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Update README.md

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noahshen98
2022-03-24 15:46:03 +08:00
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@@ -70,9 +70,9 @@ CUDA_VISIBLE_DEVICES=0,1,2,3 python -m torch.distributed.launch --nproc_per_node
## Get the submission file
```shell
CUDA_VISIBLE_DEVICES=0,1,2,3 python -m torch.distributed.launch --nproc_per_node=4 lib/main.py --cfgs ./misc/HID/baseline_hid.yaml --phase test
CUDA_VISIBLE_DEVICES=0,1,2,3 python -m torch.distributed.launch --nproc_per_node=4 lib/main.py --cfgs ./config/baseline_GREW.yaml --phase test
```
The result will be generated in your working directory, you must rename and compress it as the requirements before submitting.
## Evaluation locally
While the original grew treat both seq_01 and seq_02 as gallery, but there is no ground truth for probe. Therefore, it is nessesary to upload the submission file on grew competitation. We seperate test set to: seq_01 as gallery, seq_02 as probe. Then you can modify `eval_func` in the `./config/baseline_GREW.yaml` to `identification_real_scene`, you can obtain result localy like setting of OUMVLP.
While the original grew treat both seq_01 and seq_02 as gallery, but there is no ground truth for probe. Therefore, it is nessesary to upload the submission file on grew competitation. We seperate test set to: seq_01 as gallery, seq_02 as probe. Then you can modify `eval_func` in the `./config/baseline_GREW.yaml` to `identification_real_scene`, you can obtain result localy like setting of OUMVLP.