MODEL:
  TYPE: generalized_rcnn
  CONV_BODY: FPN.add_fpn_ResNet101_conv5_body
  NUM_CLASSES: 2
  FASTER_RCNN: True
  KEYPOINTS_ON: True
NUM_GPUS: 8
SOLVER:
  WEIGHT_DECAY: 0.0001
  LR_POLICY: steps_with_decay
  BASE_LR: 0.02
  GAMMA: 0.1
  MAX_ITER: 130000
  STEPS: [0, 100000, 120000]
FPN:
  FPN_ON: True
  MULTILEVEL_ROIS: True
  MULTILEVEL_RPN: True
RESNETS:
  STRIDE_1X1: False  # default True for MSRA; False for C2 or Torch models
  TRANS_FUNC: bottleneck_transformation
  NUM_GROUPS: 64
  WIDTH_PER_GROUP: 4
FAST_RCNN:
  ROI_BOX_HEAD: head_builder.add_roi_2mlp_head
  ROI_XFORM_METHOD: RoIAlign
  ROI_XFORM_RESOLUTION: 7
  ROI_XFORM_SAMPLING_RATIO: 2
KRCNN:
  ROI_KEYPOINTS_HEAD: keypoint_rcnn_heads.add_roi_pose_head_v1convX
  NUM_STACKED_CONVS: 8
  NUM_KEYPOINTS: 17
  USE_DECONV_OUTPUT: True
  CONV_INIT: MSRAFill
  CONV_HEAD_DIM: 512
  UP_SCALE: 2
  HEATMAP_SIZE: 56  # ROI_XFORM_RESOLUTION (14) * UP_SCALE (2) * USE_DECONV_OUTPUT (2)
  ROI_XFORM_METHOD: RoIAlign
  ROI_XFORM_RESOLUTION: 14
  ROI_XFORM_SAMPLING_RATIO: 2
  KEYPOINT_CONFIDENCE: bbox
TRAIN:
  # md5sum of weights pkl file: aa14062280226e48f569ef1c7212e7c7
  WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl
  DATASETS: ('keypoints_coco_2014_train', 'keypoints_coco_2014_valminusminival')
  SCALES: (640, 672, 704, 736, 768, 800)
  MAX_SIZE: 1333
  BATCH_SIZE_PER_IM: 512
  RPN_PRE_NMS_TOP_N: 2000  # Per FPN level
TEST:
  DATASETS: ('keypoints_coco_2014_minival',)
  SCALES: (800,)
  MAX_SIZE: 1333
  NMS: 0.5
  RPN_PRE_NMS_TOP_N: 1000  # Per FPN level
  RPN_POST_NMS_TOP_N: 1000
OUTPUT_DIR: .
