basic版本的yolo,在yolov3版本上增加人体跟踪
xuepengqiang
2020-05-26 5966f2b095841627d62daac0159e81f83544b85c
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[net]
subdivisions=1
inputs=256
batch = 1
momentum=0.9
decay=0.001
time_steps=1
learning_rate=0.5
 
policy=poly
power=4
max_batches=2000
 
[gru]
batch_normalize=1
output = 1024
 
[gru]
batch_normalize=1
output = 1024
 
[gru]
batch_normalize=1
output = 1024
 
[connected]
output=256
activation=linear
 
[softmax]
 
[cost]
type=sse