We provide baseline DETR and DETR-DC5 models, and plan to include more in future. AP is computed on COCO 2017 val5k, and inference time is over the first 100 val5k COCO images, with torchscript transformer.
| name | backbone | schedule | inf_time | box AP | url | size | |
|---|---|---|---|---|---|---|---|
| 0 | DETR | R50 | 500 | 0.036 | 42.0 | model | logs | 159Mb |
| 1 | DETR-DC5 | R50 | 500 | 0.083 | 43.3 | model | logs | 159Mb |
| 2 | DETR | R101 | 500 | 0.050 | 43.5 | model | logs | 232Mb |
| 3 | DETR-DC5 | R101 | 500 | 0.097 | 44.9 | model | logs | 232Mb |
COCO val5k evaluation results can be found in this gist.
The models are also available via torch hub, to load DETR R50 with pretrained weights simply do:
model = torch.hub.load('facebookresearch/detr', 'detr_resnet50', pretrained=True)COCO panoptic val5k models:
| name | backbone | box AP | segm AP | PQ | url | size | |
|---|---|---|---|---|---|---|---|
| 0 | DETR | R50 | 38.8 | 31.1 | 43.4 | download | 165Mb |
| 1 | DETR-DC5 | R50 | 40.2 | 31.9 | 44.6 | download | 165Mb |
| 2 | DETR | R101 | 40.1 | 33 | 45.1 | download | 237Mb |