mirror of https://github.com/AlexeyAB/darknet.git
333 lines
3.6 KiB
INI
333 lines
3.6 KiB
INI
[net]
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# Testing
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#batch=1
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#subdivisions=1
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# Training
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batch=64
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subdivisions=1
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width=608
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height=608
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channels=3
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momentum=0.9
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decay=0.0005
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angle=0
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saturation = 1.5
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exposure = 1.5
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hue=.1
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learning_rate=0.00261
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burn_in=1000
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max_batches = 500200
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policy=steps
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steps=400000,450000
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scales=.1,.1
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[convolutional]
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batch_normalize=1
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filters=32
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size=3
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stride=2
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pad=1
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activation=leaky
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[convolutional]
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batch_normalize=1
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filters=64
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size=3
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stride=2
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pad=1
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activation=leaky
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[convolutional]
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batch_normalize=1
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filters=64
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size=3
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stride=1
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pad=1
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activation=leaky
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[route]
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layers=-1
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groups=2
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group_id=1
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[convolutional]
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batch_normalize=1
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filters=32
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size=3
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stride=1
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pad=1
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activation=leaky
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[convolutional]
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batch_normalize=1
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filters=32
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size=3
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stride=1
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pad=1
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activation=leaky
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[route]
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layers = -1,-2
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[convolutional]
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batch_normalize=1
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filters=64
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size=1
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stride=1
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pad=1
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activation=leaky
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[route]
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layers = -6,-1
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[maxpool]
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size=2
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stride=2
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[convolutional]
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batch_normalize=1
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filters=128
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size=3
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stride=1
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pad=1
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activation=leaky
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[route]
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layers=-1
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groups=2
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group_id=1
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[convolutional]
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batch_normalize=1
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filters=64
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size=3
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stride=1
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pad=1
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activation=leaky
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[convolutional]
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batch_normalize=1
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filters=64
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size=3
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stride=1
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pad=1
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activation=leaky
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[route]
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layers = -1,-2
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[convolutional]
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batch_normalize=1
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filters=128
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size=1
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stride=1
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pad=1
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activation=leaky
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[route]
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layers = -6,-1
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[maxpool]
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size=2
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stride=2
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[convolutional]
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batch_normalize=1
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filters=256
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size=3
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stride=1
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pad=1
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activation=leaky
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[route]
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layers=-1
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groups=2
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group_id=1
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[convolutional]
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batch_normalize=1
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filters=128
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size=3
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stride=1
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pad=1
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activation=leaky
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[convolutional]
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batch_normalize=1
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filters=128
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size=3
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stride=1
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pad=1
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activation=leaky
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[route]
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layers = -1,-2
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[convolutional]
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batch_normalize=1
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filters=256
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size=1
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stride=1
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pad=1
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activation=leaky
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[route]
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layers = -6,-1
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[maxpool]
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size=2
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stride=2
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[convolutional]
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batch_normalize=1
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filters=512
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size=3
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stride=1
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pad=1
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activation=leaky
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##################################
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[convolutional]
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batch_normalize=1
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filters=256
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size=1
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stride=1
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pad=1
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activation=leaky
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[convolutional]
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batch_normalize=1
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filters=512
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size=3
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stride=1
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pad=1
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activation=leaky
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[convolutional]
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size=1
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stride=1
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pad=1
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filters=255
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activation=linear
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[yolo]
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mask = 6,7,8
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anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401
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classes=80
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num=9
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jitter=.3
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scale_x_y = 1.05
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cls_normalizer=1.0
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iou_normalizer=0.07
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iou_loss=ciou
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ignore_thresh = .7
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truth_thresh = 1
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random=0
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resize=1.5
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nms_kind=greedynms
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beta_nms=0.6
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[route]
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layers = -4
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[convolutional]
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batch_normalize=1
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filters=128
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size=1
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stride=1
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pad=1
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activation=leaky
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[upsample]
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stride=2
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[route]
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layers = -1, 23
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[convolutional]
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batch_normalize=1
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filters=256
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size=3
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stride=1
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pad=1
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activation=leaky
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[convolutional]
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size=1
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stride=1
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pad=1
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filters=255
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activation=linear
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[yolo]
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mask = 3,4,5
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anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401
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classes=80
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num=9
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jitter=.3
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scale_x_y = 1.05
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cls_normalizer=1.0
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iou_normalizer=0.07
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iou_loss=ciou
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ignore_thresh = .7
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truth_thresh = 1
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random=0
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resize=1.5
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nms_kind=greedynms
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beta_nms=0.6
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[route]
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layers = -3
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[convolutional]
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batch_normalize=1
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filters=64
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size=1
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stride=1
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pad=1
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activation=leaky
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[upsample]
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stride=2
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[route]
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layers = -1, 15
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[convolutional]
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batch_normalize=1
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filters=128
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size=3
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stride=1
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pad=1
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activation=leaky
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[convolutional]
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size=1
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stride=1
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pad=1
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filters=255
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activation=linear
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[yolo]
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mask = 0,1,2
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anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401
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classes=80
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num=9
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jitter=.3
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scale_x_y = 1.05
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cls_normalizer=1.0
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iou_normalizer=0.07
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iou_loss=ciou
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ignore_thresh = .7
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truth_thresh = 1
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random=0
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resize=1.5
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nms_kind=greedynms
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beta_nms=0.6
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