text: _base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'
  
  # 1. dataset settings
  dataset_type = 'CocoDataset'
  classes = ('ulcer','erosive')
  num_classes=2
  data_root = '/data1/qilei_chen/DATA/erosive_ulcer/'
  data = dict(
      samples_per_gpu=2,
      workers_per_gpu=2,
      train=dict(
          type=dataset_type,
          # explicitly add your class names to the field `classes`
          classes=classes,
          ann_file= data_root+'annotations/train.json',
          img_prefix=data_root+'images/'),
      val=dict(
          type=dataset_type,
          # explicitly add your class names to the field `classes`
          classes=classes,
          ann_file= data_root+'annotations/test.json',
          img_prefix=data_root+'images/'),
      test=dict(
          type=dataset_type,
          # explicitly add your class names to the field `classes`
          classes=classes,
          ann_file= data_root+'annotations/test.json',
          img_prefix=data_root+'images/'),)
  
  # 2. model settings
  
  # explicitly over-write all the `num_classes` field from default 80 to 1.
  model = dict(
      roi_head=dict(
          bbox_head=
              dict(type='Shared2FCBBoxHead',
                  num_classes=num_classes)),
      test_cfg=dict(
          rpn=dict(
              nms_pre=1000,
              max_per_img=1000,
              nms=dict(type='nms', iou_threshold=0.5),
              min_bbox_size=0),
          rcnn=dict(
              score_thr=0.05,
              nms=dict(type='nms', iou_threshold=0.1),
              max_per_img=100)))# explicitly over-write all the `num_classes` field from default 80 to 1.
  
  runner = dict(type='EpochBasedRunner', max_epochs=24)
  #resume_from = "/data1/qilei_chen/DATA/erosive/work_dirs/faster_rcnn_r50_fpn_1x_coco_with_empty/latest.pth"