Prepare

Prerequisites

• Python 3.6
• GPU Memory >= 11G
• Numpy
• pytorch 1.2
• OpenCV 4.5

Step 1: Download Datasets and Camstyle aug-data.

• Market-1501 [BaiduYun] [GoogleDriver] CamStyle (generated by CycleGAN) [GoogleDriver] [BaiduYun] (password: 6bu4)

• DukeMTMC-reID [BaiduYun] (password: bhbh) [GoogleDriver] CamStyle (generated by CycleGAN) [GoogleDriver] [BaiduYun] (password: 6bu4)

  Camstyle images generated by GAN are provided by Zhun Zhong

Step 2: Unzip datasets and create folder.

unzip Market-1501 and DukeMTMC-reID datasets to data dir following the below structure.

├── MACM
   ├── data
      ├── market
         ├── bounding_box_train
         ├── bounding_box_test
         ├── query
      ├── duke
         ├── bounding_box_train
         ├── bounding_box_test
         ├── query

Step 3: Generate VotingMask data by SCHP.

1.Down load SCHP and build the required environment following SCHP'readme.md.

2.Down pretrained model LIP and put it into SCHP/models/lip

3.Replace SCHP'simple_extractor.py by our simple_extractor.py.

4.Copy data in MCAM/data/market/bounding_box_train to /SCHP/input and run python simple_extractor.py.

5.Copy VoingMask data in SCHP/output to MACM/data/market/bouding_box_train.

6.Do the same thing to duke.

Step 4: Add Camstyle aug-data and construct dataset for pretrain and cluster.

1.unzip Camstyle aug-data of Market-1501 and DukeMTMC-reID and copy them to MACM/data/market/bounding_box_train and MACM/data/duke/bounding_box_train .

2.run python prepare.py for market.

3.modify download_path as duke in prepare.py and run python prepare.py for duke.

Then,if everything goes well,you will get directory like below structure.

├── MACM
   ├── data
      ├── market
         ├── bounding_box_train
         ├── bounding_box_test
         ├── query
         ├── pytorch
             ├── gallery
             ├── query
             ├── train_aug
             ├── train_aug_newID
             ├── train_ori
             ├── train_ori_newID

Training and Evaluate

For market to duke:

python train_m2d.py

For duke to market:

python train_d2m.py