OpenMMLab Detection Toolbox and Benchmark
https://mmdetection.readthedocs.io/
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57 lines
1.7 KiB
57 lines
1.7 KiB
2 years ago
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# model settings
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input_size = 300
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model = dict(
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type='SingleStageDetector',
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backbone=dict(
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type='SSDVGG',
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depth=16,
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with_last_pool=False,
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ceil_mode=True,
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out_indices=(3, 4),
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out_feature_indices=(22, 34),
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init_cfg=dict(
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type='Pretrained', checkpoint='open-mmlab://vgg16_caffe')),
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neck=dict(
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type='SSDNeck',
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in_channels=(512, 1024),
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out_channels=(512, 1024, 512, 256, 256, 256),
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level_strides=(2, 2, 1, 1),
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level_paddings=(1, 1, 0, 0),
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l2_norm_scale=20),
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bbox_head=dict(
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type='AscendSSDHead',
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in_channels=(512, 1024, 512, 256, 256, 256),
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num_classes=80,
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anchor_generator=dict(
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type='SSDAnchorGenerator',
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scale_major=False,
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input_size=input_size,
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basesize_ratio_range=(0.15, 0.9),
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strides=[8, 16, 32, 64, 100, 300],
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ratios=[[2], [2, 3], [2, 3], [2, 3], [2], [2]]),
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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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# model training and testing settings
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train_cfg=dict(
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assigner=dict(
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type='AscendMaxIoUAssigner',
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pos_iou_thr=0.5,
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neg_iou_thr=0.5,
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min_pos_iou=0.,
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ignore_iof_thr=-1,
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gt_max_assign_all=False),
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smoothl1_beta=1.,
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allowed_border=-1,
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pos_weight=-1,
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neg_pos_ratio=3,
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debug=False),
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test_cfg=dict(
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nms_pre=1000,
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nms=dict(type='nms', iou_threshold=0.45),
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min_bbox_size=0,
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score_thr=0.02,
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max_per_img=200))
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cudnn_benchmark = True
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