PyTorch torchvision.transforms This function generates a random image transformation for data augmentation. It randomly selects one from several transformations such as horizontal flip, rotation, color jitter, random cropping, etc. Image processing 2024-12-16 12:10:18 3 views
PyTorch torchvision.transforms This function uses the resnet18 model from PyTorch to classify the input image. It first loads a pre-trained model, then defines a transform to normalize the input image. Next, the transform is applied to the input image, and the result is passed to the model for classification. Finally, softmax function is used to get the probabilities for each class, and the index of the class with the highest probability is returned. Image classification 2024-12-16 12:01:07 5 views
PyTorch torchvision.transforms This function generates a random image transformation using PyTorch libraries, which is suitable for data augmentation. Function 2024-12-16 11:59:08 4 views
PyTorch torchvision.transforms This function implements classification training for a pre-trained ResNet50 model using automatic augmentation techniques. The function takes a pre-trained model, a dataset, and the number of training epochs as parameters. Deep learning 2024-12-16 11:56:27 3 views
PyTorch torchvision This function randomly selects an image from a given dataset, applies specified transformations, predicts it using a pre-trained ResNet18 model, and displays the image. The type of code 2024-12-16 11:54:25 3 views
PyTorch torchvision This function randomly loads images from the CIFAR10 dataset, resizes them to a specified size, converts them to tensors, and normalizes them. Then, it returns batches of images using PyTorch's DataLoader. Function 2024-12-16 11:53:50 3 views
PyTorch torchvision.transforms This function uses the PyTorch torchvision library to generate a random image transform, including random flips, rotations, crops, color jittering, and normalization, returning a transform object. Image processing 2024-12-16 11:49:05 3 views
PyTorch torchvision.transforms This function generates a random set of image transformations for data augmentation, which can improve the generalization ability of the model in image classification tasks. Data enhancement function 2024-12-16 11:39:22 3 views
PyTorch torchvision.transforms This function randomly loads the MNIST dataset and transforms its images to a specified size. First, a data transformer is defined, which adjusts the image size, converts it to a tensor, and normalizes it. Then, the MNIST dataset is loaded, and a DataLoader is created that shuffles the data and provides it in batches. The type of code 2024-12-16 11:37:16 4 views
PyTorch torchvision.transforms This function generates a data loader for randomly loading images of a specified size and resolution from a dataset. The dataset path, batch size, and image size are specified by the function parameters. Custom function 2024-12-16 11:35:16 4 views
