place-recognition-db
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Tool for creating optimally sized databases (containing the minimum number of frames covering the scene) for place recognition task from RGBD and LiDAR data
https://github.com/prime-slam/place-recognition-db/blob/43e4aa21801b55d9a016db79b108c4c68308c879/vprdb/vpr_systems/cos_place/cos_place.py#L49 ```RuntimeError: Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False. If you are running on a CPU-only machine, please use torch.load with map_location=torch.device('cpu') to map your...
https://github.com/prime-slam/place-recognition-db/blob/43e4aa21801b55d9a016db79b108c4c68308c879/vprdb/global_localization/global_localization.py#L77-L80 Currently, local features are computed all at once, which can cause problems if the dataset is large enough
https://github.com/prime-slam/place-recognition-db/blob/43e4aa21801b55d9a016db79b108c4c68308c879/vprdb/core/utils.py#L66 At the moment, the function checks the coverage of each frame with each