2019-03-25 01:22:43 +08:00
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< h1 > Source code for torchreid.data.datamanager< / h1 > < div class = "highlight" > < pre >
< span > < / span > < span class = "kn" > from< / span > < span class = "nn" > __future__< / span > < span class = "k" > import< / span > < span class = "n" > absolute_import< / span >
< span class = "kn" > from< / span > < span class = "nn" > __future__< / span > < span class = "k" > import< / span > < span class = "n" > print_function< / span >
< span class = "kn" > from< / span > < span class = "nn" > __future__< / span > < span class = "k" > import< / span > < span class = "n" > division< / span >
< span class = "kn" > import< / span > < span class = "nn" > torch< / span >
< span class = "kn" > from< / span > < span class = "nn" > torchreid.data.sampler< / span > < span class = "k" > import< / span > < span class = "n" > build_train_sampler< / span >
< span class = "kn" > from< / span > < span class = "nn" > torchreid.data.transforms< / span > < span class = "k" > import< / span > < span class = "n" > build_transforms< / span >
< span class = "kn" > from< / span > < span class = "nn" > torchreid.data.datasets< / span > < span class = "k" > import< / span > < span class = "n" > init_image_dataset< / span > < span class = "p" > ,< / span > < span class = "n" > init_video_dataset< / span >
< div class = "viewcode-block" id = "DataManager" > < a class = "viewcode-back" href = "../../../pkg/data.html#torchreid.data.datamanager.DataManager" > [docs]< / a > < span class = "k" > class< / span > < span class = "nc" > DataManager< / span > < span class = "p" > (< / span > < span class = "nb" > object< / span > < span class = "p" > ):< / span >
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< span class = "sa" > r< / span > < span class = "sd" > " " " Base data manager.< / span >
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< span class = "sd" > Args:< / span >
< span class = "sd" > sources (str or list): source dataset(s).< / span >
< span class = "sd" > targets (str or list, optional): target dataset(s). If not given,< / span >
< span class = "sd" > it equals to ``sources``.< / span >
< span class = "sd" > height (int, optional): target image height. Default is 256.< / span >
< span class = "sd" > width (int, optional): target image width. Default is 128.< / span >
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< span class = "sd" > transforms (str or list of str, optional): transformations applied to model training.< / span >
< span class = "sd" > Default is ' random_flip' .< / span >
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< span class = "sd" > use_cpu (bool, optional): use cpu. Default is False.< / span >
< span class = "sd" > " " " < / span >
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< span class = "k" > def< / span > < span class = "nf" > __init__< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "p" > ,< / span > < span class = "n" > sources< / span > < span class = "o" > =< / span > < span class = "kc" > None< / span > < span class = "p" > ,< / span > < span class = "n" > targets< / span > < span class = "o" > =< / span > < span class = "kc" > None< / span > < span class = "p" > ,< / span > < span class = "n" > height< / span > < span class = "o" > =< / span > < span class = "mi" > 256< / span > < span class = "p" > ,< / span > < span class = "n" > width< / span > < span class = "o" > =< / span > < span class = "mi" > 128< / span > < span class = "p" > ,< / span > < span class = "n" > transforms< / span > < span class = "o" > =< / span > < span class = "s1" > ' random_flip' < / span > < span class = "p" > ,< / span >
< span class = "n" > use_cpu< / span > < span class = "o" > =< / span > < span class = "kc" > False< / span > < span class = "p" > ):< / span >
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< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > sources< / span > < span class = "o" > =< / span > < span class = "n" > sources< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > targets< / span > < span class = "o" > =< / span > < span class = "n" > targets< / span >
< span class = "k" > if< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > sources< / span > < span class = "ow" > is< / span > < span class = "kc" > None< / span > < span class = "p" > :< / span >
< span class = "k" > raise< / span > < span class = "ne" > ValueError< / span > < span class = "p" > (< / span > < span class = "s1" > ' sources must not be None' < / span > < span class = "p" > )< / span >
< span class = "k" > if< / span > < span class = "nb" > isinstance< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > sources< / span > < span class = "p" > ,< / span > < span class = "nb" > str< / span > < span class = "p" > ):< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > sources< / span > < span class = "o" > =< / span > < span class = "p" > [< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > sources< / span > < span class = "p" > ]< / span >
< span class = "k" > if< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > targets< / span > < span class = "ow" > is< / span > < span class = "kc" > None< / span > < span class = "p" > :< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > targets< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > sources< / span >
< span class = "k" > if< / span > < span class = "nb" > isinstance< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > targets< / span > < span class = "p" > ,< / span > < span class = "nb" > str< / span > < span class = "p" > ):< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > targets< / span > < span class = "o" > =< / span > < span class = "p" > [< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > targets< / span > < span class = "p" > ]< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > transform_tr< / span > < span class = "p" > ,< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > transform_te< / span > < span class = "o" > =< / span > < span class = "n" > build_transforms< / span > < span class = "p" > (< / span >
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< span class = "n" > height< / span > < span class = "p" > ,< / span > < span class = "n" > width< / span > < span class = "p" > ,< / span > < span class = "n" > transforms< / span >
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< span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > use_gpu< / span > < span class = "o" > =< / span > < span class = "p" > (< / span > < span class = "n" > torch< / span > < span class = "o" > .< / span > < span class = "n" > cuda< / span > < span class = "o" > .< / span > < span class = "n" > is_available< / span > < span class = "p" > ()< / span > < span class = "ow" > and< / span > < span class = "ow" > not< / span > < span class = "n" > use_cpu< / span > < span class = "p" > )< / span >
