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configs/baselines/e2e_faster_rcnn_R-101-FPN_1x.yaml

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+MODEL:
+  TYPE: generalized_rcnn
+  CONV_BODY: FPN.fpn_ResNet101_conv5_body
+  FASTER_RCNN: True
+RESNETS:
+  IMAGENET_PRETRAINED_WEIGHTS: 'data/pretrained_model/resnet101_caffe.pth'
+NUM_GPUS: 8
+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_ROIS: True
+  MULTILEVEL_RPN: True
+FAST_RCNN:
+  ROI_BOX_HEAD: fast_rcnn_heads.roi_2mlp_head
+  ROI_XFORM_METHOD: RoIAlign
+  ROI_XFORM_RESOLUTION: 7
+  ROI_XFORM_SAMPLING_RATIO: 2
+TRAIN:
+  SCALES: (800,)
+  MAX_SIZE: 1333
+  BATCH_SIZE_PER_IM: 512
+  RPN_PRE_NMS_TOP_N: 2000  # Per FPN level
+TEST:
+  SCALE: 800
+  MAX_SIZE: 1333
+  NMS: 0.5
+  RPN_PRE_NMS_TOP_N: 1000  # Per FPN level
+  RPN_POST_NMS_TOP_N: 1000
+

configs/baselines/e2e_faster_rcnn_R-101-FPN_2x.yaml

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+MODEL:
+  TYPE: generalized_rcnn
+  CONV_BODY: FPN.fpn_ResNet101_conv5_body
+  FASTER_RCNN: True
+RESNETS:
+  IMAGENET_PRETRAINED_WEIGHTS: 'data/pretrained_model/resnet101_caffe.pth'
+NUM_GPUS: 8
+SOLVER:
+  WEIGHT_DECAY: 0.0001
+  LR_POLICY: steps_with_decay
+  BASE_LR: 0.02
+  GAMMA: 0.1
+  MAX_ITER: 180000
+  STEPS: [0, 120000, 160000]
+FPN:
+  FPN_ON: True
+  MULTILEVEL_ROIS: True
+  MULTILEVEL_RPN: True
+FAST_RCNN:
+  ROI_BOX_HEAD: fast_rcnn_heads.roi_2mlp_head
+  ROI_XFORM_METHOD: RoIAlign
+  ROI_XFORM_RESOLUTION: 7
+  ROI_XFORM_SAMPLING_RATIO: 2
+TRAIN:
+  SCALES: (800,)
+  MAX_SIZE: 1333
+  BATCH_SIZE_PER_IM: 512
+  RPN_PRE_NMS_TOP_N: 2000  # Per FPN level
+TEST:
+  SCALE: 800
+  MAX_SIZE: 1333
+  NMS: 0.5
+  RPN_PRE_NMS_TOP_N: 1000  # Per FPN level
+  RPN_POST_NMS_TOP_N: 1000

configs/baselines/e2e_faster_rcnn_R-50-C4_1x.yaml

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+MODEL:
+  TYPE: generalized_rcnn
+  CONV_BODY: ResNet.ResNet50_conv4_body
+  FASTER_RCNN: True
+NUM_GPUS: 8
+RESNETS:
+  IMAGENET_PRETRAINED_WEIGHTS: 'data/pretrained_model/resnet50_caffe.pth'
+SOLVER:
+  WEIGHT_DECAY: 0.0001
+  LR_POLICY: steps_with_decay
+  BASE_LR: 0.01
+  GAMMA: 0.1
+  # 1x schedule (note TRAIN.IMS_PER_BATCH: 1)
+  MAX_ITER: 180000
+  STEPS: [0, 120000, 160000]
+RPN:
+  SIZES: (32, 64, 128, 256, 512)
+FAST_RCNN:
+  ROI_BOX_HEAD: ResNet.ResNet_roi_conv5_head
+  ROI_XFORM_METHOD: RoIAlign
+TRAIN:
+  SCALES: (800,)
+  MAX_SIZE: 1333
+  IMS_PER_BATCH: 1
+  BATCH_SIZE_PER_IM: 512
+TEST:
+  SCALE: 800
+  MAX_SIZE: 1333
+  NMS: 0.5
+  RPN_PRE_NMS_TOP_N: 6000
+  RPN_POST_NMS_TOP_N: 1000

