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botsort_ppyoloe.yml
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# This config is an assembled config for ByteTrack MOT, used as eval/infer mode for MOT.
_BASE_: [
'../bytetrack/detector/ppyoloe_crn_l_36e_640x640_mot17half.yml',
'../bytetrack/_base_/mot17.yml',
'../bytetrack/_base_/ppyoloe_mot_reader_640x640.yml'
]
weights: output/botsort_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: BOTSORTTracker
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
BOTSORTTracker:
track_high_thresh: 0.3
track_low_thresh: 0.2
new_track_thresh: 0.4
match_thresh: 0.7
track_buffer: 30
min_box_area: 0
camera_motion: False
cmc_method: 'sparseOptFlow' # only camera_motion is True,
# sparseOptFlow | files (Vidstab GMC) | orb | ecc
# MOTDataset for MOT evaluation and inference
EvalMOTDataset:
!MOTImageFolder
dataset_dir: dataset/mot
data_root: MOT17/images/half
keep_ori_im: True # set as True in DeepSORT and ByteTrack
TestMOTDataset:
!MOTImageFolder
dataset_dir: dataset/mot
keep_ori_im: True # set True if save visualization images or video