_BASE_: [
  '../datasets/coco_detection.yml',
  '../runtime.yml',
  '_base_/yolov3_darknet53.yml',
  '_base_/yolov3_reader.yml',
]

snapshot_epoch: 5
weights: output/yolov3_darknet53_270e_coco/model_final

norm_type: bn

YOLOv3Loss:
  ignore_thresh: 0.5
  downsample: [32, 16, 8]
  label_smooth: false

worker_num: 8
TrainReader:
  inputs_def:
    num_max_boxes: 50
  sample_transforms:
    - Decode: {}
    - RandomDistort: {}
    - RandomExpand: {fill_value: [123.675, 116.28, 103.53], ratio: 2.0}
    - RandomCrop: {}
    - RandomFlip: {}
  batch_transforms:
    - BatchRandomResize: {target_size: [416], random_size: True, random_interp: True, keep_ratio: False}
    - NormalizeBox: {}
    - PadBox: {num_max_boxes: 50}
    - BboxXYXY2XYWH: {}
    - NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: True}
    - Permute: {}
    - Gt2YoloTarget: {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]], downsample_ratios: [32, 16, 8], iou_thresh: 0.5}
  batch_size: 32
  shuffle: true
  drop_last: true
  mixup_epoch: -1
  use_shared_memory: true

epoch: 320

LearningRate:
  base_lr: 0.001
  schedulers:
  - !CosineDecay
    max_epochs: 320
  - !LinearWarmup
    start_factor: 0.
    epochs: 4

OptimizerBuilder:
  optimizer:
    momentum: 0.9
    type: Momentum
  regularizer:
    factor: 0.016
    type: L2