hysts/pytorch_image_classification
PyTorch implementations of deep learning models for image classification on CIFAR, MNIST, and ImageNet datasets.
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This repository provides PyTorch implementations of numerous deep learning architectures for image classification tasks. It includes models such as ResNet, DenseNet, PyramidNet, SENet, and various augmentation techniques like CutMix, Mixup, and Random Erasing. The code supports training on standard benchmark datasets including CIFAR-10, CIFAR-100, MNIST, FashionMNIST, and ImageNet with configurable settings via YAML files.
Frequently asked
- What is hysts/pytorch_image_classification?
- PyTorch implementations of deep learning models for image classification on CIFAR, MNIST, and ImageNet datasets.
- Is pytorch_image_classification open source?
- Yes — hysts/pytorch_image_classification is open source, released under the MIT license.
- What language is pytorch_image_classification written in?
- hysts/pytorch_image_classification is primarily written in Python.
- How popular is pytorch_image_classification?
- hysts/pytorch_image_classification has 1.4k stars on GitHub.
- Where can I find pytorch_image_classification?
- hysts/pytorch_image_classification is on GitHub at https://github.com/hysts/pytorch_image_classification.