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 |
unofficial implementation of efficientdet
- supported efficientnet backbone (B0 for now)
- supported resnet backbone.
- supports BiFPN.
- supports VOC and COCO training.
pip install --upgrade efficientnet-pytorch
- see
train_efficientdet.ipynb - see
eval.ipynbfor evaluation
- see
train_efficientdet.ipynband configure MS-COCO dataset.
- see
train_fp16_apex.ipynb
