24 lines
750 B
Python
24 lines
750 B
Python
import torchvision
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from consts import CIFAR_DIR
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#optional transformations:
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# https://pytorch.org/vision/0.11/transforms.html
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#training data using torchvision cifar.
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cifar_data_train = torchvision.datasets.CIFAR10(root = CIFAR_DIR, train = True, transform = None, download = True)
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#example of cifar data sample. It is an image, class example.
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# here, the image is the image (PIL, or pillow) and the corresponding label, frog. I've chopped the dataset to only include cats
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# and dogs, so we can apply a different form of classification so it's easier to perform
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example_data = cifar_data_train[0]
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print(f'items in an instance of cifar10: {len(example_data)}')
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example_data[0].show()
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print(f'class corresponding to image: {example_data[1]}')
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