World-class computer vision skill for image/video processing, object detection, segmentation, and visual AI systems. Expertise in PyTorch, OpenCV, YOLO, SAM, diffusion models, and vision transformers. Includes 3D vision, video analysis, real-time processing, and production deployment. Use when building vision AI systems, implementing object detection, training custom vision models, or optimizing inference pipelines.
World-class senior computer vision engineer skill for production-grade AI/ML/Data systems.
# Core Tool 1
python scripts/vision_model_trainer.py --input data/ --output results/
# Core Tool 2
python scripts/inference_optimizer.py --target project/ --analyze
# Core Tool 3
python scripts/dataset_pipeline_builder.py --config config.yaml --deploy
This skill covers world-class capabilities in:
Languages: Python, SQL, R, Scala, Go ML Frameworks: PyTorch, TensorFlow, Scikit-learn, XGBoost Data Tools: Spark, Airflow, dbt, Kafka, Databricks LLM Frameworks: LangChain, LlamaIndex, DSPy Deployment: Docker, Kubernetes, AWS/GCP/Azure Monitoring: MLflow, Weights & Biases, Prometheus Databases: PostgreSQL, BigQuery, Snowflake, Pinecone
Comprehensive guide available in references/computer_vision_architectures.md covering:
Complete workflow documentation in references/object_detection_optimization.md including:
Technical reference guide in references/production_vision_systems.md with:
Enterprise-scale data processing with distributed computing:
Production ML system with high availability:
High-throughput inference system:
Latency:
Throughput:
Availability:
# Development
python -m pytest tests/ -v --cov
python -m black src/
python -m pylint src/
# Training
python scripts/train.py --config prod.yaml
python scripts/evaluate.py --model best.pth
# Deployment
docker build -t service:v1 .
kubectl apply -f k8s/
helm upgrade service ./charts/
# Monitoring
kubectl logs -f deployment/service
python scripts/health_check.py
references/computer_vision_architectures.mdreferences/object_detection_optimization.mdreferences/production_vision_systems.mdscripts/ directoryAs a world-class senior professional:
Technical Leadership
Strategic Thinking
Collaboration
Innovation
Production Excellence
npx skills add davila7/senior-computer-vision下载完整 Skill 目录，包含 SKILL.md 及所有相关文件
Delegate coding tasks to Codex, Claude Code, or Pi agents via background process. Use when: (1) building/creating new features or apps, (2) reviewing PRs (spawn in temp dir), (3) refactoring large codebases, (4) iterative coding that needs file exploration. NOT for: simple one-liner fixes (just edit), reading code (use read tool), thread-bound ACP harness requests in chat (for example spawn/run Codex or Claude Code in a Discord thread; use sessions_spawn with runtime:"acp"), or any work in ~/clawd workspace (never spawn agents here). Claude Code: use --print --permission-mode bypassPermissions (no PTY). Codex/Pi/OpenCode: pty:true required.
Create or update AgentSkills. Use when designing, structuring, or packaging skills with scripts, references, and assets.
Use CodexBar CLI local cost usage to summarize per-model usage for Codex or Claude, including the current (most recent) model or a full model breakdown. Trigger when asked for model-level usage/cost data from codexbar, or when you need a scriptable per-model summary from codexbar cost JSON.
Use the mcporter CLI to list, configure, auth, and call MCP servers/tools directly (HTTP or stdio), including ad-hoc servers, config edits, and CLI/type generation.
Search and analyze your own session logs (older/parent conversations) using jq.
iMessage/SMS CLI for listing chats, history, and sending messages via Messages.app.
Category:developer