Swin Transformer for Object Detection by detectron2
This repo contains the supported code and configuration files to reproduce object detection results of Swin Transformer. It is based on detectron2.
Backbone | Pretrain | Lr Schd | box mAP | mask mAP | #params | FLOPs | config | log | model |
---|---|---|---|---|---|---|---|---|---|
Swin-T | ImageNet-1K | 3x | 44.6 | - | - | - | config | - | model |
Backbone | Pretrain | Lr Schd | box mAP | mask mAP | #params | FLOPs | config | log | model |
---|---|---|---|---|---|---|---|---|---|
Swin-T FPN | ImageNet-1K | 3x | 45.1 | - | - | - | config | - | model |
Backbone | Pretrain | Lr Schd | box mAP | mask mAP | #params | FLOPs | config | log | model |
---|---|---|---|---|---|---|---|---|---|
Swin-T FPN | ImageNet-1K | 3x | 45.5 | 41.8 | - | - | config | - | model |
The mask mAP (41.8 vs 41.6) is same as the mmdetection, but box mAP is worse (45.5 vs 46.0)
Please refer to get_started.md for installation and dataset preparation.
note: you need convert the original pretrained weights to d2 format by convert_to_d2.py