_BASE_: [
  'detector/ppyolov2_r50vd_dcn_365e_640x640_mot17half.yml',
  '../../datasets/mot.yml',
  '../../runtime.yml',
  '_base_/deepsort_reader_1088x608.yml',
]
metric: MOT
num_classes: 1

EvalMOTDataset:
  !MOTImageFolder
    dataset_dir: dataset/mot
    data_root: MOT17/images/half
    keep_ori_im: True # set as True in DeepSORT

det_weights: https://paddledet.bj.bcebos.com/models/mot/deepsort/ppyolov2_r50vd_dcn_365e_640x640_mot17half.pdparams
reid_weights: https://paddledet.bj.bcebos.com/models/mot/deepsort/deepsort_pplcnet.pdparams


# DeepSORT configuration
architecture: DeepSORT
pretrain_weights: None

DeepSORT:
  detector: YOLOv3 # PPYOLOv2 version
  reid: PPLCNetEmbedding
  tracker: DeepSORTTracker


# reid and tracker configuration
# see 'configs/mot/deepsort/reid/deepsort_pplcnet.yml'
PPLCNetEmbedding:
  input_ch: 1280
  output_ch: 512

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: PPYOLOv2 version
# see 'configs/mot/deepsort/detector/ppyolov2_r50vd_dcn_365e_640x640_mot17half.yml'
YOLOv3:
  backbone: ResNet
  neck: PPYOLOPAN
  yolo_head: YOLOv3Head
  post_process: BBoxPostProcess

ResNet:
  depth: 50
  variant: d
  return_idx: [1, 2, 3]
  dcn_v2_stages: [3]
  freeze_at: -1
  freeze_norm: false
  norm_decay: 0.

# Tracking requires higher quality boxes, so decode.conf_thresh will be higher
BBoxPostProcess:
  decode:
    name: YOLOBox
    conf_thresh: 0.25 # 0.01 in original detector
    downsample_ratio: 32
    clip_bbox: true
    scale_x_y: 1.05
  nms:
    name: MatrixNMS
    keep_top_k: 100
    score_threshold: 0.25 # 0.01 in original detector
    post_threshold: 0.25 # 0.01 in original detector
    nms_top_k: -1
    background_label: -1