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torchvision

Computer vision library with datasets, transforms, and pre-trained models

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Datasets, transforms, and models for computer vision

Commands

torchvision

Examples

Load a pre-trained ResNet50 model for image classification$ python3 -c "import torchvision.models as models; model = models.resnet50(pretrained=True); print(model)"

Download and use the CIFAR-10 dataset with standard transforms

$ python3 -c "from torchvision import datasets, transforms; transform = transforms.ToTensor(); cifar10 = datasets.CIFAR10(root='./data', download=True, transform=transform)"

Apply image transformations like resize and normalization

$ python3 -c "from torchvision import transforms; transform = transforms.Compose([transforms.Resize(224), transforms.ToTensor(), transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])]); print(transform)"