text: """
  This file contains definitions of useful data stuctures and the paths
  for the datasets and data files necessary to run the code.
  Things you need to change: *_ROOT that indicate the path to each dataset
  """
  from os.path import join
  
  H36M_ROOT = ''
  LSP_ROOT = ''
  LSP_ORIGINAL_ROOT = ''
  LSPET_ROOT = ''
  MPII_ROOT = ''
  COCO_ROOT = ''
  MPI_INF_3DHP_ROOT = ''
  PW3D_ROOT = ''
  UPI_S1H_ROOT = ''
  YOUTUBE_ROOT = ''
  
  # Output folder to save test/train npz files
  DATASET_NPZ_PATH = 'data/dataset_extras'
  
  # Output folder to store the openpose detections
  # This is requires only in case you want to regenerate 
  # the .npz files with the annotations.
  OPENPOSE_PATH = 'datasets/openpose'
  
  # Path to test/train npz files
  DATASET_FILES = [ {'h36m-p1': join(DATASET_NPZ_PATH, 'h36m_valid_protocol1.npz'),
                     'h36m-p2': join(DATASET_NPZ_PATH, 'h36m_valid_protocol2.npz'),
                     'lsp': join(DATASET_NPZ_PATH, 'lsp_dataset_test.npz'),
                     'mpi-inf-3dhp': join(DATASET_NPZ_PATH, 'mpi_inf_3dhp_valid.npz'),
                     '3dpw': join(DATASET_NPZ_PATH, '3dpw_test.npz'),
                    },
  
                    {'h36m': join(DATASET_NPZ_PATH, 'h36m_train.npz'),
                     'lsp-orig': join(DATASET_NPZ_PATH, 'lsp_dataset_original_train.npz'),
                     'mpii': join(DATASET_NPZ_PATH, 'mpii_train.npz'),
                     'coco': join(DATASET_NPZ_PATH, 'coco_2014_train.npz'),
                     'lspet': join(DATASET_NPZ_PATH, 'hr-lspet_train.npz'),
                     'mpi-inf-3dhp': join(DATASET_NPZ_PATH, 'mpi_inf_3dhp_train.npz'),
                     'youtube': join(DATASET_NPZ_PATH, 'youtube_train.npz'),
                    }
                  ]
  
  DATASET_FOLDERS = {'h36m': H36M_ROOT,
                     'h36m-p1': H36M_ROOT,
                     'h36m-p2': H36M_ROOT,
                     'lsp-orig': LSP_ORIGINAL_ROOT,
                     'lsp': LSP_ROOT,
                     'lspet': LSPET_ROOT,
                     'mpi-inf-3dhp': MPI_INF_3DHP_ROOT,
                     'mpii': MPII_ROOT,
                     'coco': COCO_ROOT,
                     '3dpw': PW3D_ROOT,
                     'upi-s1h': UPI_S1H_ROOT,
                     'youtube': YOUTUBE_ROOT,
                  }
  
  CUBE_PARTS_FILE = 'data/cube_parts.npy'
  JOINT_REGRESSOR_TRAIN_EXTRA = 'data/J_regressor_extra.npy'
  JOINT_REGRESSOR_H36M = 'data/J_regressor_h36m.npy'
  VERTEX_TEXTURE_FILE = 'data/vertex_texture.npy'
  STATIC_FITS_DIR = 'data/static_fits'
  SMPL_MEAN_PARAMS = 'data/smpl_mean_params.npz'
  SMPL_MODEL_DIR = 'data/smpl'
  