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- Added the [MIT license](https://github.com/filipradenovic/cnnimageretrieval-pytorch/blob/master/LICENSE)
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- Added mutli-scale performance on `roxford5k` and `rparis6k` for new pre-trained networks with end-to-end whitening, trained on both `retrieval-SfM-120` and `Google Landmarks 2018` train datasets
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- Added a new example test script without post-processing, for networks that are trained in a fully end-to-end manner, with whitening as FC layer learned during training
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- Added few things in train example: GeMmp pooling, triplet loss, small trick to handle really large batches
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