< span class = "nd" > @property< / span >
< span class = "k" > def< / span > < span class = "nf" > num_train_pids< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "p" > ):< / span >
< span class = "sd" > " " " Returns the number of training person identities." " " < / span >
< span class = "k" > return< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > _num_train_pids< / span >
< span class = "nd" > @property< / span >
< span class = "k" > def< / span > < span class = "nf" > num_train_cams< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "p" > ):< / span >
< span class = "sd" > " " " Returns the number of training cameras." " " < / span >
< span class = "k" > return< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > _num_train_cams< / span >
< div class = "viewcode-block" id = "DataManager.return_dataloaders" > < a class = "viewcode-back" href = "../../../pkg/data.html#torchreid.data.datamanager.DataManager.return_dataloaders" > [docs]< / a > < span class = "k" > def< / span > < span class = "nf" > return_dataloaders< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "p" > ):< / span >
< span class = "sd" > " " " Returns trainloader and testloader." " " < / span >
< span class = "k" > return< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > trainloader< / span > < span class = "p" > ,< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > testloader< / span > < / div >
< div class = "viewcode-block" id = "DataManager.return_testdataset_by_name" > < a class = "viewcode-back" href = "../../../pkg/data.html#torchreid.data.datamanager.DataManager.return_testdataset_by_name" > [docs]< / a > < span class = "k" > def< / span > < span class = "nf" > return_testdataset_by_name< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "p" > ,< / span > < span class = "n" > name< / span > < span class = "p" > ):< / span >
< span class = "sd" > " " " Returns query and gallery of a test dataset, each containing< / span >
< span class = "sd" > tuples of (img_path(s), pid, camid).< / span >
< span class = "sd" > Args:< / span >
< span class = "sd" > name (str): dataset name.< / span >
< span class = "sd" > " " " < / span >
< span class = "k" > return< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > testdataset< / span > < span class = "p" > [< / span > < span class = "n" > name< / span > < span class = "p" > ][< / span > < span class = "s1" > ' query' < / span > < span class = "p" > ],< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > testdataset< / span > < span class = "p" > [< / span > < span class = "n" > name< / span > < span class = "p" > ][< / span > < span class = "s1" > ' gallery' < / span > < span class = "p" > ]< / span > < / div > < / div >
< div class = "viewcode-block" id = "ImageDataManager" > < a class = "viewcode-back" href = "../../../pkg/data.html#torchreid.data.datamanager.ImageDataManager" > [docs]< / a > < span class = "k" > class< / span > < span class = "nc" > ImageDataManager< / span > < span class = "p" > (< / span > < span class = "n" > DataManager< / span > < span class = "p" > ):< / span >
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< span class = "sa" > r< / span > < span class = "sd" > " " " Image data manager.< / span >
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< span class = "sd" > Args:< / span >
< span class = "sd" > root (str): root path to datasets.< / span >
< span class = "sd" > sources (str or list): source dataset(s).< / span >
< span class = "sd" > targets (str or list, optional): target dataset(s). If not given,< / span >
< span class = "sd" > it equals to ``sources``.< / span >
< span class = "sd" > height (int, optional): target image height. Default is 256.< / span >
< span class = "sd" > width (int, optional): target image width. Default is 128.< / span >
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< span class = "sd" > transforms (str or list of str, optional): transformations applied to model training.< / span >
< span class = "sd" > Default is ' random_flip' .< / span >
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< span class = "sd" > use_cpu (bool, optional): use cpu. Default is False.< / span >
< span class = "sd" > split_id (int, optional): split id (*0-based*). Default is 0.< / span >
< span class = "sd" > combineall (bool, optional): combine train, query and gallery in a dataset for< / span >
< span class = "sd" > training. Default is False.< / span >
< span class = "sd" > batch_size (int, optional): number of images in a batch. Default is 32.< / span >
< span class = "sd" > workers (int, optional): number of workers. Default is 4.< / span >
< span class = "sd" > num_instances (int, optional): number of instances per identity in a batch.< / span >
< span class = "sd" > Default is 4.< / span >
< span class = "sd" > train_sampler (str, optional): sampler. Default is empty (``RandomSampler``).< / span >
< span class = "sd" > cuhk03_labeled (bool, optional): use cuhk03 labeled images.< / span >
< span class = "sd" > Default is False (defaul is to use detected images).< / span >
< span class = "sd" > cuhk03_classic_split (bool, optional): use the classic split in cuhk03.< / span >
< span class = "sd" > Default is False.< / span >
< span class = "sd" > market1501_500k (bool, optional): add 500K distractors to the gallery< / span >
< span class = "sd" > set in market1501. Default is False.< / span >
< span class = "sd" > Examples::< / span >
< span class = "sd" > datamanager = torchreid.data.ImageDataManager(< / span >
< span class = "sd" > root=' path/to/reid-data' ,< / span >
< span class = "sd" > sources=' market1501' ,< / span >
< span class = "sd" > height=256,< / span >
< span class = "sd" > width=128,< / span >
< span class = "sd" > batch_size=32< / span >
< span class = "sd" > )< / span >
< span class = "sd" > " " " < / span >
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< span class = "k" > def< / span > < span class = "nf" > __init__< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "p" > ,< / span > < span class = "n" > root< / span > < span class = "o" > =< / span > < span class = "s1" > ' ' < / span > < span class = "p" > ,< / span > < span class = "n" > sources< / span > < span class = "o" > =< / span > < span class = "kc" > None< / span > < span class = "p" > ,< / span > < span class = "n" > targets< / span > < span class = "o" > =< / span > < span class = "kc" > None< / span > < span class = "p" > ,< / span > < span class = "n" > height< / span > < span class = "o" > =< / span > < span class = "mi" > 256< / span > < span class = "p" > ,< / span > < span class = "n" > width< / span > < span class = "o" > =< / span > < span class = "mi" > 128< / span > < span class = "p" > ,< / span > < span class = "n" > transforms< / span > < span class = "o" > =< / span > < span class = "s1" > ' random_flip' < / span > < span class = "p" > ,< / span >
