[net] batch=64 subdivisions=64 height=448 width=448 channels=3 learning_rate=0.001 momentum=0.9 decay=0.0005 policy=steps steps=50, 5000 scales=10, .1 max_batches = 8000 [crop] crop_width=448 crop_height=448 flip=0 angle=0 saturation = 2 exposure = 2 [convolutional] filters=64 size=7 stride=2 pad=1 activation=ramp [convolutional] filters=192 size=3 stride=2 pad=1 activation=ramp [convolutional] filters=128 size=1 stride=1 pad=1 activation=ramp [convolutional] filters=256 size=3 stride=2 pad=1 activation=ramp [convolutional] filters=128 size=1 stride=1 pad=1 activation=ramp [convolutional] filters=256 size=3 stride=1 pad=1 activation=ramp [convolutional] filters=128 size=1 stride=1 pad=1 activation=ramp [convolutional] filters=512 size=3 stride=2 pad=1 activation=ramp [convolutional] filters=256 size=1 stride=1 pad=1 activation=ramp [convolutional] filters=512 size=3 stride=1 pad=1 activation=ramp [convolutional] filters=256 size=1 stride=1 pad=1 activation=ramp [convolutional] filters=512 size=3 stride=1 pad=1 activation=ramp [convolutional] filters=256 size=1 stride=1 pad=1 activation=ramp [convolutional] filters=512 size=3 stride=1 pad=1 activation=ramp [convolutional] filters=256 size=1 stride=1 pad=1 activation=ramp [convolutional] filters=512 size=3 stride=1 pad=1 activation=ramp [convolutional] filters=256 size=1 stride=1 pad=1 activation=ramp [convolutional] filters=1024 size=3 stride=2 pad=1 activation=ramp [convolutional] filters=512 size=1 stride=1 pad=1 activation=ramp [convolutional] filters=1024 size=3 stride=1 pad=1 activation=ramp [convolutional] size=3 stride=1 pad=1 filters=1024 activation=ramp [convolutional] size=3 stride=2 pad=1 filters=1024 activation=ramp [convolutional] size=3 stride=1 pad=1 filters=1024 activation=ramp [convolutional] size=3 stride=1 pad=1 filters=1024 activation=ramp [connected] output=4096 activation=ramp [dropout] probability=.5 [connected] output=1225 activation=logistic [detection] classes=20 coords=4 rescore=0 joint=0 objectness=1 background=0