Does it help with data annotation and management?

While it is not an annotation tool, it provides scripts for auditing, cleaning, and converting between common formats like COCO, Pascal VOC, and YOLO.

Can I use this for model deployment on edge devices?

Yes, it includes specific workflows for optimizing models via ONNX, TensorRT, and OpenVINO for deployment on edge, mobile, and cloud hardware.

How does it help in choosing the right model architecture?

It includes a detailed architecture selection guide that compares inference speed, mAP accuracy, and trade-offs between CNN and Vision Transformer models.

Is this skill suitable for real-time video analysis?

Absolutely. It covers high-speed architectures like YOLO and RT-DETR, as well as object tracking techniques for continuous video stream processing.

Which computer vision frameworks does this skill support?

It supports major frameworks including PyTorch, torchvision, Ultralytics (YOLO), Detectron2, MMDetection, and segment-anything.

Senior Computer Vision

Name: Senior Computer Vision
Author: oabdelmaksoud

byoabdelmaksoud

0•

Data Science & ML

Develops, trains, and deploys production-grade computer vision models for object detection, segmentation, and visual AI systems.

This skill provides a comprehensive engineering framework for building advanced visual AI systems, covering the entire lifecycle from custom dataset preparation to high-performance production deployment. It offers specialized workflows for industry-leading architectures like YOLO, Faster R-CNN, and Vision Transformers, while providing expert guidance on model optimization using ONNX and TensorRT. Whether you are building real-time detection pipelines or complex image segmentation tools, this skill ensures best practices in model selection, training configuration, and inference acceleration across various hardware targets.

Key Features

01Advanced segmentation support including Mask R-CNN, SegFormer, and Segment Anything (SAM)

020 GitHub stars

03Automated dataset auditing, cleaning, and multi-format annotation conversion

04Architecture selection guides comparing speed, accuracy, and hardware requirements

05Model optimization workflows for TensorRT, ONNX, OpenVINO, and CoreML

06End-to-end pipelines for object detection using YOLO, DETR, and Faster R-CNN

Use Cases

01Training a custom YOLOv11 model for real-time industrial defect detection

02Optimizing PyTorch vision models for low-latency inference on NVIDIA edge devices

03Building robust data preprocessing and augmentation pipelines for large-scale image datasets

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add oabdelmaksoud/agention senior-computer-vision

For use in Claude.ai and ChatGPT

Key Features

01Advanced segmentation support including Mask R-CNN, SegFormer, and Segment Anything (SAM)

020 GitHub stars

03Automated dataset auditing, cleaning, and multi-format annotation conversion

04Architecture selection guides comparing speed, accuracy, and hardware requirements

05Model optimization workflows for TensorRT, ONNX, OpenVINO, and CoreML

06End-to-end pipelines for object detection using YOLO, DETR, and Faster R-CNN

Use Cases

01Training a custom YOLOv11 model for real-time industrial defect detection

02Optimizing PyTorch vision models for low-latency inference on NVIDIA edge devices

03Building robust data preprocessing and augmentation pipelines for large-scale image datasets