Closed Ehsan-Yaghoubi closed 4 years ago
Yes, it's not exactly the same as dangweili's project, but they provide a good example.
The label
in MultiLabelDataset
class means the file that encoding the mapping between image name and its ground-truth (GT vector should contain only 0 or 1 values).
For PETA and PA-100K, they provide the same format, just download it from the official websites (be careful about GT values since some of them using -1 or 1).
For RAP, they only provide .mat
files, which need to be processed according to their ReadMe.txt
(sorry I can't find my scripts but it's not difficult).
I've uploaded the label lists.
Could you please explain about the dataset preparation. Is it similar to this project? (https://github.com/dangweili/pedestrian-attribute-recognition-pytorch)
I used this script (https://github.com/dangweili/pedestrian-attribute-recognition-pytorch/blob/master/script/dataset/transform_peta.py) to prepare the
peta
dataset. It is producing a.pkl
file. But, in your codes, you don't analyze.pkl
files!What should be the type of the
label
in the__init__
function of theMultiLabelDataset
class?I appreciate your clarification about dataset preparation.
Could you please explain about the dataset preparation. Is it similar to this project? (https://github.com/dangweili/pedestrian-attribute-recognition-pytorch)
I used this script (https://github.com/dangweili/pedestrian-attribute-recognition-pytorch/blob/master/script/dataset/transform_peta.py) to prepare the
peta
dataset. It is producing a.pkl
file. But, in your codes, you don't analyze.pkl
files!What should be the type of the
label
in the__init__
function of theMultiLabelDataset
class?I appreciate your clarification about dataset preparation.