Solution

Google Landmark Retrieval 2021 2nd Place Solution

The 2nd place solution of 2021 google landmark retrieval on kaggle.

Environment

We use cuda 11.1/python 3.7/torch 1.9.1/torchvision 0.8.1 for training and testing.

Download imagenet pretrained model ResNeXt101ibn and SEResNet101ibn from IBN-Net. ResNest101 and ResNeSt269 can be found in ResNest.

Prepare data

  1. Download GLDv2 full version from the official site.

  2. Run python tools/generate_gld_list.py. This will generate clean, c2x, trainfull and all data for different stage of training.

  3. Validation annotation comes from all 1129 images in GLDv2. We expand the competition index set to index_expand. Each query could find all its GTs in the expanded index set and the validation could be more accurate.

 

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