TrainReader:
  inputs_def:
    fields: ['image', 'im_info', 'im_id', 'gt_bbox', 'gt_class', 'is_crowd', 'gt_mask']
  dataset:
    !COCODataSet
    image_dir: train
    anno_path: annotations/instances_split_train.json
    dataset_dir: dataset/cocome
  sample_transforms:
  - !DecodeImage
    to_rgb: true
  - !RandomFlipImage
    prob: 0.5
    is_mask_flip: true
  - !NormalizeImage
    is_channel_first: false
    is_scale: true
    mean: [0.485,0.456,0.406]
    std: [0.229, 0.224,0.225]
  - !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: -1.
    use_padded_im_info: false
  batch_size: 1
  shuffle: true
  worker_num: 2
  drop_last: false
  use_process: false

EvalReader:
  inputs_def:
    fields: ['image', 'im_info', 'im_id', 'im_shape']
    # for voc
    #fields: ['image', 'im_info', 'im_id', 'gt_bbox', 'gt_class', 'is_difficult']
  dataset:
    !COCODataSet
    image_dir: train
    anno_path: annotations/instances_split_val.json
    dataset_dir: dataset/cocome
  sample_transforms:
  - !DecodeImage
    to_rgb: true
  - !NormalizeImage
    is_channel_first: false
    is_scale: true
    mean: [0.485,0.456,0.406]
    std: [0.229, 0.224,0.225]
  - !ResizeImage
    interp: 1
    max_size: 1333
    target_size: 800
    use_cv2: true
  - !Permute
    channel_first: true
    to_bgr: false
  batch_size: 1
  shuffle: false
  drop_last: false
  drop_empty: false
  worker_num: 2

TestReader:
  inputs_def:
    fields: ['image', 'im_info', 'im_id', 'im_shape']
  dataset:
    !ImageFolder
    anno_path: dataset/cocome/annotations/instances_split_val.json
  sample_transforms:
  - !DecodeImage
    to_rgb: true
    with_mixup: false
  - !NormalizeImage
    is_channel_first: false
    is_scale: true
    mean: [0.485,0.456,0.406]
    std: [0.229, 0.224,0.225]
  - !ResizeImage
    interp: 1
    max_size: 1333
    target_size: 800
    use_cv2: true
  - !Permute
    channel_first: true
    to_bgr: false
  batch_size: 1
  shuffle: false
  drop_last: false