Fresh Challenge
Please refer to install.md for installation and dataset preparation.
Please see getting_started.md for the basic usage of MMDetection.
Link the dataset to the folder "./data/" under this repo.
ln -s path/to/dataset data
./tools/dist_train.sh local_config/atss_r50_fpn_ms12.py 8
Note that the model of this example is trained under 8-GPU settings. If you donot have enough GPU cards, try to adjust some related settings for efficient training.
Run test_example.ipynb to see detected results (see as follows) of pretrained baseline model. The baseline model is relatively weak, try your best to improve it~!
Pay attention to the constraints of the complexity for your detectors. The following commands are used for official judgements, with 640x400 images for inference.
python3 ./tools/get_flops.py local_config/atss_r50_fpn_ms12.py --shape 640 400
python3 ./tools/benchmark.py local_config/atss_r50_fpn_ms12.py pretrain_model/atss_r50_fpn_ms12.model --fuse-conv-bn
MMDetection is an open source project that is contributed by researchers and engineers from various colleges and companies. The technical report is on ArXiv.
Documentation: https://mmdetection.readthedocs.io/
The branch works with PyTorch 1.3 to 1.5.
This project is released under the Apache 2.0 license.
截止7.28提交队伍的成绩如下，经代码核验成绩均有效。
| 排名 | 队伍英文名 | 性能 | 测速(fps) | Flops(GMac) | Params (M) |
|---|---|---|---|---|---|
| 1 | Faster_Better | 80.4 | 99.3 | 19.05 | 10.72 |
| 2 | xitianqujing | 80.2 | 51.7 | 33.03 | 26.30 |
| 3 | flying | 79.0 | 27.2 | 19.04 | 14.65 |
截止7.8提交队伍的成绩如下，经代码核验成绩均有效。
| 排名 | 队伍英文名 | 性能 | 测速(fps) | Flops(GMac) | Params (M) |
|---|---|---|---|---|---|
| 1 | Faster_Better | 76.7 | 98.5 | 16.88 | 10.66 |
| 2 | xitianqujing | 75.7 | 51.4 | 10.32 | 6.58 |
| 3 | flying | 39.0 | 52.4 | 9.93 | 6.35 |