yolov3_mobilenet_v3_large_ssld_270e_voc.yml

_BASE_: [
  '../datasets/coco_detection.yml',
  '../runtime.yml',
  '_base_/optimizer_270e.yml',
  '_base_/yolov3_mobilenet_v3_large.yml',
  '_base_/yolov3_reader.yml',
]

snapshot_epoch: 5
pretrain_weights:  https://paddledet.bj.bcebos.com/models/pretrained/MobileNetV3_large_x1_0_ssld_pretrained.pdparams
weights: output/yolov3_mobilenet_v3_large_ssld_270e_voc/model_final

TrainReader:
  inputs_def:
    num_max_boxes: 50
  sample_transforms:
    - Decode: {}
    - Mixup: {alpha: 1.5, beta: 1.5}
    - RandomDistort: {}
    - RandomExpand: {fill_value: [123.675, 116.28, 103.53]}
    - RandomCrop: {}
    - RandomFlip: {}
  batch_transforms:
    - BatchRandomResize:
        target_size: [320, 352, 384, 416, 448, 480, 512, 544, 576, 608]
        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]
        num_classes: 20
  batch_size: 8
  shuffle: true
  drop_last: true
  mixup_epoch: 250

EvalReader:
  batch_transforms:
  - PadBatch: {pad_gt: True}

LearningRate:
  base_lr: 0.001
  schedulers:
  - !PiecewiseDecay
    gamma: 0.1
    milestones:
    - 216
    - 243
  - !LinearWarmup
    start_factor: 0.
    steps: 1000