configs/baselines/e2e_faster_rcnn_R-50-C4_2x.yaml

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+MODEL:
+  TYPE: generalized_rcnn
+  CONV_BODY: ResNet.ResNet50_conv4_body
+  FASTER_RCNN: True
+RESNETS:
+  IMAGENET_PRETRAINED_WEIGHTS: 'data/pretrained_model/resnet50_caffe.pth'
+NUM_GPUS: 8
+SOLVER:
+  WEIGHT_DECAY: 0.0001
+  LR_POLICY: steps_with_decay
+  BASE_LR: 0.01
+  GAMMA: 0.1
+  # 2x schedule (note TRAIN.IMS_PER_BATCH: 1)
+  MAX_ITER: 360000
+  STEPS: [0, 240000, 320000]
+RPN:
+  SIZES: (32, 64, 128, 256, 512)
+FAST_RCNN:
+  ROI_BOX_HEAD: ResNet.ResNet_roi_conv5_head
+  ROI_XFORM_METHOD: RoIAlign
+TRAIN:
+  SCALES: (800,)
+  MAX_SIZE: 1333
+  IMS_PER_BATCH: 1
+  BATCH_SIZE_PER_IM: 512
+TEST:
+  SCALE: 800
+  MAX_SIZE: 1333
+  NMS: 0.5
+  RPN_PRE_NMS_TOP_N: 6000
+  RPN_POST_NMS_TOP_N: 1000
+

configs/baselines/e2e_faster_rcnn_R-50-FPN_1x.yaml

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+MODEL:
+  TYPE: generalized_rcnn
+  CONV_BODY: FPN.fpn_ResNet50_conv5_body
+  FASTER_RCNN: True
+RESNETS:
+  IMAGENET_PRETRAINED_WEIGHTS: 'data/pretrained_model/resnet50_caffe.pth'
+NUM_GPUS: 2
+SOLVER:
+  WEIGHT_DECAY: 0.0001
+  LR_POLICY: steps_with_decay
+  BASE_LR: 0.02
+  GAMMA: 0.1
+  MAX_ITER: 95000
+  STEPS: [0, 24000, 80000]
+FPN:
+  FPN_ON: True
+  MULTILEVEL_ROIS: True
+  MULTILEVEL_RPN: True
+FAST_RCNN:
+  ROI_BOX_HEAD: fast_rcnn_heads.roi_2mlp_head
+  ROI_XFORM_METHOD: RoIAlign
+  ROI_XFORM_RESOLUTION: 7
+  ROI_XFORM_SAMPLING_RATIO: 2
+TRAIN:
+  SCALES: (800,)
+  MAX_SIZE: 1333
+  BATCH_SIZE_PER_IM: 512
+  RPN_PRE_NMS_TOP_N: 2000  # Per FPN level
+TEST:
+  SCALE: 800
+  MAX_SIZE: 1333
+  NMS: 0.5
+  RPN_PRE_NMS_TOP_N: 1000  # Per FPN level
+  RPN_POST_NMS_TOP_N: 1000

