_BASE_: [
  'detector/jde_yolov3_darknet53_30e_1088x608_mix.yml',
  '../../datasets/mot.yml',
  '../../runtime.yml',
  '_base_/deepsort_reader_1088x608.yml',
]
metric: MOT
num_classes: 1

EvalMOTDataset:
  !MOTImageFolder
    dataset_dir: dataset/mot
    data_root: MOT16/images/train
    keep_ori_im: True # set as True in DeepSORT

det_weights: https://paddledet.bj.bcebos.com/models/mot/deepsort/jde_yolov3_darknet53_30e_1088x608_mix.pdparams
reid_weights: https://paddledet.bj.bcebos.com/models/mot/deepsort/deepsort_pcb_pyramid_r101.pdparams


# DeepSORT configuration
architecture: DeepSORT
pretrain_weights: None

DeepSORT:
  detector: YOLOv3 # JDE version YOLOv3
  reid: PCBPyramid
  tracker: DeepSORTTracker


# reid and tracker configuration
# see 'configs/mot/deepsort/reid/deepsort_pcb_pyramid_r101.yml'
PCBPyramid:
  num_conv_out_channels: 128
  num_classes: 751

DeepSORTTracker:
  input_size: [64, 192]
  min_box_area: 0
  vertical_ratio: -1
  budget: 100
  max_age: 70
  n_init: 3
  metric_type: cosine
  matching_threshold: 0.2
  max_iou_distance: 0.9
  motion: KalmanFilter


# detector configuration: JDE version YOLOv3
# see 'configs/mot/deepsort/detector/jde_yolov3_darknet53_30e_1088x608_mix.yml'
# The most obvious difference from general YOLOv3 is the JDEBBoxPostProcess and the bboxes coordinates output are not scaled to the original image.
YOLOv3:
  backbone: DarkNet
  neck: YOLOv3FPN
  yolo_head: YOLOv3Head
  post_process: JDEBBoxPostProcess

# Tracking requires higher quality boxes, so decode.conf_thresh will be higher
JDEBBoxPostProcess:
  decode:
    name: JDEBox
    conf_thresh: 0.3
    downsample_ratio: 32
  nms:
    name: MultiClassNMS
    keep_top_k: 500
    score_threshold: 0.01
    nms_threshold: 0.5
    nms_top_k: 2000
    normalized: true
  return_idx: false