< span class = "n" > use_cpu< / span > < span class = "o" > =< /span>< span class = "kc" > False< / span > < span class = "p" > ,< / span > < span class = "n" > split_id< / span > < span class = "o" > =< / span > < span class = "mi" > 0< / span > < span class = "p" > ,< / span > < span class = "n" > combineall< / span > < span class = "o" > =< / span > < span class = "kc" > False< / span > < span class = "p" > ,< / span >
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< span class = "n" > batch_size< / span > < span class = "o" > =< / span > < span class = "mi" > 32< / span > < span class = "p" > ,< / span > < span class = "n" > workers< / span > < span class = "o" > =< / span > < span class = "mi" > 4< / span > < span class = "p" > ,< / span > < span class = "n" > num_instances< / span > < span class = "o" > =< / span > < span class = "mi" > 4< / span > < span class = "p" > ,< / span > < span class = "n" > train_sampler< / span > < span class = "o" > =< / span > < span class = "s1" > ' ' < / span > < span class = "p" > ,< / span >
< span class = "n" > cuhk03_labeled< / span > < span class = "o" > =< / span > < span class = "kc" > False< / span > < span class = "p" > ,< / span > < span class = "n" > cuhk03_classic_split< / span > < span class = "o" > =< / span > < span class = "kc" > False< / span > < span class = "p" > ,< / span > < span class = "n" > market1501_500k< / span > < span class = "o" > =< / span > < span class = "kc" > False< / span > < span class = "p" > ):< / span >
< span class = "nb" > super< / span > < span class = "p" > (< / span > < span class = "n" > ImageDataManager< / span > < span class = "p" > ,< / span > < span class = "bp" > self< / span > < span class = "p" > )< / span > < span class = "o" > .< / span > < span class = "fm" > __init__< / span > < span class = "p" > (< / span > < span class = "n" > sources< / span > < span class = "o" > =< / span > < span class = "n" > sources< / span > < span class = "p" > ,< / span > < span class = "n" > targets< / span > < span class = "o" > =< / span > < span class = "n" > targets< / span > < span class = "p" > ,< / span > < span class = "n" > height< / span > < span class = "o" > =< / span > < span class = "n" > height< / span > < span class = "p" > ,< / span > < span class = "n" > width< / span > < span class = "o" > =< / span > < span class = "n" > width< / span > < span class = "p" > ,< / span >
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< span class = "n" > transforms< / span > < span class = "o" > =< / span > < span class = "n" > transforms< / span > < span class = "p" > ,< / span > < span class = "n" > use_cpu< / span > < span class = "o" > =< / span > < span class = "n" > use_cpu< / span > < span class = "p" > )< / span >
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< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "s1" > ' => Loading train (source) dataset' < / span > < span class = "p" > )< / span >
< span class = "n" > trainset< / span > < span class = "o" > =< / span > < span class = "p" > []< / span >
< span class = "k" > for< / span > < span class = "n" > name< / span > < span class = "ow" > in< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > sources< / span > < span class = "p" > :< / span >
< span class = "n" > trainset_< / span > < span class = "o" > =< / span > < span class = "n" > init_image_dataset< / span > < span class = "p" > (< / span >
< span class = "n" > name< / span > < span class = "p" > ,< / span >
< span class = "n" > transform< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > transform_tr< / span > < span class = "p" > ,< / span >
< span class = "n" > mode< / span > < span class = "o" > =< / span > < span class = "s1" > ' train' < / span > < span class = "p" > ,< / span >
< span class = "n" > combineall< / span > < span class = "o" > =< / span > < span class = "n" > combineall< / span > < span class = "p" > ,< / span >
< span class = "n" > root< / span > < span class = "o" > =< / span > < span class = "n" > root< / span > < span class = "p" > ,< / span >
< span class = "n" > split_id< / span > < span class = "o" > =< / span > < span class = "n" > split_id< / span > < span class = "p" > ,< / span >
< span class = "n" > cuhk03_labeled< / span > < span class = "o" > =< / span > < span class = "n" > cuhk03_labeled< / span > < span class = "p" > ,< / span >
< span class = "n" > cuhk03_classic_split< / span > < span class = "o" > =< / span > < span class = "n" > cuhk03_classic_split< / span > < span class = "p" > ,< / span >
< span class = "n" > market1501_500k< / span > < span class = "o" > =< / span > < span class = "n" > market1501_500k< / span >
< span class = "p" > )< / span >
< span class = "n" > trainset< / span > < span class = "o" > .< / span > < span class = "n" > append< / span > < span class = "p" > (< / span > < span class = "n" > trainset_< / span > < span class = "p" > )< / span >
< span class = "n" > trainset< / span > < span class = "o" > =< / span > < span class = "nb" > sum< / span > < span class = "p" > (< / span > < span class = "n" > trainset< / span > < span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > _num_train_pids< / span > < span class = "o" > =< / span > < span class = "n" > trainset< / span > < span class = "o" > .< / span > < span class = "n" > num_train_pids< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > _num_train_cams< / span > < span class = "o" > =< / span > < span class = "n" > trainset< / span > < span class = "o" > .< / span > < span class = "n" > num_train_cams< / span >
< span class = "n" > train_sampler< / span > < span class = "o" > =< / span > < span class = "n" > build_train_sampler< / span > < span class = "p" > (< / span >
< span class = "n" > trainset< / span > < span class = "o" > .< / span > < span class = "n" > train< / span > < span class = "p" > ,< / span > < span class = "n" > train_sampler< / span > < span class = "p" > ,< / span >
< span class = "n" > batch_size< / span > < span class = "o" > =< / span > < span class = "n" > batch_size< / span > < span class = "p" > ,< / span >
< span class = "n" > num_instances< / span > < span class = "o" > =< / span > < span class = "n" > num_instances< / span >
< span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > trainloader< / span > < span class = "o" > =< / span > < span class = "n" > torch< / span > < span class = "o" > .< / span > < span class = "n" > utils< / span > < span class = "o" > .< / span > < span class = "n" > data< / span > < span class = "o" > .< / span > < span class = "n" > DataLoader< / span > < span class = "p" > (< / span >
< span class = "n" > trainset< / span > < span class = "p" > ,< / span >
< span class = "n" > sampler< / span > < span class = "o" > =< / span > < span class = "n" > train_sampler< / span > < span class = "p" > ,< / span >
< span class = "n" > batch_size< / span > < span class = "o" > =< / span > < span class = "n" > batch_size< / span > < span class = "p" > ,< / span >
