This repository provides a complete pipeline for CNN-based image retrieval, including fine-tuning pre-trained convolutional neural networks with metric learning losses, learning supervised whitening as post-processing for global descriptors, and evaluating on standard benchmarks. The approach handles hard example mining during training and supports various architectures, pooling methods, and whitening strategies. The code builds on the PyTorch framework for tensor operations and automatic differentiation.