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PTCR_MindSpore

This is a MindSpore Ascend implementation of the PTCR proposed in Pyramidal Transformer with Conv-Patchify for Person Re-identification.

Environment

  • Python 3.8
  • MindSpore 2.0.0 (Ascend)
  • mindcv

Usage

  • Organize datasets as below
├──"DATASETS.ROOT_DIR" in /src/PTCR_MindSpore.yaml
   ├──market1501
      ├──Market-1501
         ├──bounding_box_train
         ├──query
         ├──bounding_box_test
   ├──dukemtmc-reid
      ├──DukeMTMC-reID
         ├──bounding_box_train
         ├──query
         ├──bounding_box_test
   ├──cuhk03
      ├──cuhk03_release
         ├──cuhk-03.mat
         ├──cuhk03_new_protocol_config_labeled.mat
         ├──cuhk03_new_protocol_config_detected.mat
   ├──msmt17
      ├──MSMT17_V1
         ├──train
         ├──test
         ├──list_val.txt
         ├──list_train.txt
         ├──list_query.txt
         ├──list_query.txt
  • Set your own "OUTPUT_DIR " in /src/PTCR_MindSpore.yaml
  • Set your own "DATASETS.NAMES " in /src/PTCR_MindSpore.yaml:{market1501、dukemtmcreid、cuhk03、msmt17}
  • Train
python train.py
  • Test
python test.py
  • Checkpoint
  • you can download the pretrained weight for train from Google Drive
  • you can download the finetuned weight for evaluation from Google Drive