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[Fix] Twice softmax bug in
bbox_head & evaluation bug in dense head.
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
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@@ -124,4 +124,5 @@ work_dirs/ | |
| *.sh~ | ||
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||
| *.slurm | ||
| slurm_* | ||
| slurm_* | ||
| slurm-* | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,266 @@ | ||
| _base_ = [ | ||
| '../_base_/models/cascade_rcnn_r50_fpn_locount.py', | ||
| '../_base_/datasets/coco_LHC.py', | ||
| '../_base_/schedules/schedule_1x.py', | ||
| '../_base_/default_runtime.py' | ||
| ] | ||
| model = dict( | ||
| roi_head=dict( | ||
| num_stages=6, | ||
| stage_loss_weights=[1, 0.833, 0.667, 0.5, 0.333, 0.167], # TODO | ||
| stage_cnt_loss_weights=[0.1, 0.1, 0.1, 0.1, 0.1, 0.1], # TODO | ||
| base=2, | ||
| bbox_head=[ | ||
| dict( | ||
| type='FCBBoxHeadWithCount', | ||
| num_shared_fcs=2, | ||
| in_channels=256, | ||
| fc_out_channels=1024, | ||
| roi_feat_size=7, | ||
| num_classes=140, | ||
| num_counts=56, | ||
| bbox_coder=dict( | ||
| type='DeltaXYWHBBoxCoder', | ||
| target_means=[0., 0., 0., 0.], | ||
| target_stds=[0.1, 0.1, 0.2, 0.2]), | ||
| reg_class_agnostic=True, | ||
| loss_cls=dict( | ||
| type='CrossEntropyLoss', | ||
| use_sigmoid=False, | ||
| loss_weight=1.0), | ||
| loss_bbox=dict( | ||
| type='SmoothL1Loss', | ||
| beta=1.0, | ||
| loss_weight=1.0), | ||
| loss_cnt=dict( | ||
| type='CrossEntropyLoss', | ||
| use_sigmoid=False, | ||
| loss_weight=1.0)), | ||
| dict( | ||
| type='FCBBoxHeadWithCount', | ||
| num_shared_fcs=2, | ||
| in_channels=256, | ||
| fc_out_channels=1024, | ||
| roi_feat_size=7, | ||
| num_classes=140, | ||
| num_counts=56, | ||
| bbox_coder=dict( | ||
| type='DeltaXYWHBBoxCoder', | ||
| target_means=[0., 0., 0., 0.], | ||
| target_stds=[0.083, 0.083, 0.167, 0.167]), # TODO | ||
| reg_class_agnostic=True, | ||
| loss_cls=dict( | ||
| type='CrossEntropyLoss', | ||
| use_sigmoid=False, | ||
| loss_weight=1.0), | ||
| loss_bbox=dict( | ||
| type='SmoothL1Loss', | ||
| beta=1.0, | ||
| loss_weight=1.0), | ||
| loss_cnt=dict( | ||
| type='CrossEntropyLoss', | ||
| use_sigmoid=False, | ||
| loss_weight=1.0)), | ||
| dict( | ||
| type='FCBBoxHeadWithCount', | ||
| num_shared_fcs=2, | ||
| in_channels=256, | ||
| fc_out_channels=1024, | ||
| roi_feat_size=7, | ||
| num_classes=140, | ||
| num_counts=56, | ||
| bbox_coder=dict( | ||
| type='DeltaXYWHBBoxCoder', | ||
| target_means=[0., 0., 0., 0.], | ||
| target_stds=[0.067, 0.067, 0.133, 0.133]), # TODO | ||
| reg_class_agnostic=True, | ||
| loss_cls=dict( | ||
| type='CrossEntropyLoss', | ||
| use_sigmoid=False, | ||
| loss_weight=1.0), | ||
| loss_bbox=dict( | ||
| type='SmoothL1Loss', | ||
| beta=1.0, | ||
| loss_weight=1.0), | ||
| loss_cnt=dict( | ||
| type='CrossEntropyLoss', | ||
| use_sigmoid=False, | ||
| loss_weight=1.0)), | ||
| dict( | ||
| type='FCBBoxHeadWithCount', | ||
| num_shared_fcs=2, | ||
| in_channels=256, | ||
| fc_out_channels=1024, | ||
| roi_feat_size=7, | ||
| num_classes=140, | ||
| num_counts=56, | ||
| bbox_coder=dict( | ||
| type='DeltaXYWHBBoxCoder', | ||
| target_means=[0., 0., 0., 0.], | ||
| target_stds=[0.05, 0.05, 0.1, 0.1]), | ||
| reg_class_agnostic=True, | ||
| loss_cls=dict( | ||
| type='CrossEntropyLoss', | ||
| use_sigmoid=False, | ||
| loss_weight=1.0), | ||
| loss_bbox=dict( | ||
| type='SmoothL1Loss', | ||
| beta=1.0, | ||
| loss_weight=1.0), | ||
| loss_cnt=dict( | ||
| type='CrossEntropyLoss', | ||
| use_sigmoid=False, | ||
| loss_weight=1.0)), | ||
| dict( | ||
| type='FCBBoxHeadWithCount', | ||
| num_shared_fcs=2, | ||
| in_channels=256, | ||
| fc_out_channels=1024, | ||
| roi_feat_size=7, | ||
