architecture: CLRNet

CLRNet:
  backbone: CLRResNet
  neck: CLRFPN
  clr_head: CLRHead

CLRResNet:
  resnet: 'resnet18'
  pretrained: True

CLRFPN:
  in_channels: [128,256,512]
  out_channel: 64
  extra_stage: 0

CLRHead:
  prior_feat_channels: 64
  fc_hidden_dim: 64
  num_priors: 192
  num_fc: 2
  refine_layers: 3
  sample_points: 36
  loss: CLRNetLoss
  conf_threshold: 0.4
  nms_thres: 0.8

CLRNetLoss:
  cls_loss_weight : 2.0
  xyt_loss_weight : 0.2
  iou_loss_weight : 2.0
  seg_loss_weight : 1.0
  refine_layers : 3
  ignore_label: 255
  bg_weight: 0.4

# for visualize lane detection results
sample_y:
  start: 589
  end: 230
  step: -20