yhenon/pytorch-retinanet

Health v2 · maintenance only

Flags: no_releases archived

Adoption not part of the score

2205 stars · 675 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A PyTorch implementation of the RetinaNet object detection model with focal loss, designed for readability and easy modification. It includes training and validation scripts with COCO and CSV dataloaders plus a pre-trained ResNet-50 model.

Use cases

• train a RetinaNet object detection model in PyTorch
• train an object detector on a custom dataset with CSV annotations
• evaluate object detection mAP on COCO
• use a pre-trained RetinaNet model for object detection
• modify a simple object detection implementation for research

When to choose

• you want a readable, hackable RetinaNet implementation in PyTorch
• you need to train object detection on custom datasets via CSV annotations
• you want to reproduce the Focal Loss paper results

When to avoid

• you need a production-grade, actively maintained detection framework like MMDetection or Detectron2
• you need the latest detection architectures or optimized training performance

Facets

library · maturity maintenance

machine-learning computer-vision deep-learning computer-vision machine-learning deep-learning python object-detection retinanet pytorch focal-loss coco

Member repositories

For agents

markdown · JSON · MCP: product_card(name="yhenon/pytorch-retinanet")