< span class = "n" > shuffle< / span > < span class = "o" > =< / span > < span class = "kc" > False< / span > < span class = "p" > ,< / span >
< span class = "n" > num_workers< / span > < span class = "o" > =< / span > < span class = "n" > workers< / span > < span class = "p" > ,< / span >
< span class = "n" > pin_memory< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > use_gpu< / span > < span class = "p" > ,< / span >
< span class = "n" > drop_last< / span > < span class = "o" > =< / span > < span class = "kc" > True< / span >
< span class = "p" > )< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "s1" > ' => Loading test (target) dataset' < / span > < span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > testloader< / span > < span class = "o" > =< / span > < span class = "p" > {< / span > < span class = "n" > name< / span > < span class = "p" > :< / span > < span class = "p" > {< / span > < span class = "s1" > ' query' < / span > < span class = "p" > :< / span > < span class = "kc" > None< / span > < span class = "p" > ,< / span > < span class = "s1" > ' gallery' < / span > < span class = "p" > :< / span > < span class = "kc" > None< / span > < span class = "p" > }< / span > < span class = "k" > for< / span > < span class = "n" > name< / span > < span class = "ow" > in< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > targets< / span > < span class = "p" > }< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > testdataset< / span > < span class = "o" > =< / span > < span class = "p" > {< / span > < span class = "n" > name< / span > < span class = "p" > :< / span > < span class = "p" > {< / span > < span class = "s1" > ' query' < / span > < span class = "p" > :< / span > < span class = "kc" > None< / span > < span class = "p" > ,< / span > < span class = "s1" > ' gallery' < / span > < span class = "p" > :< / span > < span class = "kc" > None< / span > < span class = "p" > }< / span > < span class = "k" > for< / span > < span class = "n" > name< / span > < span class = "ow" > in< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > targets< / span > < span class = "p" > }< / span >
< span class = "k" > for< / span > < span class = "n" > name< / span > < span class = "ow" > in< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > targets< / span > < span class = "p" > :< / span >
< span class = "c1" > # build query loader< / span >
< span class = "n" > queryset< / span > < span class = "o" > =< / span > < span class = "n" > init_image_dataset< / span > < span class = "p" > (< / span >
< span class = "n" > name< / span > < span class = "p" > ,< / span >
< span class = "n" > transform< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > transform_te< / span > < span class = "p" > ,< / span >
< span class = "n" > mode< / span > < span class = "o" > =< / span > < span class = "s1" > ' query' < / span > < span class = "p" > ,< / span >
< span class = "n" > combineall< / span > < span class = "o" > =< / span > < span class = "n" > combineall< / span > < span class = "p" > ,< / span >
< span class = "n" > root< / span > < span class = "o" > =< / span > < span class = "n" > root< / span > < span class = "p" > ,< / span >
< span class = "n" > split_id< / span > < span class = "o" > =< / span > < span class = "n" > split_id< / span > < span class = "p" > ,< / span >
< span class = "n" > cuhk03_labeled< / span > < span class = "o" > =< / span > < span class = "n" > cuhk03_labeled< / span > < span class = "p" > ,< / span >
< span class = "n" > cuhk03_classic_split< / span > < span class = "o" > =< / span > < span class = "n" > cuhk03_classic_split< / span > < span class = "p" > ,< / span >
< span class = "n" > market1501_500k< / span > < span class = "o" > =< / span > < span class = "n" > market1501_500k< / span >
< span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > testloader< / span > < span class = "p" > [< / span > < span class = "n" > name< / span > < span class = "p" > ][< / span > < span class = "s1" > ' query' < / span > < span class = "p" > ]< / span > < span class = "o" > =< / span > < span class = "n" > torch< / span > < span class = "o" > .< / span > < span class = "n" > utils< / span > < span class = "o" > .< / span > < span class = "n" > data< / span > < span class = "o" > .< / span > < span class = "n" > DataLoader< / span > < span class = "p" > (< / span >
< span class = "n" > queryset< / span > < span class = "p" > ,< / span >
< span class = "n" > batch_size< / span > < span class = "o" > =< / span > < span class = "n" > batch_size< / span > < span class = "p" > ,< / span >
< span class = "n" > shuffle< / span > < span class = "o" > =< / span > < span class = "kc" > False< / span > < span class = "p" > ,< / span >
< span class = "n" > num_workers< / span > < span class = "o" > =< / span > < span class = "n" > workers< / span > < span class = "p" > ,< / span >
< span class = "n" > pin_memory< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > use_gpu< / span > < span class = "p" > ,< / span >
< span class = "n" > drop_last< / span > < span class = "o" > =< / span > < span class = "kc" > False< / span >
< span class = "p" > )< / span >
< span class = "c1" > # build gallery loader< / span >
< span class = "n" > galleryset< / span > < span class = "o" > =< / span > < span class = "n" > init_image_dataset< / span > < span class = "p" > (< / span >
< span class = "n" > name< / span > < span class = "p" > ,< / span >
< span class = "n" > transform< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > transform_te< / span > < span class = "p" > ,< / span >
< span class = "n" > mode< / span > < span class = "o" > =< / span > < span class = "s1" > ' gallery' < / span > < span class = "p" > ,< / span >
< span class = "n" > combineall< / span > < span class = "o" > =< / span > < span class = "n" > combineall< / span > < span class = "p" > ,< / span >
< span class = "n" > verbose< / span > < span class = "o" > =< / span > < span class = "kc" > False< / span > < span class = "p" > ,< / span >
< span class = "n" > root< / span > < span class = "o" > =< / span > < span class = "n" > root< / span > < span class = "p" > ,< / span >
< span class = "n" > split_id< / span > < span class = "o" > =< / span > < span class = "n" > split_id< / span > < span class = "p" > ,< / span >
< span class = "n" > cuhk03_labeled< / span > < span class = "o" > =< / span > < span class = "n" > cuhk03_labeled< / span > < span class = "p" > ,< / span >
< span class = "n" > cuhk03_classic_split< / span > < span class = "o" > =< / span > < span class = "n" > cuhk03_classic_split< / span > < span class = "p" > ,< / span >
< span class = "n" > market1501_500k< / span > < span class = "o" > =< / span > < span class = "n" > market1501_500k< / span >
