rwightman/efficientdet-pytorch

Health v2 · maintenance only

Adoption not part of the score

1654 stars · 300 forks observed · 2026-08-28

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

A PyTorch implementation of EfficientDet object detection, faithful to the original Google TensorFlow implementation with ported pretrained weights. It offers configurable BiFPN connections, swappable backbones from the timm collection, and training/validation scripts for MS COCO and custom datasets.

Use cases

• run object detection with pretrained EfficientDet weights in PyTorch
• train EfficientDet on a custom dataset
• reproduce MS COCO training results from scratch
• experiment with different backbones like EfficientNetV2 for detection
• port TensorFlow detection models to PyTorch

When to choose

• you need a faithful PyTorch reproduction of Google's EfficientDet with ported weights
• you want flexible BiFPN and backbone configuration for detection experiments
• you already use the timm ecosystem and want interchangeable backbones

When to avoid

• you need the latest actively developed detection framework or YOLO-family models
• you want a TensorFlow or JAX implementation
• you need detection models beyond the EfficientDet family

Facets

library · maturity maintenance

machine-learning computer-vision image-processing computer-vision deep-learning machine-learning python object-detection efficientdet efficientnet pytorch bifpn model-weights coco timm gpu

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