fairmot_enhance_hardnet85_30e_1088x608.yml

_BASE_: [
  '../../datasets/mot.yml',
  '../../runtime.yml',
  '_base_/optimizer_30e.yml',
  '_base_/fairmot_hardnet85.yml',
  '_base_/fairmot_reader_1088x608.yml',
]
norm_type: sync_bn
use_ema: true
ema_decay: 0.9998

# add crowdhuman
TrainDataset:
  !MOTDataSet
    dataset_dir: dataset/mot
    image_lists: ['mot17.train', 'caltech.all', 'cuhksysu.train', 'prw.train', 'citypersons.train', 'eth.train', 'crowdhuman.train', 'crowdhuman.val']
    data_fields: ['image', 'gt_bbox', 'gt_class', 'gt_ide']

worker_num: 4
TrainReader:
  inputs_def:
    image_shape: [3, 608, 1088]
  sample_transforms:
    - Decode: {}
    - RGBReverse: {}
    - AugmentHSV: {}
    - LetterBoxResize: {target_size: [608, 1088]}
    - MOTRandomAffine: {reject_outside: False}
    - RandomFlip: {}
    - BboxXYXY2XYWH: {}
    - NormalizeBox: {}
    - NormalizeImage: {mean: [0, 0, 0], std: [1, 1, 1]}
    - RGBReverse: {}
    - Permute: {}
  batch_transforms:
    - Gt2FairMOTTarget: {}
  batch_size: 10
  shuffle: True
  drop_last: True
  use_shared_memory: True

epoch: 30
LearningRate:
  base_lr: 0.0001
  schedulers:
  - !PiecewiseDecay
    gamma: 0.1
    milestones: [20,]
    use_warmup: False

OptimizerBuilder:
  optimizer:
    type: Adam
  regularizer: NULL

weights: output/fairmot_enhance_hardnet85_30e_1088x608/model_final