< span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > testloader< / span > < span class = "p" > [< / span > < span class = "n" > name< / span > < span class = "p" > ][< / span > < span class = "s1" > ' gallery' < / span > < span class = "p" > ]< / span > < span class = "o" > =< / span > < span class = "n" > torch< / span > < span class = "o" > .< / span > < span class = "n" > utils< / span > < span class = "o" > .< / span > < span class = "n" > data< / span > < span class = "o" > .< / span > < span class = "n" > DataLoader< / span > < span class = "p" > (< / span >
< span class = "n" > galleryset< / span > < span class = "p" > ,< / span >
< span class = "n" > batch_size< / span > < span class = "o" > =< / span > < span class = "n" > batch_size< / span > < span class = "p" > ,< / span >
< span class = "n" > shuffle< / span > < span class = "o" > =< / span > < span class = "kc" > False< / span > < span class = "p" > ,< / span >
< span class = "n" > num_workers< / span > < span class = "o" > =< / span > < span class = "n" > workers< / span > < span class = "p" > ,< / span >
< span class = "n" > pin_memory< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > use_gpu< / span > < span class = "p" > ,< / span >
< span class = "n" > drop_last< / span > < span class = "o" > =< / span > < span class = "kc" > False< / span >
< span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > testdataset< / span > < span class = "p" > [< / span > < span class = "n" > name< / span > < span class = "p" > ][< / span > < span class = "s1" > ' query' < / span > < span class = "p" > ]< / span > < span class = "o" > =< / span > < span class = "n" > queryset< / span > < span class = "o" > .< / span > < span class = "n" > query< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > testdataset< / span > < span class = "p" > [< / span > < span class = "n" > name< / span > < span class = "p" > ][< / span > < span class = "s1" > ' gallery' < / span > < span class = "p" > ]< / span > < span class = "o" > =< / span > < span class = "n" > galleryset< / span > < span class = "o" > .< / span > < span class = "n" > gallery< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "s1" > ' < / span > < span class = "se" > \n< / span > < span class = "s1" > ' < / span > < span class = "p" > )< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "s1" > ' **************** Summary ****************' < / span > < span class = "p" > )< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "s1" > ' train : < / span > < span class = "si" > {}< / span > < span class = "s1" > ' < / span > < span class = "o" > .< / span > < span class = "n" > format< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > sources< / span > < span class = "p" > ))< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "s1" > ' # train datasets : < / span > < span class = "si" > {}< / span > < span class = "s1" > ' < / span > < span class = "o" > .< / span > < span class = "n" > format< / span > < span class = "p" > (< / span > < span class = "nb" > len< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > sources< / span > < span class = "p" > )))< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "s1" > ' # train ids : < / span > < span class = "si" > {}< / span > < span class = "s1" > ' < / span > < span class = "o" > .< / span > < span class = "n" > format< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > num_train_pids< / span > < span class = "p" > ))< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "s1" > ' # train images : < / span > < span class = "si" > {}< / span > < span class = "s1" > ' < / span > < span class = "o" > .< / span > < span class = "n" > format< / span > < span class = "p" > (< / span > < span class = "nb" > len< / span > < span class = "p" > (< / span > < span class = "n" > trainset< / span > < span class = "p" > )))< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "s1" > ' # train cameras : < / span > < span class = "si" > {}< / span > < span class = "s1" > ' < / span > < span class = "o" > .< / span > < span class = "n" > format< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > num_train_cams< / span > < span class = "p" > ))< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "s1" > ' test : < / span > < span class = "si" > {}< / span > < span class = "s1" > ' < / span > < span class = "o" > .< / span > < span class = "n" > format< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > targets< / span > < span class = "p" > ))< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "s1" > ' *****************************************' < / span > < span class = "p" > )< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "s1" > ' < / span > < span class = "se" > \n< / span > < span class = "s1" > ' < / span > < span class = "p" > )< / span > < / div >
< div class = "viewcode-block" id = "VideoDataManager" > < a class = "viewcode-back" href = "../../../pkg/data.html#torchreid.data.datamanager.VideoDataManager" > [docs]< / a > < span class = "k" > class< / span > < span class = "nc" > VideoDataManager< / span > < span class = "p" > (< / span > < span class = "n" > DataManager< / span > < span class = "p" > ):< / span >
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< span class = "sa" > r< / span > < span class = "sd" > " " " Video data manager.< / span >
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< span class = "sd" > Args:< / span >
< span class = "sd" > root (str): root path to datasets.< / span >
< span class = "sd" > sources (str or list): source dataset(s).< / span >
< span class = "sd" > targets (str or list, optional): target dataset(s). If not given,< / span >
< span class = "sd" > it equals to ``sources``.< / span >
< span class = "sd" > height (int, optional): target image height. Default is 256.< / span >
< span class = "sd" > width (int, optional): target image width. Default is 128.< / span >
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< span class = "sd" > transforms (str or list of str, optional): transformations applied to model training.< / span >
< span class = "sd" > Default is ' random_flip' .< / span >
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< span class = "sd" > use_cpu (bool, optional): use cpu. Default is False.< / span >
< span class = "sd" > split_id (int, optional): split id (*0-based*). Default is 0.< / span >
< span class = "sd" > combineall (bool, optional): combine train, query and gallery in a dataset for< / span >
< span class = "sd" > training. Default is False.< / span >
< span class = "sd" > batch_size (int, optional): number of *tracklets* in a batch. Default is 3.< / span >
< span class = "sd" > workers (int, optional): number of workers. Default is 4.< / span >
< span class = "sd" > num_instances (int, optional): number of instances per identity in a batch.< / span >
< span class = "sd" > Default is 4.< / span >
< span class = "sd" > train_sampler (str, optional): sampler. Default is empty (``RandomSampler``).< / span >