configs/baselines/e2e_faster_rcnn_R-50-FPN_2x.yaml

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+MODEL:
+  TYPE: generalized_rcnn
+  CONV_BODY: FPN.fpn_ResNet50_conv5_body
+  FASTER_RCNN: True
+RESNETS:
+  IMAGENET_PRETRAINED_WEIGHTS: 'data/pretrained_model/resnet50_caffe.pth'
+NUM_GPUS: 8
+SOLVER:
+  WEIGHT_DECAY: 0.0001
+  LR_POLICY: steps_with_decay
+  BASE_LR: 0.02
+  GAMMA: 0.1
+  MAX_ITER: 180000
+  STEPS: [0, 120000, 160000]
+FPN:
+  FPN_ON: True
+  MULTILEVEL_ROIS: True
+  MULTILEVEL_RPN: True
+FAST_RCNN:
+  ROI_BOX_HEAD: fast_rcnn_heads.roi_2mlp_head
+  ROI_XFORM_METHOD: RoIAlign
+  ROI_XFORM_RESOLUTION: 7
+  ROI_XFORM_SAMPLING_RATIO: 2
+TRAIN:
+  SCALES: (800,)
+  MAX_SIZE: 1333
+  BATCH_SIZE_PER_IM: 512
+  RPN_PRE_NMS_TOP_N: 2000  # Per FPN level
+TEST:
+  SCALE: 800
+  MAX_SIZE: 1333
+  NMS: 0.5
+  RPN_PRE_NMS_TOP_N: 1000  # Per FPN level
+  RPN_POST_NMS_TOP_N: 1000

configs/baselines/e2e_faster_rcnn_R-50-FPN_ciou_1x.yaml

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+MODEL:
+  TYPE: generalized_rcnn
+  CONV_BODY: FPN.fpn_ResNet50_conv5_body
+  FASTER_RCNN: True
+  LOSS_TYPE: 'ciou'
+  LOSS_BBOX_WEIGHT: 12.
+RESNETS:
+  IMAGENET_PRETRAINED_WEIGHTS: 'data/pretrained_model/resnet50_caffe.pth'
+NUM_GPUS: 8
+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_ROIS: True
+  MULTILEVEL_RPN: True
+FAST_RCNN:
+  ROI_BOX_HEAD: fast_rcnn_heads.roi_2mlp_head
+  ROI_XFORM_METHOD: RoIAlign
+  ROI_XFORM_RESOLUTION: 7
+  ROI_XFORM_SAMPLING_RATIO: 2
+TRAIN:
+  SCALES: (800,)
+  MAX_SIZE: 1333
+  BATCH_SIZE_PER_IM: 512
+  RPN_PRE_NMS_TOP_N: 2000  # Per FPN level
+TEST:
+  SCALE: 800
+  MAX_SIZE: 1333
+  NMS: 0.5
+  RPN_PRE_NMS_TOP_N: 1000  # Per FPN level
+  RPN_POST_NMS_TOP_N: 1000

configs/baselines/e2e_faster_rcnn_R-50-FPN_diou_1x.yaml

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+MODEL:
+  TYPE: generalized_rcnn
+  CONV_BODY: FPN.fpn_ResNet50_conv5_body
+  FASTER_RCNN: True
+  LOSS_TYPE: 'diou'
+  LOSS_BBOX_WEIGHT: 12.
+RESNETS:
+  IMAGENET_PRETRAINED_WEIGHTS: 'data/pretrained_model/resnet50_caffe.pth'
+NUM_GPUS: 8
+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_ROIS: True
+  MULTILEVEL_RPN: True
+FAST_RCNN:
+  ROI_BOX_HEAD: fast_rcnn_heads.roi_2mlp_head
+  ROI_XFORM_METHOD: RoIAlign
+  ROI_XFORM_RESOLUTION: 7
+  ROI_XFORM_SAMPLING_RATIO: 2
+TRAIN:
+  SCALES: (800,)
+  MAX_SIZE: 1333
+  BATCH_SIZE_PER_IM: 512
+  RPN_PRE_NMS_TOP_N: 2000  # Per FPN level
+TEST:
+  SCALE: 800
+  MAX_SIZE: 1333
+  NMS: 0.5
+  RPN_PRE_NMS_TOP_N: 1000  # Per FPN level
+  RPN_POST_NMS_TOP_N: 1000

