Python datasetZSL Examples

Example #1

import utils
from utils.wheels import *
from utils.trainer import trainer_epoch
from utils.DataAug import data_aug_ZSL
# Make experiment result folder
TimeStamp, path_folderExp, path_folderExpBestModel = utils.backup.createBackUp(
)

# get all data for dataset
from prepareData import *

# Make dataset
dataset_trn = datasetZSL(
    path_folderTrainImage,
    path_txtImageLabel,
    index_split=index_SeenTrn,
    label_enc=label_enc,
    data_aug=data_aug_ZSL,
)
dataset_val = datasetZSL(path_folderTrainImage,
                         path_txtImageLabel,
                         index_split=index_SeenVal,
                         label_enc=label_enc)
dataset_tst = datasetZSL(path_folderTrainImage,
                         path_txtImageLabel,
                         index_split=index_UnseenTst,
                         label_enc=label_enc)
dataset_prd = datasetZSL(path_folderTestImage,
                         path_txtImage,
                         index_split=index_UnseenPrd,
                         label_enc=label_enc,

Example #2

File: predictLDFBaseline_TestAug.py Project: wufan0910/ZSLPR-TIANCHI

from utils.wheels import *
from utils.trainer import trainer_epoch
from utils.DataAug import data_aug_ZSL_TestAug
# Make experiment result folder
TimeStamp, path_folderExp, path_folderExpBestModel = utils.backup.createBackUp(
)

from prepareData import *

# Make dataset
# dataset_trn = datasetZSL(path_folderTrainImage, path_txtImageLabel, index_split=index_SeenTrn,    label_enc=label_enc, data_aug=data_aug_ZSL,)
# dataset_val = datasetZSL(path_folderTrainImage, path_txtImageLabel, index_split=index_SeenVal, label_enc=label_enc)
# dataset_tst = datasetZSL(path_folderTrainImage, path_txtImageLabel, index_split=index_UnseenTst, label_enc=label_enc)
dataset_prd = datasetZSL(path_folderTestImage,
                         path_txtImage,
                         index_split=index_UnseenPrd,
                         label_enc=label_enc,
                         DummyTarget=True)
dataset_prd_DataAug = datasetZSL_wtDataAug(datasetZSL(
    path_folderTestImage,
    path_txtImage,
    index_split=index_UnseenPrd,
    label_enc=label_enc,
    DummyTarget=True,
    data_aug=data_aug_ZSL_TestAug,
),
                                           num_DataAug=params_numDataAug)

# Make dataloader
# dataloader_trn = torch.utils.data.DataLoader(
#     dataset=dataset_trn, batch_size=params_batch_size, shuffle=True,

Example #3

from config import *

import utils
from utils.wheels import *
from utils.trainer import trainer_epoch
from utils.DataAug import data_aug_ZSL
# Make experiment result folder
TimeStamp, path_folderExp, path_folderExpBestModel = utils.backup.createBackUp(
)

from prepareData import *

# Make dataset
dataset_trn = datasetZSL(
    path_folderTrainImage,
    path_txtImageLabel,
    label_enc=label_enc,
    # data_aug=data_aug_ZSL,
)
lst_tsClassEmb = [
    Tensor(emb).cuda() for emb in [arr_ClassNameVec, arr_ClassAttr]
]
emb_size = [emb.shape[1] for emb in lst_tsClassEmb]

G = G_Feat(
    emb_size=emb_size,
    dimHid=params_dimHid_G,
    feat_size=params_dimVisFeat,
).cuda()

state_dict = torch.load(path_ptmdlWGAN_G,
                        map_location={

Example #4

from config import *

import utils
from utils.wheels import *
from utils.trainer import trainer_epoch_fWGAN
from utils.DataAug import data_aug_ZSL
# Make experiment result folder
TimeStamp, path_folderExp, path_folderExpBestModel = utils.backup.createBackUp(
)

from prepareData import *

# Make dataset
dataset_trn = datasetZSL(
    path_folderTrainImage,
    path_txtImageLabel,
    label_enc=label_enc,
    # data_aug=data_aug_ZSL,
)
# Make dataloader
dataloader_trn = torch.utils.data.DataLoader(
    dataset=dataset_trn,
    batch_size=params_batch_size_fWGAN,
    shuffle=True,
    # sampler=WeightedRandomSampler(np.ones(len(dataset_trn)), num_samples=len(dataset_trn)//100),
    num_workers=params_num_workers,
    pin_memory=True,
)

torch.cuda.set_device(params_cuda_device)
# Model & Loss
lst_tsClassEmb = [