The training data should be put in args.train_folder.
The evaluation data should be put in args.eval_folder.
If the data size is too large, the data can be divided into multiple files and put in the same folder.The calc_files function in train_model.py will walk your directory and generate a file list.
The data format of the input is an N * L * 2 GPS trajectories, where N is the number of the data samples, L is GPS the sequence length.
When everything is prepared run train.bash to train the model.
When the training process is over, run export.bash to generate human embeddings. The human's trajectories should be input in args.eval_folder.
When the human embedding generation process is over, run region_export.bash to generate region embeddings. The human's embedding should be input in args.embedding_path.