< span class = "sd" > seq_len (int, optional): how many images to sample in a tracklet. Default is 15.< / span >
< span class = "sd" > sample_method (str, optional): how to sample images in a tracklet. Default is " evenly" .< / span >
< span class = "sd" > Choices are [" evenly" , " random" , " all" ]. " evenly" and " random" sample ``seq_len``< / span >
< span class = "sd" > images in a tracklet while " all" samples all images in a tracklet, thus ``batch_size``< / span >
< span class = "sd" > needs to be set to 1.< / span >
< span class = "sd" > Examples::< / span >
< span class = "sd" > datamanager = torchreid.data.VideoDataManager(< / span >
< span class = "sd" > root=' path/to/reid-data' ,< / span >
< span class = "sd" > sources=' mars' ,< / span >
< span class = "sd" > height=256,< / span >
< span class = "sd" > width=128,< / span >
< span class = "sd" > batch_size=3,< / span >
< span class = "sd" > seq_len=15,< / span >
< span class = "sd" > sample_method=' evenly' < / span >
< span class = "sd" > )< / span >
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< span class = "sd" > .. note::< / span >
< span class = "sd" > The current implementation only supports image-like training. Therefore, each image in a< / span >
< span class = "sd" > sampled tracklet will undergo independent transformation functions. To achieve tracklet-aware< / span >
< span class = "sd" > training, you need to modify the transformation functions for video reid such that each function< / span >
< span class = "sd" > applies the same operation to all images in a tracklet to keep consistency.< / span >
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< span class = "sd" > " " " < / span >
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< span class = "k" > def< / span > < span class = "nf" > __init__< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "p" > ,< / span > < span class = "n" > root< / span > < span class = "o" > =< / span > < span class = "s1" > ' ' < / span > < span class = "p" > ,< / span > < span class = "n" > sources< / span > < span class = "o" > =< / span > < span class = "kc" > None< / span > < span class = "p" > ,< / span > < span class = "n" > targets< / span > < span class = "o" > =< / span > < span class = "kc" > None< / span > < span class = "p" > ,< / span > < span class = "n" > height< / span > < span class = "o" > =< / span > < span class = "mi" > 256< / span > < span class = "p" > ,< / span > < span class = "n" > width< / span > < span class = "o" > =< / span > < span class = "mi" > 128< / span > < span class = "p" > ,< / span > < span class = "n" > transforms< / span > < span class = "o" > =< / span > < span class = "s1" > ' random_flip' < / span > < span class = "p" > ,< / span >
< span class = "n" > use_cpu< / span > < span class = "o" > =< / span > < span class = "kc" > False< / span > < span class = "p" > ,< / span > < span class = "n" > split_id< / span > < span class = "o" > =< / span > < span class = "mi" > 0< / span > < span class = "p" > ,< / span > < span class = "n" > combineall< / span > < span class = "o" > =< / span > < span class = "kc" > False< / span > < span class = "p" > ,< / span >
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< span class = "n" > batch_size< / span > < span class = "o" > =< / span > < span class = "mi" > 3< / span > < span class = "p" > ,< / span > < span class = "n" > workers< / span > < span class = "o" > =< / span > < span class = "mi" > 4< / span > < span class = "p" > ,< / span > < span class = "n" > num_instances< / span > < span class = "o" > =< / span > < span class = "mi" > 4< / span > < span class = "p" > ,< / span > < span class = "n" > train_sampler< / span > < span class = "o" > =< / span > < span class = "kc" > None< / span > < span class = "p" > ,< / span >
< span class = "n" > seq_len< / span > < span class = "o" > =< / span > < span class = "mi" > 15< / span > < span class = "p" > ,< / span > < span class = "n" > sample_method< / span > < span class = "o" > =< / span > < span class = "s1" > ' evenly' < / span > < span class = "p" > ):< / span >
< span class = "nb" > super< / span > < span class = "p" > (< / span > < span class = "n" > VideoDataManager< / span > < span class = "p" > ,< / span > < span class = "bp" > self< / span > < span class = "p" > )< / span > < span class = "o" > .< / span > < span class = "fm" > __init__< / span > < span class = "p" > (< / span > < span class = "n" > sources< / span > < span class = "o" > =< / span > < span class = "n" > sources< / span > < span class = "p" > ,< / span > < span class = "n" > targets< / span > < span class = "o" > =< / span > < span class = "n" > targets< / span > < span class = "p" > ,< / span > < span class = "n" > height< / span > < span class = "o" > =< / span > < span class = "n" > height< / span > < span class = "p" > ,< / span > < span class = "n" > width< / span > < span class = "o" > =< / span > < span class = "n" > width< / span > < span class = "p" > ,< / span >
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< span class = "n" > transforms< / span > < span class = "o" > =< / span > < span class = "n" > transforms< / span > < span class = "p" > ,< / span > < span class = "n" > use_cpu< / span > < span class = "o" > =< / span > < span class = "n" > use_cpu< / span > < span class = "p" > )< / span >
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< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "s1" > ' => Loading train (source) dataset' < / span > < span class = "p" > )< / span >
< span class = "n" > trainset< / span > < span class = "o" > =< / span > < span class = "p" > []< / span >
< span class = "k" > for< / span > < span class = "n" > name< / span > < span class = "ow" > in< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > sources< / span > < span class = "p" > :< / span >
< span class = "n" > trainset_< / span > < span class = "o" > =< / span > < span class = "n" > init_video_dataset< / span > < span class = "p" > (< / span >
< span class = "n" > name< / span > < span class = "p" > ,< / span >
< span class = "n" > transform< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > transform_tr< / span > < span class = "p" > ,< / span >
< span class = "n" > mode< / span > < span class = "o" > =< / span > < span class = "s1" > ' train' < / span > < span class = "p" > ,< / span >
< span class = "n" > combineall< / span > < span class = "o" > =< / span > < span class = "n" > combineall< / span > < span class = "p" > ,< / span >
< span class = "n" > root< / span > < span class = "o" > =< / span > < span class = "n" > root< / span > < span class = "p" > ,< / span >
< span class = "n" > split_id< / span > < span class = "o" > =< / span > < span class = "n" > split_id< / span > < span class = "p" > ,< / span >
< span class = "n" > seq_len< / span > < span class = "o" > =< / span > < span class = "n" > seq_len< / span > < span class = "p" > ,< / span >
