ppyolo_r18vd.yml

architecture: YOLOv3
pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet18_vd_pretrained.tar
load_static_weights: true
norm_type: sync_bn
use_ema: true
ema_decay: 0.9998

YOLOv3:
  backbone: ResNet
  neck: PPYOLOFPN
  yolo_head: YOLOv3Head
  post_process: BBoxPostProcess

ResNet:
  depth: 18
  variant: d
  return_idx: [2, 3]
  freeze_at: -1
  freeze_norm: false
  norm_decay: 0.

PPYOLOFPN:
  feat_channels: [512, 512]
  drop_block: true
  block_size: 3
  keep_prob: 0.9
  conv_block_num: 0

YOLOv3Head:
  anchor_masks: [[3, 4, 5], [0, 1, 2]]
  anchors: [[10, 14], [23, 27], [37, 58],
            [81, 82], [135, 169], [344, 319]]
  loss: YOLOv3Loss

YOLOv3Loss:
  ignore_thresh: 0.7
  downsample: [32, 16]
  label_smooth: false
  scale_x_y: 1.05
  iou_loss: IouLoss

IouLoss:
  loss_weight: 2.5
  loss_square: true

BBoxPostProcess:
  decode:
    name: YOLOBox
    conf_thresh: 0.01
    downsample_ratio: 32
    clip_bbox: true
    scale_x_y: 1.05
  nms:
    name: MatrixNMS
    keep_top_k: 100
    score_threshold: 0.01
    post_threshold: 0.01
    nms_top_k: -1
    normalized: false
    background_label: -1