(Re-)implementation of evaluation code for SYSU_MM01 dataset in python
The code is a python translation of the Matlab-code provided by SYSU-MM01 dataset authors here.
Baiduyun: http://pan.baidu.com/s/1gfIlcmZ
Dropbox: https://www.dropbox.com/sh/v036mg1q4yg7awb/AABhxU-FJ4X2oyq7-Ts6bgD0a?dl=0
Please refer the readme file of original Matlab version of evaluation code for more information about the dataset and evaluation protocol.
As per original protocol, the feature vectors are to be stored in .mat files for each camera in a particular directory.
Then you can run the evaluation to get the performance numbers.
check the file src/evaluate_SYSU_MM01.py to locate the function call for evaluation.
evaluate_results(feature_dir, prefix, mode, number_shot, total_runs=10)
# feature_dir = the directory path where the camera based features are stored
# prefix = prefix of the files or model name
# mode = all | indoor
# number_shot = 1 = single-shot | 10 = multi-shot
# total_runs = number of test iterations to run (usually 10, as given in the original paper)
You can cite the original paper from Wu et al., if you use the dataset.
Ancong Wu, Wei-Shi Zheng, Hong-Xing Yu, Shaogang Gong and Jianhuang Lai. RGB-Infrared Cross-Modality Person Re-Identification. IEEE International Conference on Computer Vision (ICCV), 2017.