_BASE_: [ 'detector/yolov3_darknet53_40e_608x608_mot17half.yml', '_base_/mot17.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_40e_608x608_mot17half.pdparams reid_weights: https://paddledet.bj.bcebos.com/models/mot/deepsort/deepsort_pplcnet.pdparams # reader EvalMOTReader: sample_transforms: - Decode: {} - Resize: {target_size: [608, 608], keep_ratio: False, interp: 2} - NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: True} - Permute: {} batch_size: 1 TestMOTReader: inputs_def: image_shape: [3, 608, 608] sample_transforms: - Decode: {} - Resize: {target_size: [608, 608], keep_ratio: False, interp: 2} - NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: True} - Permute: {} batch_size: 1 # 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_40e_608x608_mot17half.yml' YOLOv3: backbone: DarkNet neck: YOLOv3FPN yolo_head: YOLOv3Head post_process: BBoxPostProcess # Tracking requires higher quality boxes, so NMS score_threshold will be higher BBoxPostProcess: decode: name: YOLOBox conf_thresh: 0.005 downsample_ratio: 32 clip_bbox: true nms: name: MultiClassNMS keep_top_k: 100 score_threshold: 0.3 # 0.01 in original detector nms_threshold: 0.45 nms_top_k: 1000