| Collections: | |
| - Name: DETR | |
| Metadata: | |
| Training Data: COCO | |
| Training Techniques: | |
| - AdamW | |
| - Multi Scale Train | |
| - Gradient Clip | |
| Training Resources: 8x V100 GPUs | |
| Architecture: | |
| - ResNet | |
| - Transformer | |
| Paper: | |
| URL: https://arxiv.org/abs/2005.12872 | |
| Title: 'End-to-End Object Detection with Transformers' | |
| README: configs/detr/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.7.0/mmdet/models/detectors/detr.py#L7 | |
| Version: v2.7.0 | |
| Models: | |
| - Name: detr_r50_8xb2-150e_coco | |
| In Collection: DETR | |
| Config: configs/detr/detr_r50_8xb2-150e_coco.py | |
| Metadata: | |
| Training Memory (GB): 7.9 | |
| Epochs: 150 | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 39.9 | |
| Weights: https://download.openmmlab.com/mmdetection/v3.0/detr/detr_r50_8xb2-150e_coco/detr_r50_8xb2-150e_coco_20221023_153551-436d03e8.pth | |