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_base_ = [ |
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'../_base_/models/faster_rcnn_r50_fpn.py', |
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'../_base_/datasets/cityscapes_detection.py', |
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'../_base_/default_runtime.py' |
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] |
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model = dict( |
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backbone=dict(init_cfg=None), |
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roi_head=dict( |
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bbox_head=dict( |
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type='Shared2FCBBoxHead', |
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in_channels=256, |
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fc_out_channels=1024, |
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roi_feat_size=7, |
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num_classes=8, |
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bbox_coder=dict( |
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type='DeltaXYWHBBoxCoder', |
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target_means=[0., 0., 0., 0.], |
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target_stds=[0.1, 0.1, 0.2, 0.2]), |
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reg_class_agnostic=False, |
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loss_cls=dict( |
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type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0), |
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loss_bbox=dict(type='SmoothL1Loss', beta=1.0, loss_weight=1.0)))) |
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optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001) |
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optimizer_config = dict(grad_clip=None) |
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lr_config = dict( |
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policy='step', |
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warmup='linear', |
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warmup_iters=500, |
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warmup_ratio=0.001, |
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step=[7]) |
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runner = dict( |
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type='EpochBasedRunner', max_epochs=8) |
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log_config = dict(interval=100) |
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load_from = 'https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_1x_coco/faster_rcnn_r50_fpn_1x_coco_20200130-047c8118.pth' |
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auto_scale_lr = dict(base_batch_size=8) |
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