yolov3_darknet.yml

architecture: YOLOv3
use_gpu: true
max_iters: 11000
log_smooth_window: 20
save_dir: output
snapshot_iter: 1000
metric: COCO
pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/DarkNet53_pretrained.tar
weights: output/yolov3_darknet/model_final
num_classes: 6
use_fine_grained_loss: false

YOLOv3:
  backbone: DarkNet
  yolo_head: YOLOv3Head

DarkNet:
  norm_type: sync_bn
  norm_decay: 0.
  depth: 53

YOLOv3Head:
  anchor_masks: [[6, 7, 8], [3, 4, 5], [0, 1, 2]]
  anchors: [[12, 22], [19, 20], [30, 20],
            [22, 28], [16, 41], [45, 22],
            [26, 43], [36, 34], [53, 53]]
  norm_decay: 0.
  yolo_loss: YOLOv3Loss
  nms:
    background_label: -1
    keep_top_k: 100
    nms_threshold: 0.45
    nms_top_k: 1000
    normalized: false
    score_threshold: 0.01

YOLOv3Loss:
  ignore_thresh: 0.7
  label_smooth: true

LearningRate:
  base_lr: 0.00025
  schedulers:
  - !PiecewiseDecay
    gamma: 0.1
    milestones:
    - 7122
    - 9800
  - !LinearWarmup
    start_factor: 0.
    steps: 500

OptimizerBuilder:
  optimizer:
    momentum: 0.9
    type: Momentum
  regularizer:
    factor: 0.0005
    type: L2

TrainReader:
  inputs_def:
    fields: ['image', 'gt_bbox', 'gt_class', 'gt_score']
    num_max_boxes: 50
  dataset:
    !COCODataSet
      image_dir: images
      anno_path: Annotations/train.json
      dataset_dir: /home/aistudio/work/PCB_DATASET/
      with_background: false
  sample_transforms:
    - !DecodeImage
      to_rgb: True
    - !NormalizeBox {}
    - !PadBox
      num_max_boxes: 50
    - !BboxXYXY2XYWH {}
  batch_transforms:
  - !RandomShape
    sizes: [640, 704, 768, 832, 896, 960]
    random_inter: True
  - !NormalizeImage
    mean: [0.485, 0.456, 0.406]
    std: [0.229, 0.224, 0.225]
    is_scale: True
    is_channel_first: false
  - !Permute
    to_bgr: false
    channel_first: True
  # Gt2YoloTarget is only used when use_fine_grained_loss set as true,
  # this operator will be deleted automatically if use_fine_grained_loss
  # is set as false
  - !Gt2YoloTarget
    anchor_masks: [[6, 7, 8], [3, 4, 5], [0, 1, 2]]
    anchors: [[12, 22], [19, 20], [30, 20],
            [22, 28], [16, 41], [45, 22],
            [26, 43], [36, 34], [53, 53]]
    downsample_ratios: [32, 16, 8]
  batch_size: 4
  shuffle: true
  drop_last: true
  worker_num: 8
  bufsize: 4
  use_process: true

EvalReader:
  inputs_def:
    fields: ['image', 'im_size', 'im_id']
    num_max_boxes: 50
  dataset:
    !COCODataSet
      image_dir: images
      anno_path: Annotations/val.json
      dataset_dir: /home/aistudio/work/PCB_DATASET/
      with_background: false
  sample_transforms:
    - !DecodeImage
      to_rgb: True
    - !ResizeImage
      target_size: 896
      interp: 2
    - !NormalizeImage
      mean: [0.485, 0.456, 0.406]
      std: [0.229, 0.224, 0.225]
      is_scale: True
      is_channel_first: false
    - !PadBox
      num_max_boxes: 50
    - !Permute
      to_bgr: false
      channel_first: True
  batch_size: 2
  drop_empty: false
  worker_num: 8
  bufsize: 4

TestReader:
  inputs_def:
    image_shape: [3, 896, 896]
    fields: ['image', 'im_size', 'im_id']
  dataset:
    !ImageFolder
      anno_path: /home/aistudio/work/PCB_DATASET/Annotations/val.json
      with_background: false
  sample_transforms:
    - !DecodeImage
      to_rgb: True
    - !ResizeImage
      target_size: 896
      interp: 2
    - !NormalizeImage
      mean: [0.485, 0.456, 0.406]
      std: [0.229, 0.224, 0.225]
      is_scale: True
      is_channel_first: false
    - !Permute
      to_bgr: false
      channel_first: True
  batch_size: 1