< span class = "n" > sample_method< / span > < span class = "o" > =< / span > < span class = "n" > sample_method< / span >
< span class = "p" > )< / span >
< span class = "n" > trainset< / span > < span class = "o" > .< / span > < span class = "n" > append< / span > < span class = "p" > (< / span > < span class = "n" > trainset_< / span > < span class = "p" > )< / span >
< span class = "n" > trainset< / span > < span class = "o" > =< / span > < span class = "nb" > sum< / span > < span class = "p" > (< / span > < span class = "n" > trainset< / span > < span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > _num_train_pids< / span > < span class = "o" > =< / span > < span class = "n" > trainset< / span > < span class = "o" > .< / span > < span class = "n" > num_train_pids< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > _num_train_cams< / span > < span class = "o" > =< / span > < span class = "n" > trainset< / span > < span class = "o" > .< / span > < span class = "n" > num_train_cams< / span >
< span class = "n" > train_sampler< / span > < span class = "o" > =< / span > < span class = "n" > build_train_sampler< / span > < span class = "p" > (< / span >
< span class = "n" > trainset< / span > < span class = "o" > .< / span > < span class = "n" > train< / span > < span class = "p" > ,< / span > < span class = "n" > train_sampler< / span > < span class = "p" > ,< / span >
< span class = "n" > batch_size< / span > < span class = "o" > =< / span > < span class = "n" > batch_size< / span > < span class = "p" > ,< / span >
< span class = "n" > num_instances< / span > < span class = "o" > =< / span > < span class = "n" > num_instances< / span >
< span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > trainloader< / span > < span class = "o" > =< / span > < span class = "n" > torch< / span > < span class = "o" > .< / span > < span class = "n" > utils< / span > < span class = "o" > .< / span > < span class = "n" > data< / span > < span class = "o" > .< / span > < span class = "n" > DataLoader< / span > < span class = "p" > (< / span >
< span class = "n" > trainset< / span > < span class = "p" > ,< / span >
< span class = "n" > sampler< / span > < span class = "o" > =< / span > < span class = "n" > train_sampler< / span > < span class = "p" > ,< / span >
< span class = "n" > batch_size< / span > < span class = "o" > =< / span > < span class = "n" > batch_size< / span > < span class = "p" > ,< / span >
< span class = "n" > shuffle< / span > < span class = "o" > =< / span > < span class = "kc" > False< / span > < span class = "p" > ,< / span >
< span class = "n" > num_workers< / span > < span class = "o" > =< / span > < span class = "n" > workers< / span > < span class = "p" > ,< / span >
< span class = "n" > pin_memory< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > use_gpu< / span > < span class = "p" > ,< / span >
< span class = "n" > drop_last< / span > < span class = "o" > =< / span > < span class = "kc" > True< / span >
< span class = "p" > )< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "s1" > ' => Loading test (target) dataset' < / span > < span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > testloader< / span > < span class = "o" > =< / span > < span class = "p" > {< / span > < span class = "n" > name< / span > < span class = "p" > :< / span > < span class = "p" > {< / span > < span class = "s1" > ' query' < / span > < span class = "p" > :< / span > < span class = "kc" > None< / span > < span class = "p" > ,< / span > < span class = "s1" > ' gallery' < / span > < span class = "p" > :< / span > < span class = "kc" > None< / span > < span class = "p" > }< / span > < span class = "k" > for< / span > < span class = "n" > name< / span > < span class = "ow" > in< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > targets< / span > < span class = "p" > }< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > testdataset< / span > < span class = "o" > =< / span > < span class = "p" > {< / span > < span class = "n" > name< / span > < span class = "p" > :< / span > < span class = "p" > {< / span > < span class = "s1" > ' query' < / span > < span class = "p" > :< / span > < span class = "kc" > None< / span > < span class = "p" > ,< / span > < span class = "s1" > ' gallery' < / span > < span class = "p" > :< / span > < span class = "kc" > None< / span > < span class = "p" > }< / span > < span class = "k" > for< / span > < span class = "n" > name< / span > < span class = "ow" > in< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > targets< / span > < span class = "p" > }< / span >
< span class = "k" > for< / span > < span class = "n" > name< / span > < span class = "ow" > in< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > targets< / span > < span class = "p" > :< / span >
< span class = "c1" > # build query loader< / span >
< span class = "n" > queryset< / span > < span class = "o" > =< / span > < span class = "n" > init_video_dataset< / span > < span class = "p" > (< / span >
< span class = "n" > name< / span > < span class = "p" > ,< / span >
< span class = "n" > transform< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > transform_te< / span > < span class = "p" > ,< / span >
< span class = "n" > mode< / span > < span class = "o" > =< / span > < span class = "s1" > ' query' < / span > < span class = "p" > ,< / span >
< span class = "n" > combineall< / span > < span class = "o" > =< / span > < span class = "n" > combineall< / span > < span class = "p" > ,< / span >
< span class = "n" > root< / span > < span class = "o" > =< / span > < span class = "n" > root< / span > < span class = "p" > ,< / span >
< span class = "n" > split_id< / span > < span class = "o" > =< / span > < span class = "n" > split_id< / span > < span class = "p" > ,< / span >
< span class = "n" > seq_len< / span > < span class = "o" > =< / span > < span class = "n" > seq_len< / span > < span class = "p" > ,< / span >
< span class = "n" > sample_method< / span > < span class = "o" > =< / span > < span class = "n" > sample_method< / span >
< span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > testloader< / span > < span class = "p" > [< / span > < span class = "n" > name< / span > < span class = "p" > ][< / span > < span class = "s1" > ' query' < / span > < span class = "p" > ]< / span > < span class = "o" > =< / span > < span class = "n" > torch< / span > < span class = "o" > .< / span > < span class = "n" > utils< / span > < span class = "o" > .< / span > < span class = "n" > data< / span > < span class = "o" > .< / span > < span class = "n" > DataLoader< / span > < span class = "p" > (< / span >
< span class = "n" > queryset< / span > < span class = "p" > ,< / span >
< span class = "n" > batch_size< / span > < span class = "o" > =< / span > < span class = "n" > batch_size< / span > < span class = "p" > ,< / span >
