senior-computer-vision

Topics in the source

• Senior Computer Vision Engineer
• Table of Contents
• Quick Start
• Core Expertise
• Tech Stack
• Workflow 1: Object Detection Pipeline
• Step 1: Define Detection Requirements
• Step 2: Select Detection Architecture

Production computer vision engineering skill for object detection, image segmentation, and visual AI system deployment. 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 This skill provides guidance on: Object Detection: YOLO family (v5-v11), Faster R-CNN, DETR, RT-DETR Instance Segmentation: Mask R-CNN, YOLACT, SOLOv2 Semantic Segmentation: DeepLabV3+, SegFormer, SAM (Segment Anything) Image Classification: ResNet, EfficientNet, Vision Transformers (ViT, DeiT) Video Analysis: Object tracking (ByteTrack, SORT), action recognition 3D Vision: Depth estimation, point cloud processing, NeRF Production Deployment: ONNX, TensorRT, OpenVINO, CoreML | Category | Technologies | |----------|--------------| | Frameworks | PyTorch, torchvision, timm | | Detection | Ultralytics (YOLO), Detectron2, MMDetection | | Segmentation | segment-anything, mmsegmentation | | Optimization | ONNX, TensorRT, OpenVINO, torch.compile | | Image Processing | OpenCV, Pillow, albumentations | | Annotation | CVAT, Label Studio, Roboflow | | Experiment Tr

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