TIL.yml

MODEL:
  PRETRAIN_HW_RATIO: 2
  METRIC_LOSS_TYPE: 'triplet'
  IF_LABELSMOOTH: 'off'
  IF_WITH_CENTER: 'no'
  NAME: 'transformer'
  NO_MARGIN: True
  DEVICE_ID: ('0')
  TRANSFORMER_TYPE: 'swin_base_patch4_window7_224'
  STRIDE_SIZE: [16, 16]
  SIE_CAMERA: True
  ID_LOSS_WEIGHT: 1.0  # 1.0
  TRIPLET_LOSS_WEIGHT: 1.0  # 1.0

INPUT:
  SIZE_TRAIN: [224, 224]
  SIZE_TEST: [224, 224]
  HFLIP_PROB: 0.5 # random horizontal flip
  VFLIP_PROB: 0.5 # random vertical flip
  RE_PROB: 0.5 # random erasing
  PIXEL_MEAN: [0.5, 0.5, 0.5]
  PIXEL_STD: [0.5, 0.5, 0.5]

DATASETS:
  NAMES: ('TILCustomDataset')  # follow the market1501.py filename since TIL custom mods are all in that file
  ROOT_DIR: ('../RT-DETR/dataset/reid/')

DATALOADER:
  SAMPLER: 'softmax_triplet'
  NUM_INSTANCE: 1
  NUM_WORKERS: 2

SOLVER:
  OPTIMIZER_NAME: 'SGD'  # SGD
  MAX_EPOCHS: 500
  BASE_LR: 5e-3 # 0.0002
  WARMUP_EPOCHS: 3
  IMS_PER_BATCH: 128
  WARMUP_METHOD: 'cosine'
  LARGE_FC_LR: False
  CHECKPOINT_PERIOD: 1
  LOG_PERIOD: 20
  EVAL_PERIOD: 1
  WEIGHT_DECAY:  1e-4
  WEIGHT_DECAY_BIAS: 1e-4
  BIAS_LR_FACTOR: 2

TEST:
  EVAL: True
  IMS_PER_BATCH: 256
  RE_RANKING: False
  WEIGHT: 'log_SGD_200epoch_5e-4_test_hand_labeled/transformer_12_map0.931630612762169_acc0.9921742677688599.pth'
  # WEIGHT: ''
  NECK_FEAT: 'before'
  FEAT_NORM: 'yes'
  # THRESHOLD: 0.0013236288040655365 # without RR transformer_29 0.0013236288040655365
  THRESHOLD: 0.8669 # with RR, transformer_29 0.7868934651156535

OUTPUT_DIR: 'log_SGD_200epoch_5e-4_test_hand_labeled'