< span class = "n" > shuffle< / span > < span class = "o" > =< / span > < span class = "kc" > False< / span > < span class = "p" > ,< / span >
< span class = "n" > num_workers< / span > < span class = "o" > =< / span > < span class = "n" > workers< / span > < span class = "p" > ,< / span >
< span class = "n" > pin_memory< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > use_gpu< / span > < span class = "p" > ,< / span >
< span class = "n" > drop_last< / span > < span class = "o" > =< / span > < span class = "kc" > False< / span >
< span class = "p" > )< / span >
< span class = "c1" > # build gallery loader< / span >
< span class = "n" > galleryset< / span > < span class = "o" > =< / span > < span class = "n" > init_video_dataset< / span > < span class = "p" > (< / span >
< span class = "n" > name< / span > < span class = "p" > ,< / span >
< span class = "n" > transform< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > transform_te< / span > < span class = "p" > ,< / span >
< span class = "n" > mode< / span > < span class = "o" > =< / span > < span class = "s1" > ' gallery' < / span > < span class = "p" > ,< / span >
< span class = "n" > combineall< / span > < span class = "o" > =< / span > < span class = "n" > combineall< / span > < span class = "p" > ,< / span >
< span class = "n" > verbose< / span > < span class = "o" > =< / span > < span class = "kc" > False< / span > < span class = "p" > ,< / span >
< span class = "n" > root< / span > < span class = "o" > =< / span > < span class = "n" > root< / span > < span class = "p" > ,< / span >
< span class = "n" > split_id< / span > < span class = "o" > =< / span > < span class = "n" > split_id< / span > < span class = "p" > ,< / span >
< span class = "n" > seq_len< / span > < span class = "o" > =< / span > < span class = "n" > seq_len< / span > < span class = "p" > ,< / span >
< span class = "n" > sample_method< / span > < span class = "o" > =< / span > < span class = "n" > sample_method< / span >
< span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > testloader< / span > < span class = "p" > [< / span > < span class = "n" > name< / span > < span class = "p" > ][< / span > < span class = "s1" > ' gallery' < / span > < span class = "p" > ]< / span > < span class = "o" > =< / span > < span class = "n" > torch< / span > < span class = "o" > .< / span > < span class = "n" > utils< / span > < span class = "o" > .< / span > < span class = "n" > data< / span > < span class = "o" > .< / span > < span class = "n" > DataLoader< / span > < span class = "p" > (< / span >
< span class = "n" > galleryset< / span > < span class = "p" > ,< / span >
< span class = "n" > batch_size< / span > < span class = "o" > =< / span > < span class = "n" > batch_size< / span > < span class = "p" > ,< / span >
< span class = "n" > shuffle< / span > < span class = "o" > =< / span > < span class = "kc" > False< / span > < span class = "p" > ,< / span >
< span class = "n" > num_workers< / span > < span class = "o" > =< / span > < span class = "n" > workers< / span > < span class = "p" > ,< / span >
< span class = "n" > pin_memory< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > use_gpu< / span > < span class = "p" > ,< / span >
< span class = "n" > drop_last< / span > < span class = "o" > =< / span > < span class = "kc" > False< / span >
< span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > testdataset< / span > < span class = "p" > [< / span > < span class = "n" > name< / span > < span class = "p" > ][< / span > < span class = "s1" > ' query' < / span > < span class = "p" > ]< / span > < span class = "o" > =< / span > < span class = "n" > queryset< / span > < span class = "o" > .< / span > < span class = "n" > query< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > testdataset< / span > < span class = "p" > [< / span > < span class = "n" > name< / span > < span class = "p" > ][< / span > < span class = "s1" > ' gallery' < / span > < span class = "p" > ]< / span > < span class = "o" > =< / span > < span class = "n" > galleryset< / span > < span class = "o" > .< / span > < span class = "n" > gallery< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "s1" > ' < / span > < span class = "se" > \n< / span > < span class = "s1" > ' < / span > < span class = "p" > )< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "s1" > ' **************** Summary ****************' < / span > < span class = "p" > )< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "s1" > ' train : < / span > < span class = "si" > {}< / span > < span class = "s1" > ' < / span > < span class = "o" > .< / span > < span class = "n" > format< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > sources< / span > < span class = "p" > ))< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "s1" > ' # train datasets : < / span > < span class = "si" > {}< / span > < span class = "s1" > ' < / span > < span class = "o" > .< / span > < span class = "n" > format< / span > < span class = "p" > (< / span > < span class = "nb" > len< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > sources< / span > < span class = "p" > )))< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "s1" > ' # train ids : < / span > < span class = "si" > {}< / span > < span class = "s1" > ' < / span > < span class = "o" > .< / span > < span class = "n" > format< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > num_train_pids< / span > < span class = "p" > ))< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "s1" > ' # train tracklets : < / span > < span class = "si" > {}< / span > < span class = "s1" > ' < / span > < span class = "o" > .< / span > < span class = "n" > format< / span > < span class = "p" > (< / span > < span class = "nb" > len< / span > < span class = "p" > (< / span > < span class = "n" > trainset< / span > < span class = "p" > )))< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "s1" > ' # train cameras : < / span > < span class = "si" > {}< / span > < span class = "s1" > ' < / span > < span class = "o" > .< / span > < span class = "n" > format< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > num_train_cams< / span > < span class = "p" > ))< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "s1" > ' test : < / span > < span class = "si" > {}< / span > < span class = "s1" > ' < / span > < span class = "o" > .< / span > < span class = "n" > format< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > targets< / span > < span class = "p" > ))< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "s1" > ' *****************************************' < / span > < span class = "p" > )< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "s1" > ' < / span > < span class = "se" > \n< / span > < span class = "s1" > ' < / span > < span class = "p" > )< / span > < / div >
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© Copyright 2019, Kaiyang Zhou
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