_BASE_: [
  '_base_/optimizer_70e.yml',
  '_base_/centertrack_dla34.yml',
  '_base_/centertrack_reader.yml',
  '../../runtime.yml',
]
log_iter: 20
snapshot_epoch: 5
weights: output/centertrack_dla34_70e_mot17half/model_final
pretrain_weights: https://bj.bcebos.com/v1/paddledet/models/pretrained/crowdhuman_centertrack.pdparams


### for Detection eval.py/infer.py
# mot_metric: False
# metric: COCO

### for MOT eval_mot.py/infer_mot_mot.py
mot_metric: True
metric: MOT


worker_num: 4
TrainReader:
  batch_size: 16 # total 32 for 2 GPUs

EvalReader:
  batch_size: 1

EvalMOTReader:
  batch_size: 1


# COCO style dataset for training
num_classes: 1
TrainDataset:
  !COCODataSet
    dataset_dir: dataset/mot/MOT17
    anno_path: annotations/train_half.json
    image_dir: images/train
    data_fields: ['image', 'gt_bbox', 'gt_class', 'is_crowd', 'gt_track_id']
    # add 'gt_track_id', the boxes annotations of json file should have 'gt_track_id'

EvalDataset:
  !COCODataSet
    dataset_dir: dataset/mot/MOT17
    anno_path: annotations/val_half.json
    image_dir: images/train

TestDataset:
  !ImageFolder
    dataset_dir: dataset/mot/MOT17
    anno_path: annotations/val_half.json

# for MOT evaluation
# If you want to change the MOT evaluation dataset, please modify 'data_root'
EvalMOTDataset:
  !MOTImageFolder
    dataset_dir: dataset/mot/MOT17
    data_root: images/half
    keep_ori_im: True # set True if save visualization images or video, or used in SDE MOT

# for MOT video inference
TestMOTDataset:
  !MOTImageFolder
    dataset_dir: dataset/mot/MOT17
    keep_ori_im: True # set True if save visualization images or video