| num_classes=140, | ||
| num_counts=56, | ||
| bbox_coder=dict( | ||
| type='DeltaXYWHBBoxCoder', | ||
| target_means=[0., 0., 0., 0.], | ||
| target_stds=[0.033, 0.033, 0.067, 0.067]), | ||
| reg_class_agnostic=True, | ||
| loss_cls=dict( | ||
| type='CrossEntropyLoss', | ||
| use_sigmoid=False, | ||
| loss_weight=1.0), | ||
| loss_bbox=dict( | ||
| type='SmoothL1Loss', | ||
| beta=1.0, | ||
| loss_weight=1.0), | ||
| loss_cnt=dict( | ||
| type='CrossEntropyLoss', | ||
| use_sigmoid=False, | ||
| loss_weight=1.0)), | ||
| dict( | ||
| type='FCBBoxHeadWithCount', | ||
| num_shared_fcs=2, | ||
| in_channels=256, | ||
| fc_out_channels=1024, | ||
| roi_feat_size=7, | ||
| num_classes=140, | ||
| num_counts=56, | ||
| bbox_coder=dict( | ||
| type='DeltaXYWHBBoxCoder', | ||
| target_means=[0., 0., 0., 0.], | ||
| target_stds=[0.017, 0.017, 0.033, 0.033]), # TODO | ||
| reg_class_agnostic=True, | ||
| loss_cls=dict( | ||
| type='CrossEntropyLoss', | ||
| use_sigmoid=False, | ||
| loss_weight=1.0), | ||
| loss_bbox=dict( | ||
| type='SmoothL1Loss', | ||
| beta=1.0, | ||
| loss_weight=1.0), | ||
| loss_cnt=dict( | ||
| type='CrossEntropyLoss', | ||
| use_sigmoid=False, | ||
| loss_weight=1.0)), | ||
| ] | ||
| ), | ||
| train_cfg=dict( | ||
| rcnn=[ | ||
| dict( | ||
| assigner=dict( | ||
| type='MaxIoUAssignerWithCount', | ||
| pos_iou_thr=0.5, | ||
| neg_iou_thr=0.5, | ||
| min_pos_iou=0.5, | ||
| match_low_quality=False, | ||
| ignore_iof_thr=-1), | ||
| sampler=dict( | ||
| type='RandomSamplerWithCount', | ||
| num=512, | ||
| pos_fraction=0.25, | ||
| neg_pos_ub=-1, | ||
| add_gt_as_proposals=True), | ||
| pos_weight=-1, | ||
| debug=False), | ||
| dict( | ||
| assigner=dict( | ||
| type='MaxIoUAssignerWithCount', | ||
| pos_iou_thr=0.55, | ||
| neg_iou_thr=0.55, | ||
| min_pos_iou=0.55, | ||
| match_low_quality=False, | ||
| ignore_iof_thr=-1), | ||
| sampler=dict( | ||
| type='RandomSamplerWithCount', | ||
| num=512, | ||
| pos_fraction=0.25, | ||
| neg_pos_ub=-1, | ||
| add_gt_as_proposals=True), | ||
| pos_weight=-1, | ||
| debug=False), | ||
| dict( | ||
| assigner=dict( | ||
| type='MaxIoUAssignerWithCount', | ||
| pos_iou_thr=0.6, | ||
| neg_iou_thr=0.6, | ||
| min_pos_iou=0.6, | ||
| match_low_quality=False, | ||
| ignore_iof_thr=-1), | ||
| sampler=dict( | ||
| type='RandomSamplerWithCount', | ||
| num=512, | ||
| pos_fraction=0.25, | ||
| neg_pos_ub=-1, | ||
| add_gt_as_proposals=True), | ||
| pos_weight=-1, | ||
| debug=False), | ||
| dict( | ||
| assigner=dict( | ||
| type='MaxIoUAssignerWithCount', | ||
| pos_iou_thr=0.65, | ||
| neg_iou_thr=0.65, | ||
| min_pos_iou=0.65, | ||
| match_low_quality=False, | ||
| ignore_iof_thr=-1), | ||
| sampler=dict( | ||
| type='RandomSamplerWithCount', | ||
| num=512, | ||
| pos_fraction=0.25, | ||
| neg_pos_ub=-1, | ||
| add_gt_as_proposals=True), | ||
| pos_weight=-1, | ||
| debug=False), | ||
| dict( | ||
| assigner=dict( | ||
| type='MaxIoUAssignerWithCount', | ||
| pos_iou_thr=0.7, | ||
| neg_iou_thr=0.7, | ||
| min_pos_iou=0.7, | ||
| match_low_quality=False, | ||
| ignore_iof_thr=-1), | ||
| sampler=dict( | ||
| type='RandomSamplerWithCount', | ||
| num=512, | ||
| pos_fraction=0.25, | ||
| neg_pos_ub=-1, | ||
| add_gt_as_proposals=True), | ||
| pos_weight=-1, | ||
| debug=False), | ||
| dict( | ||
| assigner=dict( | ||
| type='MaxIoUAssignerWithCount', | ||
| pos_iou_thr=0.75, | ||
| neg_iou_thr=0.75, | ||
| min_pos_iou=0.75, | ||
| match_low_quality=False, | ||
| ignore_iof_thr=-1), | ||
| sampler=dict( | ||
| type='RandomSamplerWithCount', | ||
| num=512, | ||
| pos_fraction=0.25, | ||
| neg_pos_ub=-1, | ||
| add_gt_as_proposals=True), | ||
| pos_weight=-1, | ||
| debug=False) | ||
| ] | ||
| ), | ||
| ) |
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