configs/baselines/e2e_faster_rcnn_R-50-FPN_giou_1x.yaml

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+MODEL:
+  TYPE: generalized_rcnn
+  CONV_BODY: FPN.fpn_ResNet50_conv5_body
+  FASTER_RCNN: True
+  LOSS_TYPE: 'giou'
+  LOSS_BBOX_WEIGHT: 12.
+RESNETS:
+  IMAGENET_PRETRAINED_WEIGHTS: 'data/pretrained_model/resnet50_caffe.pth'
+NUM_GPUS: 8
+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_ROIS: True
+  MULTILEVEL_RPN: True
+FAST_RCNN:
+  ROI_BOX_HEAD: fast_rcnn_heads.roi_2mlp_head
+  ROI_XFORM_METHOD: RoIAlign
+  ROI_XFORM_RESOLUTION: 7
+  ROI_XFORM_SAMPLING_RATIO: 2
+TRAIN:
+  SCALES: (800,)
+  MAX_SIZE: 1333
+  BATCH_SIZE_PER_IM: 512
+  RPN_PRE_NMS_TOP_N: 2000  # Per FPN level
+TEST:
+  SCALE: 800
+  MAX_SIZE: 1333
+  NMS: 0.5
+  RPN_PRE_NMS_TOP_N: 1000  # Per FPN level
+  RPN_POST_NMS_TOP_N: 1000

configs/baselines/e2e_faster_rcnn_R-50-FPN_iou_1x.yaml

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+MODEL:
+  TYPE: generalized_rcnn
+  CONV_BODY: FPN.fpn_ResNet50_conv5_body
+  FASTER_RCNN: True
+  LOSS_TYPE: 'iou'
+  LOSS_BBOX_WEIGHT: 12.
+RESNETS:
+  IMAGENET_PRETRAINED_WEIGHTS: 'data/pretrained_model/resnet50_caffe.pth'
+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_ROIS: True
+  MULTILEVEL_RPN: True
+FAST_RCNN:
+  ROI_BOX_HEAD: fast_rcnn_heads.roi_2mlp_head
+  ROI_XFORM_METHOD: RoIAlign
+  ROI_XFORM_RESOLUTION: 7
+  ROI_XFORM_SAMPLING_RATIO: 2
+TRAIN:
+  SCALES: (800,)
+  MAX_SIZE: 1333
+  BATCH_SIZE_PER_IM: 512
+  RPN_PRE_NMS_TOP_N: 2000  # Per FPN level
+TEST:
+  SCALE: 800
+  MAX_SIZE: 1333
+  NMS: 0.5
+  RPN_PRE_NMS_TOP_N: 1000  # Per FPN level
+  RPN_POST_NMS_TOP_N: 1000

configs/baselines/e2e_faster_rcnn_R-50-FPN_rpn_giou_1x.yaml

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+MODEL:
+  TYPE: generalized_rcnn
+  CONV_BODY: FPN.fpn_ResNet50_conv5_body
+  FASTER_RCNN: True
+  LOSS_TYPE: 'giou'
+  RPN_LOSS_TYPE: 'giou'
+  LOSS_BBOX_WEIGHT: 10.
+  RPN_LOSS_BBOX_WEIGHT: 1.
+RESNETS:
+  IMAGENET_PRETRAINED_WEIGHTS: 'data/pretrained_model/resnet50_caffe.pth'
+NUM_GPUS: 8
+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_ROIS: True
+  MULTILEVEL_RPN: True
+FAST_RCNN:
+  ROI_BOX_HEAD: fast_rcnn_heads.roi_2mlp_head
+  ROI_XFORM_METHOD: RoIAlign
+  ROI_XFORM_RESOLUTION: 7
+  ROI_XFORM_SAMPLING_RATIO: 2
+TRAIN:
+  SCALES: (800,)
+  MAX_SIZE: 1333
+  BATCH_SIZE_PER_IM: 512
+  RPN_PRE_NMS_TOP_N: 2000  # Per FPN level
+TEST:
+  SCALE: 800
+  MAX_SIZE: 1333
+  NMS: 0.5
+  RPN_PRE_NMS_TOP_N: 1000  # Per FPN level
+  RPN_POST_NMS_TOP_N: 1000