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bytetrack_ppyoloe.yml
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bytetrack_ppyoloe.yml
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# 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