architecture: FasterRCNN
use_gpu: false
use_xpu: true
max_iters: 2000
log_iter: 1
save_dir: output
snapshot_iter: 500
metric: VOC
pretrain_weights: https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_2x.tar
weights: output/faster_rcnn_r50_vd_fpn_roadsign_kunlun/model_final
num_classes: 5
finetune_exclude_pretrained_params: ['cls_score, bbox_pred']

FasterRCNN:
  backbone: ResNet
  fpn: FPN
  rpn_head: FPNRPNHead
  roi_extractor: FPNRoIAlign
  bbox_head: BBoxHead
  bbox_assigner: BBoxAssigner

ResNet:
  norm_type: affine_channel
  depth: 50
  feature_maps: [2, 3, 4, 5]
  freeze_at: 2
  variant: d

ResNetC5:
  depth: 50
  norm_type: affine_channel
  variant: d

FPN:
  max_level: 6
  min_level: 2
  num_chan: 256
  spatial_scale: [0.03125, 0.0625, 0.125, 0.25]

FPNRPNHead:
  anchor_generator:
    anchor_sizes: [32, 64, 128, 256, 512]
    aspect_ratios: [0.5, 1.0, 2.0]
    stride: [16.0, 16.0]
    variance: [1.0, 1.0, 1.0, 1.0]

  anchor_start_size: 32
  min_level: 2
  max_level: 6
  num_chan: 256

  rpn_target_assign:
    rpn_batch_size_per_im: 256
    rpn_fg_fraction: 0.5
    rpn_negative_overlap: 0.3
    rpn_positive_overlap: 0.7
    rpn_straddle_thresh: 0.0
    use_random: true

  train_proposal:
    min_size: 0.0
    nms_thresh: 0.7
    pre_nms_top_n: 2000
    post_nms_top_n: 2000

  test_proposal:
    min_size: 0.0
    nms_thresh: 0.7
    pre_nms_top_n: 1000
    post_nms_top_n: 1000

FPNRoIAlign:
  canconical_level: 4
  canonical_size: 224
  max_level: 5
  min_level: 2
  sampling_ratio: 2
  box_resolution: 7
  mask_resolution: 14

BBoxAssigner:
  batch_size_per_im: 512
  bbox_reg_weights: [0.1, 0.1, 0.2, 0.2]
  bg_thresh_hi: 0.5
  bg_thresh_lo: 0.0
  fg_fraction: 0.25
  fg_thresh: 0.5

BBoxHead:
  head: TwoFCHead
  nms:
    keep_top_k: 100
    nms_threshold: 0.5
    score_threshold: 0.05

TwoFCHead:
  mlp_dim: 1024

LearningRate:
  base_lr: 0.0001
  schedulers:
  - !PiecewiseDecay
    gamma: 0.1
    milestones:
    - 1300
    - 1800
  - !LinearWarmup
    start_factor: 0.3333333333333333
    steps: 100

OptimizerBuilder:
  optimizer:
    momentum: 0.9
    type: Momentum
  regularizer:
    factor: 0.0001
    type: L2


TrainReader:
  inputs_def:
    fields: ['image', 'im_info', 'im_id', 'gt_bbox', 'gt_class', 'is_crowd']
  dataset:
    !VOCDataSet
    dataset_dir: dataset/roadsign_voc
    anno_path: train.txt
    with_background: true

  batch_size: 1
  bufsize: 2
  shuffle: true
  drop_empty: true
  drop_last: true
  mixup_epoch: -1
  use_process: false
  worker_num: 2

  sample_transforms:
  - !DecodeImage
    to_rgb: true
  - !RandomFlipImage
    is_normalized: true
    prob: 0.5
  - !NormalizeImage
    mean: [0.485, 0.456, 0.406]
    std: [0.229, 0.224, 0.225]
    is_scale: true
    is_channel_first: false
  - !ResizeImage
    target_size: 800
    max_size: 1333
    interp: 1
    use_cv2: true
  - !Permute
    channel_first: true
    to_bgr: false

  batch_transforms:
  - !PadBatch
    pad_to_stride: 32
    use_padded_im_info: false


EvalReader:
  batch_size: 1
  bufsize: 1
  shuffle: false
  drop_empty: false
  drop_last: false
  use_process: false
  worker_num: 1

  inputs_def:
    fields: ['image', 'im_info', 'im_id', 'im_shape', 'gt_bbox', 'gt_class', 'is_difficult']

  dataset:
    !VOCDataSet
    dataset_dir: dataset/roadsign_voc
    anno_path: valid.txt
    with_background: true

  sample_transforms:
  - !DecodeImage
    to_rgb: true
  - !NormalizeImage
    mean: [0.485, 0.456, 0.406]
    std: [0.229, 0.224, 0.225]
    is_scale: true
    is_channel_first: false
  - !ResizeImage
    target_size: 800
    max_size: 1333
    interp: 1
    use_cv2: true
  - !Permute
    to_bgr: false
    channel_first: true

  batch_transforms:
  - !PadBatch
    pad_to_stride: 32
    use_padded_im_info: true


TestReader:
  batch_size: 1
  drop_empty: false
  drop_last: false

  inputs_def:
    fields: ['image', 'im_info', 'im_id', 'im_shape']

  dataset:
    !ImageFolder
    anno_path: dataset/roadsign_voc/label_list.txt
    with_background: true

  sample_transforms:
  - !DecodeImage
    to_rgb: true
    with_mixup: false
  - !NormalizeImage
    mean: [0.485, 0.456, 0.406]
    std: [0.229, 0.224, 0.225]
    is_scale: true
    is_channel_first: false
  - !ResizeImage
    target_size: 800
    max_size: 1333
    interp: 1
    use_cv2: true
  - !Permute
    to_bgr: false
    channel_first: true

  batch_transforms:
  - !PadBatch
    pad_to_stride: 32
    use_padded_im_info: true