architecture: YOLOv3
use_gpu: true
max_iters: 450000
log_iter: 100
save_dir: output
snapshot_iter: 10000
metric: COCO
pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet101_vd_ssld_pretrained.tar
weights: output/ppyolov2_r101vd_dcn/model_final
num_classes: 80
use_fine_grained_loss: true
use_ema: true
ema_decay: 0.9998

YOLOv3:
  backbone: ResNet
  yolo_head: YOLOv3PANHead
  use_fine_grained_loss: true

ResNet:
  norm_type: sync_bn
  freeze_at: 0
  freeze_norm: false
  norm_decay: 0.
  depth: 101
  feature_maps: [3, 4, 5]
  variant: d
  dcn_v2_stages: [5]

YOLOv3PANHead:
  anchor_masks: [[6, 7, 8], [3, 4, 5], [0, 1, 2]]
  anchors: [[10, 13], [16, 30], [33, 23],
            [30, 61], [62, 45], [59, 119],
            [116, 90], [156, 198], [373, 326]]
  norm_decay: 0.
  iou_aware: true
  iou_aware_factor: 0.5
  scale_x_y: 1.05
  spp: true
  yolo_loss: YOLOv3Loss
  nms: MatrixNMS
  drop_block: true

YOLOv3Loss:
  ignore_thresh: 0.7
  scale_x_y: 1.05
  label_smooth: false
  use_fine_grained_loss: true
  iou_loss: IouLoss
  iou_aware_loss: IouAwareLoss

IouLoss:
  loss_weight: 2.5
  max_height: 768
  max_width: 768

IouAwareLoss:
  loss_weight: 1.0
  max_height: 768
  max_width: 768

MatrixNMS:
  background_label: -1
  keep_top_k: 100
  normalized: false
  score_threshold: 0.01
  post_threshold: 0.01

LearningRate:
  base_lr: 0.005
  schedulers:
  - !PiecewiseDecay
    gamma: 0.1
    milestones:
    - 300000
  - !LinearWarmup
    start_factor: 0.
    steps: 4000

OptimizerBuilder:
  clip_grad_by_norm: 35.
  optimizer:
    momentum: 0.9
    type: Momentum
  regularizer:
    factor: 0.0005
    type: L2

_READER_: 'ppyolov2_reader.yml'