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:neckbeard:Unofficial implementation of EfficientDet

License: MIT License

Python 3.41% Jupyter Notebook 96.40% Shell 0.01% Cuda 0.18% C 0.01%
efficientdet pytorch apex retinanet ssd

efficientdet.pytorch's Introduction

Now training models..

backbone resolution VOCmAP COCOmAP Inference[ms] model
EfficientnetB0(wo/BiFPN) 512 77.0 TBD
EfficientnetB0(w/BiFPN) 512 77.2 TBD
EfficientnetB2(wo/BiFPN) 768 TBD TBD
EfficientnetB2(w/BiFPN) 768 TBD TBD
EfficientnetB4(wo/BiFPN) 1024 TBD TBD
EfficientnetB4(w/BiFPN) 1024 TBD TBD
EfficientnetB6(wo/BiFPN) 1408 TBD TBD
EfficientnetB6(w/BiFPN) 1408 TBD TBD

efficientdet.pytorch

unofficial implementation of efficientdet

  • supported efficientnet backbone (B0 for now)
  • supported resnet backbone.
  • supports BiFPN.
  • supports VOC and COCO training.

requirements

pip install --upgrade efficientnet-pytorch

PASCAL-VOC training

  • see train_efficientdet.ipynb
  • see eval.ipynb for evaluation

COCO training

  • see train_efficientdet.ipynb and configure MS-COCO dataset.

FP16 training

  • see train_fp16_apex.ipynb

configs

perf

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