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lxztju/pytorch_classification

A complete PyTorch image classification toolkit supporting CNN architectures (ResNet, DenseNet, EfficientNet, Swin Transformer), knowledge distillation, model ensemble, and deployment via Flask API or C++ libtorch.

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The repository provides end-to-end image classification capabilities using PyTorch and torchvision models. It includes training with warmup cosine learning rate scheduling, label smoothing, and multi-model ensemble prediction. The project supports CNN feature extraction followed by classification using SVM, Random Forest, MLP, or KNN classifiers. For deployment, it offers Flask + Redis cloud API, C++ libtorch inference, and TensorRT C++ inference options.

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