_BASE_: [
  'detector/yolov3_darknet53_270e_608x608_pedestrian.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/yolov3_darknet53_270e_608x608_pedestrian.pdparams
reid_weights: https://paddledet.bj.bcebos.com/models/mot/deepsort/deepsort_pplcnet.pdparams


# DeepSORT configuration
architecture: DeepSORT
pretrain_weights: None

DeepSORT:
  detector: YOLOv3 # General YOLOv3 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: General YOLOv3 version
# see 'configs/mot/deepsort/detector/yolov3_darknet53_270e_608x608_pedestrian.yml'
YOLOv3:
  backbone: DarkNet
  neck: YOLOv3FPN
  yolo_head: YOLOv3Head
  post_process: BBoxPostProcess

# Tracking requires higher quality boxes, so decode.conf_thresh will be higher
BBoxPostProcess:
  decode:
    name: YOLOBox
    conf_thresh: 0.1 # 0.005 in original detector
    downsample_ratio: 32
    clip_bbox: true
  nms:
    name: MultiClassNMS
    keep_top_k: 100
    score_threshold: 0.01
    nms_threshold: 0.45
    nms_top_k: 1000