Skip to content

Conversation

@Xuanmeng-Zhang
Copy link

Hi, Xingyu!
I integrate the re-ranking into fast-reid. As suggested, the modified code can make users use the GPU-reranking by changing config. I have tested the code in Market1501 with market_sbs_R101-ibn.pth and the result is all right as shown below.

07/31 15:10:57 fastreid.evaluation.reid_evaluation]: Test with gpu real-time rerank setting
[07/31 15:11:05 fastreid.engine.defaults]: Evaluation results for Market1501 in csv format:
[07/31 15:11:05 fastreid.evaluation.testing]: Evaluation results in csv format: 
| Dataset    | Rank-1   | Rank-5   | Rank-10   | mAP   | mINP   | metric   |
|:-----------|:---------|:---------|:----------|:------|:-------|:---------|
| Market1501 | 96.35    | 98.43    | 98.84     | 95.23 | 90.53  | 95.79    |

The method is as follows.

  1. Compile the code of gpu re-ranking .
    cd fastreid/evaluation/extension; sh make.sh
  2. When evaluating, we can use GPU-reranking by changing config.
python3 tools/train_net.py --config-file ./configs/Market1501/bagtricks_R50.yml --eval-only \
TEST.GPU_RERANK.ENABLED True MODEL.WEIGHTS /path/to/checkpoint_file MODEL.DEVICE "cuda:0"

@L1aoXingyu
Copy link
Member

Thanks for your great work! I will check it later.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Labels

None yet

Projects

None yet

Development

Successfully merging this pull request may close these issues.

3 participants