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Models:
Joel Williams
JoelW/
OpenGait
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[66de0a]: / configs / gaitssb / finetune_gait3d.yaml

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data_cfg:

  dataset_name: Gait3D

  dataset_root: your_path

  dataset_partition: ./datasets/Gait3D/Gait3D.json

  num_workers: 1

  remove_no_gallery: false # Remove probe if no gallery for it



evaluator_cfg:

  enable_float16: true

  restore_ckpt_strict: true

  restore_hint: 12000

  save_name: GaitSSB_Finetune

  eval_func: evaluate_Gait3D

  sampler:

    batch_shuffle: false

    batch_size: 4

    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

  transform:

    - type: BaseSilTransform



loss_cfg:

  - loss_term_weight: 1.0

    margin: 0.3

    type: TripletLoss

    log_prefix: triplet



model_cfg:

  model: GaitSSB_Finetune

  backbone_cfg:

    type: ResNet9

    block: BasicBlock

    channels: # Layers configuration for automatically model construction

      - 64

      - 128

      - 256

      - 512

    layers:

      - 1

      - 1

      - 1

      - 1

    strides:

      - 1

      - 2

      - 2

      - 1

    maxpool: false

  parts_num: 31

  backbone_lr: 

    - 0. 

    - 0.001

    - 0.001

    - 0.001

  projector_lr: 0.01



optimizer_cfg:

  lr: 0.1

  momentum: 0.9

  solver: SGD

  weight_decay: 0.



scheduler_cfg:

  gamma: 0.1

  milestones: # Learning Rate Reduction at each milestones

    - 6000

    - 8000

    - 10000

  scheduler: MultiStepLR



trainer_cfg:

  find_unused_parameters: true

  enable_float16: true # half_percesion float for memory reduction and speedup

  fix_BN: true

  with_test: false

  log_iter: 100

  optimizer_reset: true

  restore_ckpt_strict: false

  restore_hint: ./output/GaitLU-1M/GaitSSB_Pretrain/GaitSSB_Pretrain/checkpoints/GaitSSB_Pretrain-150000.pt

  save_iter: 2000

  save_name: GaitSSB_Finetune

  sync_BN: true

  total_iter: 12000

  sampler:

    batch_shuffle: true

    batch_size:

      - 64  # 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

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

    frames_skip_num: 4

    type: TripletSampler

  transform:

    - type: BaseSilTransform