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