SFT-ReID
This is my implementation of the model proposed in paper SFT-ReID.
My working environment is python3.5.2, and my pytorch version is 1.0.0. If things are not going well on your system, please check you environment.
Get Market1501 dataset
Execute the script in the command line:
$ sh get_market1501.sh
This will download the Market1501 dataset and extract to dataset directory.
Train and Evaluate
- To train the model, just run the training script:
$ python train.py
This will train the model and save the parameters to the directory of res/.
- To embed the gallery and query set with the trained model and compute the accuracy, directly run:
$ python evaluate.py
This will embed the gallery and query set, and then compute cmc and mAP.
Currently, I achieved accuracy of 93.20 rank-1, and 82.98 mAP without post-processing. If post-processing is added, the rank-1 and mAP can be 93.26 and 87.28.