# This config is an assembled config for ByteTrack MOT, used as eval/infer mode for MOT.
_BASE_: [
  'detector/ppyoloe_crn_l_36e_640x640_mot17half.yml',
  '_base_/mot17.yml',
  '_base_/ppyoloe_mot_reader_640x640.yml'
]
weights: output/bytetrack_ppyoloe/model_final
log_iter: 20
snapshot_epoch: 2

metric: MOT # eval/infer mode, set 'COCO' can be training mode
num_classes: 1

architecture: ByteTrack
pretrain_weights: https://bj.bcebos.com/v1/paddledet/models/ppyoloe_crn_l_300e_coco.pdparams
ByteTrack:
  detector: YOLOv3 # PPYOLOe version
  reid: None
  tracker: JDETracker
det_weights: https://bj.bcebos.com/v1/paddledet/models/mot/ppyoloe_crn_l_36e_640x640_mot17half.pdparams
reid_weights: None

YOLOv3:
  backbone: CSPResNet
  neck: CustomCSPPAN
  yolo_head: PPYOLOEHead
  post_process: ~

# Tracking requires higher quality boxes, so NMS score_threshold will be higher
PPYOLOEHead:
  fpn_strides: [32, 16, 8]
  grid_cell_scale: 5.0
  grid_cell_offset: 0.5
  static_assigner_epoch: -1 # 100
  use_varifocal_loss: True
  loss_weight: {class: 1.0, iou: 2.5, dfl: 0.5}
  static_assigner:
    name: ATSSAssigner
    topk: 9
  assigner:
    name: TaskAlignedAssigner
    topk: 13
    alpha: 1.0
    beta: 6.0
  nms:
    name: MultiClassNMS
    nms_top_k: 1000
    keep_top_k: 100
    score_threshold: 0.1 # 0.01 in original detector
    nms_threshold: 0.4 # 0.6 in original detector

# BYTETracker
JDETracker:
  use_byte: True
  match_thres: 0.9
  conf_thres: 0.2
  low_conf_thres: 0.1
  min_box_area: 100
  vertical_ratio: 1.6 # for pedestrian