rpn_densepose_only_X-101-32x8d-FPN_1x.yaml

MODEL:
  TYPE: generalized_rcnn
  CONV_BODY: FPN.add_fpn_ResNet101_conv5_body
  NUM_CLASSES: 2
  RPN_ONLY: True
NUM_GPUS: 1
SOLVER:
  WEIGHT_DECAY: 0.0001
  LR_POLICY: steps_with_decay
  BASE_LR: 0.02
  GAMMA: 0.1
  MAX_ITER: 90000
  STEPS: [0, 60000, 80000]
FPN:
  FPN_ON: True
  MULTILEVEL_RPN: True
  RPN_MAX_LEVEL: 6
  RPN_MIN_LEVEL: 2
  RPN_ANCHOR_START_SIZE: 32
  RPN_ASPECT_RATIOS: (0.5, 1, 2)
RESNETS:
  STRIDE_1X1: False  # default True for MSRA; False for C2 or Torch models
  TRANS_FUNC: bottleneck_transformation
  NUM_GROUPS: 32
  WIDTH_PER_GROUP: 8
TRAIN:
  WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl
  DATASETS: ('keypoints_coco_2014_train', 'keypoints_coco_2014_valminusminival')
  SCALES: (800,)
  MAX_SIZE: 1333
TEST:
  WEIGHTS: https://dl.fbaipublicfiles.com/detectron/36760438/12_2017_baselines/rpn_person_only_X-101-32x8d-FPN_1x.yaml.06_04_23.M2oJlDPW/output/train/keypoints_coco_2014_train%3Akeypoints_coco_2014_valminusminival/generalized_rcnn/model_final.pkl
  DATASETS: ( 'dense_coco_2014_minival', 'dense_coco_2014_valminusminival')
  SCALE: 800
  MAX_SIZE: 1333
  RPN_PRE_NMS_TOP_N: 1000  # Per FPN level
  RPN_POST_NMS_TOP_N: 2000
OUTPUT_DIR: /home/goku/DensePose/CleanJSONs/