I have used this transformation. However, when I print the number of samples for training, it is showing the same number of images I have. I want to know the number of images after the augmentation? Can any one please tell me how to find the number of images after augmentation? Thanks in advance.
train_transforms = transforms.Compose([transforms.RandomResizedCrop(size=224, interpolation=2),
                                      transforms.Resize((224,224)),
                                      transforms.RandomHorizontalFlip(),
                                      transforms.RandomRotation(15),
                                      transforms.ToTensor(),
                                      transforms.Normalize([0.485, 0.456, 0.406],
                                                           [0.229, 0.224, 0.225])
                                      ])

test_transforms = transforms.Compose([
                    transforms.Resize((224,224)),
                    transforms.ToTensor(),
                    transforms.Normalize([0.485, 0.456, 0.406], 
                                         [0.229, 0.224, 0.225])
                    ])
merge_data = datasets.ImageFolder(data_dir + "/train", transform=train_transforms)

train_data, valid_data = train_test_split(merge_data, test_size = 0.2, random_state= 123)
test_data= datasets.ImageFolder(test_dir,transform=test_transforms)
num_workers = 0
print("Number of Samples in Train: ",len(train_data))
print("Number of Samples in Valid: ",len(valid_data))
print("Number of Samples in Test ",len(test_data))
train_loader = torch.utils.data.DataLoader(train_data, batch_size,
     num_workers=num_workers)
valid_loader = torch.utils.data.DataLoader(valid_data, batch_size, 
     num_workers=num_workers)