data_cfg:

  dataset_name: Gait3D

  dataset_root: your_path

  dataset_partition: datasets/Gait3D/Gait3D.json

  data_in_use: [true, true]

  num_workers: 1

  remove_no_gallery: false # Remove probe if no gallery for it

  test_dataset_name: Gait3D

evaluator_cfg:

  enable_float16: true

  restore_ckpt_strict: true

  restore_hint: 60000

  save_name: SMPLGait

  eval_func: evaluate_Gait3D

  sampler:

    batch_shuffle: false

    batch_size: 16

    sample_type: all_ordered # all indicates whole sequence used to test, while ordered means input sequence by its natural order; Other options:   fixed_unordered

    frames_all_limit: 720 # limit the number of sampled frames to prevent out of memory

  metric: euc # cos euc

  transform:

    - type: BaseSilCuttingTransform

      img_w: 64

    - type: NoOperation

loss_cfg:

  - loss_term_weight: 1.0

    margin: 0.2

    type: TripletLoss

    log_prefix: triplet

  - loss_term_weight: 0.1

    scale: 16

    type: CrossEntropyLoss

    log_prefix: softmax

    log_accuracy: true

model_cfg:

  model: SMPLGait

  backbone_cfg:

    in_channels: 1

    layers_cfg: # Layers configuration for automatically model construction

      - BC-64

      - BC-64

      - M

      - BC-128

      - BC-128

      - M

      - BC-256

      - BC-256

      # - M

      # - BC-512

      # - BC-512

    type: Plain

  SeparateFCs:

    in_channels: 256

    out_channels: 256

    parts_num: 31

  SeparateBNNecks:

    class_num: 3000

    in_channels: 256

    parts_num: 31

  bin_num:

    - 16

    - 8

    - 4

    - 2

    - 1

optimizer_cfg:

  lr: 0.1

  momentum: 0.9

  solver: SGD

  weight_decay: 0.0005

scheduler_cfg:

  gamma: 0.1

  milestones: # Learning Rate Reduction at each milestones

    - 20000

    - 40000

    - 50000

  scheduler: MultiStepLR

trainer_cfg:

  enable_float16: true # half_percesion float for memory reduction and speedup

  fix_BN: false

  log_iter: 100

  with_test: true

  restore_ckpt_strict: true

  restore_hint: 0

  save_iter: 10000

  save_name: SMPLGait

  sync_BN: true

  total_iter: 60000

  sampler:

    batch_shuffle: true

    batch_size:

      - 32 # TripletSampler, batch_size[0] indicates Number of Identity

      - 4 #                 batch_size[1] indicates Samples sequqnce for each Identity

    frames_num_fixed: 30 # fixed frames number for training

    frames_num_max: 50 # max frames number for unfixed training

    frames_num_min: 25 # min frames number for unfixed traing

    sample_type: fixed_unordered # fixed control input frames number, unordered for controlling order of input tensor; Other options: unfixed_ordered or all_ordered

    type: TripletSampler

  transform:

    - type: BaseSilCuttingTransform

      img_w: 64

    - type: NoOperation