AntoineH/smart_augmentation
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Mise a jour de toute les modifs... (Higher: Ajout deux TF, modification val loss, ajout prob dans sample image, ...)

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Harle, Antoine (Contracteur) 2020-01-10 13:21:34 -05:00
parent e75fb96716
commit c8ce6c8024
6 changed files with 299 additions and 64 deletions
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10
higher/datasets.py
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@ -35,6 +35,8 @@ import augmentation_transforms
import numpy as np
download_data=False
num_workers=0
pin_memory=False
class AugmentedDataset(VisionDataset):
def __init__(self, root, train=True, transform=None, target_transform=None, download=False, subset=None):
@ -281,14 +283,14 @@ train_subset_indices=range(int(len(data_train)/2))
val_subset_indices=range(int(len(data_train)/2),len(data_train))
#train_subset_indices=range(BATCH_SIZE*10)
#val_subset_indices=range(BATCH_SIZE*10, BATCH_SIZE*20)
dl_train = torch.utils.data.DataLoader(data_train, batch_size=BATCH_SIZE, shuffle=False, sampler=SubsetRandomSampler(train_subset_indices))
dl_train = torch.utils.data.DataLoader(data_train, batch_size=BATCH_SIZE, shuffle=False, sampler=SubsetRandomSampler(train_subset_indices), num_workers=num_workers, pin_memory=pin_memory)
### Augmented Dataset ###
#data_train_aug = AugmentedDataset("./data", train=True, download=download_data, transform=transform, subset=(0,int(len(data_train)/2)))
#data_train_aug.augement_data(aug_copy=10)
#print(data_train_aug)
#dl_train = torch.utils.data.DataLoader(data_train_aug, batch_size=BATCH_SIZE, shuffle=True)
#dl_train = torch.utils.data.DataLoader(data_train_aug, batch_size=BATCH_SIZE, shuffle=True, num_workers=num_workers, pin_memory=pin_memory)
dl_val = torch.utils.data.DataLoader(data_train, batch_size=BATCH_SIZE, shuffle=False, sampler=SubsetRandomSampler(val_subset_indices))
dl_test = torch.utils.data.DataLoader(data_test, batch_size=TEST_SIZE, shuffle=False)
dl_val = torch.utils.data.DataLoader(data_train, batch_size=BATCH_SIZE, shuffle=False, sampler=SubsetRandomSampler(val_subset_indices), num_workers=num_workers, pin_memory=pin_memory)
dl_test = torch.utils.data.DataLoader(data_test, batch_size=TEST_SIZE, shuffle=False, num_workers=num_workers, pin_memory=pin_memory)