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# model settings | |
model = dict( | |
type='OCRMaskRCNN', | |
backbone=dict( | |
type='mmdet.ResNet', | |
depth=50, | |
num_stages=4, | |
out_indices=(0, 1, 2, 3), | |
frozen_stages=1, | |
norm_cfg=dict(type='BN', requires_grad=True), | |
init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50'), | |
norm_eval=True, | |
style='pytorch'), | |
neck=dict( | |
type='mmdet.FPN', | |
in_channels=[256, 512, 1024, 2048], | |
out_channels=256, | |
num_outs=5), | |
rpn_head=dict( | |
type='RPNHead', | |
in_channels=256, | |
feat_channels=256, | |
anchor_generator=dict( | |
type='AnchorGenerator', | |
scales=[4], | |
ratios=[0.17, 0.44, 1.13, 2.90, 7.46], | |
strides=[4, 8, 16, 32, 64]), | |
bbox_coder=dict( | |
type='DeltaXYWHBBoxCoder', | |
target_means=[.0, .0, .0, .0], | |
target_stds=[1.0, 1.0, 1.0, 1.0]), | |
loss_cls=dict( | |
type='CrossEntropyLoss', use_sigmoid=True, loss_weight=1.0), | |
loss_bbox=dict(type='L1Loss', loss_weight=1.0)), | |
roi_head=dict( | |
type='StandardRoIHead', | |
bbox_roi_extractor=dict( | |
type='SingleRoIExtractor', | |
roi_layer=dict(type='RoIAlign', output_size=7, sampling_ratio=0), | |
out_channels=256, | |
featmap_strides=[4, 8, 16, 32]), | |
bbox_head=dict( | |
type='Shared2FCBBoxHead', | |
in_channels=256, | |
fc_out_channels=1024, | |
roi_feat_size=7, | |
num_classes=1, | |
bbox_coder=dict( | |
type='DeltaXYWHBBoxCoder', | |
target_means=[0., 0., 0., 0.], | |
target_stds=[0.1, 0.1, 0.2, 0.2]), | |
reg_class_agnostic=False, | |
loss_cls=dict( | |
type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0), | |
loss_bbox=dict(type='L1Loss', loss_weight=1.0)), | |
mask_roi_extractor=dict( | |
type='SingleRoIExtractor', | |
roi_layer=dict(type='RoIAlign', output_size=14, sampling_ratio=0), | |
out_channels=256, | |
featmap_strides=[4, 8, 16, 32]), | |
mask_head=dict( | |
type='FCNMaskHead', | |
num_convs=4, | |
in_channels=256, | |
conv_out_channels=256, | |
num_classes=1, | |
loss_mask=dict( | |
type='CrossEntropyLoss', use_mask=True, loss_weight=1.0))), | |
# model training and testing settings | |
train_cfg=dict( | |
rpn=dict( | |
assigner=dict( | |
type='MaxIoUAssigner', | |
pos_iou_thr=0.7, | |
neg_iou_thr=0.3, | |
min_pos_iou=0.3, | |
match_low_quality=True, | |
ignore_iof_thr=-1, | |
gpu_assign_thr=50), | |
sampler=dict( | |
type='RandomSampler', | |
num=256, | |
pos_fraction=0.5, | |
neg_pos_ub=-1, | |
add_gt_as_proposals=False), | |
allowed_border=-1, | |
pos_weight=-1, | |
debug=False), | |
rpn_proposal=dict( | |
nms_across_levels=False, | |
nms_pre=2000, | |
nms_post=1000, | |
max_per_img=1000, | |
nms=dict(type='nms', iou_threshold=0.7), | |
min_bbox_size=0), | |
rcnn=dict( | |
assigner=dict( | |
type='MaxIoUAssigner', | |
pos_iou_thr=0.5, | |
neg_iou_thr=0.5, | |
min_pos_iou=0.5, | |
match_low_quality=True, | |
ignore_iof_thr=-1), | |
sampler=dict( | |
type='OHEMSampler', | |
num=512, | |
pos_fraction=0.25, | |
neg_pos_ub=-1, | |
add_gt_as_proposals=True), | |
mask_size=28, | |
pos_weight=-1, | |
debug=False)), | |
test_cfg=dict( | |
rpn=dict( | |
nms_across_levels=False, | |
nms_pre=1000, | |
nms_post=1000, | |
max_per_img=1000, | |
nms=dict(type='nms', iou_threshold=0.7), | |
min_bbox_size=0), | |
rcnn=dict( | |
score_thr=0.05, | |
nms=dict(type='nms', iou_threshold=0.5), | |
max_per_img=100, | |
mask_thr_binary=0.5))) | |