TensorDatasetで生画像をTensor化して読み込む[PyTorch]
from glob import glob
from PIL import Image
import numpy as np
import torch
import torch.utils.data as data_utils
from torchvision.transforms import ToTensor
path = "./imgs/*"
files = glob(path)
labels = np.array([1,0,1,1,0])
labels = torch.Tensor(labels)
images = []
for file in files:
image = Image.open(file)
image = ToTensor()(image)
images.append(image)
features = torch.stack(images)
train = data_utils.TensorDataset(features, labels)
from glob import glob
from PIL import Image
import numpy as np
import torch
import torch.utils.data as data_utils
from torchvision.transforms import ToTensor
path = "./imgs/*"
files = glob(path)
labels = np.array([1,0,1,1,0])
labels = torch.Tensor(labels)
images = []
for file in files:
image = Image.open(file)
image = ToTensor()(image)
images.append(image)
features = torch.stack(images)
train = data_utils.TensorDataset(features, labels)
from glob import glob from PIL import Image import numpy as np import torch import torch.utils.data as data_utils from torchvision.transforms import ToTensor path = "./imgs/*" files = glob(path) labels = np.array([1,0,1,1,0]) labels = torch.Tensor(labels) images = [] for file in files: image = Image.open(file) image = ToTensor()(image) images.append(image) features = torch.stack(images) train = data_utils.TensorDataset(features, labels)
Tensorflowの知識を深めたいときには、以下の書籍を読むことをお勧めします。
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