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model = dict(type='YOLOV3', |
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backbone=dict(type='Darknet', depth=53, out_indices=(3, 4, 5)), |
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neck=dict(type='YOLOV3Neck', |
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num_scales=3, |
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in_channels=[1024, 512, 256], |
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out_channels=[512, 256, 128]), |
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bbox_head=dict(type='YOLOV3Head', |
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num_classes=1, |
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in_channels=[512, 256, 128], |
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out_channels=[1024, 512, 256], |
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anchor_generator=dict(type='YOLOAnchorGenerator', |
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base_sizes=[[(116, 90), |
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(156, 198), |
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(373, 326)], |
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[(30, 61), |
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(62, 45), |
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(59, 119)], |
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[(10, 13), |
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(16, 30), |
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(33, 23)]], |
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strides=[32, 16, 8]), |
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bbox_coder=dict(type='YOLOBBoxCoder'), |
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featmap_strides=[32, 16, 8]), |
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test_cfg=dict(nms_pre=1000, |
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min_bbox_size=0, |
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score_thr=0.05, |
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conf_thr=0.005, |
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nms=dict(type='nms', iou_threshold=0.45), |
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max_per_img=100)) |
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test_pipeline = [ |
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dict(type='LoadImageFromFile'), |
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dict(type='MultiScaleFlipAug', |
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img_scale=(608, 608), |
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flip=False, |
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transforms=[ |
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dict(type='Resize', keep_ratio=True), |
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dict(type='RandomFlip'), |
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dict(type='Normalize', |
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mean=[0, 0, 0], |
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std=[255.0, 255.0, 255.0], |
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to_rgb=True), |
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dict(type='Pad', size_divisor=32), |
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dict(type='DefaultFormatBundle'), |
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dict(type='Collect', keys=['img']) |
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]) |
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] |
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data = dict(test=dict(pipeline=test_pipeline)) |
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|