
Quick Start
# Generate training configuration for YOLO or Faster R-CNN
python scripts/vision_model_trainer.py models/ --task detection --arch yolov8
# Analyze model for optimization opportunities (quantization, pruning)
python scripts/inference_optimizer.py model.pt --target onnx --benchmark
# Build dataset pipeline with augmentations
python scripts/dataset_pipeline_builder.py images/ --format coco --augment
Core Expertise
This skill provides guidance on:
Sponsors
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- Repository
- github.com/alirezarezvani/claude-skills
- Categories
- Data Science & ML, Design & UI/UX
- First seen
- Jun 3, 2026
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