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yolov4-tiny.cfg
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[net] | |
# Testing | |
#batch=1 | |
#subdivisions=1 | |
# Training | |
batch=64 | |
subdivisions=1 | |
width=416 | |
height=416 | |
channels=3 | |
momentum=0.9 | |
decay=0.0005 | |
angle=0 | |
saturation = 1.5 | |
exposure = 1.5 | |
hue=.1 | |
learning_rate=0.00261 | |
burn_in=1000 | |
max_batches = 6000 | |
policy=steps | |
steps=4800,5400 | |
scales=.1,.1 | |
#weights_reject_freq=1001 | |
#ema_alpha=0.9998 | |
#equidistant_point=1000 | |
#num_sigmas_reject_badlabels=3 | |
#badlabels_rejection_percentage=0.2 | |
[convolutional] | |
batch_normalize=1 | |
filters=32 | |
size=3 | |
stride=2 | |
pad=1 | |
activation=leaky | |
[convolutional] | |
batch_normalize=1 | |
filters=64 | |
size=3 | |
stride=2 | |
pad=1 | |
activation=leaky | |
[convolutional] | |
batch_normalize=1 | |
filters=64 | |
size=3 | |
stride=1 | |
pad=1 | |
activation=leaky | |
[route] | |
layers=-1 | |
groups=2 | |
group_id=1 | |
[convolutional] | |
batch_normalize=1 | |
filters=32 | |
size=3 | |
stride=1 | |
pad=1 | |
activation=leaky | |
[convolutional] | |
batch_normalize=1 | |
filters=32 | |
size=3 | |
stride=1 | |
pad=1 | |
activation=leaky | |
[route] | |
layers = -1,-2 | |
[convolutional] | |
batch_normalize=1 | |
filters=64 | |
size=1 | |
stride=1 | |
pad=1 | |
activation=leaky | |
[route] | |
layers = -6,-1 | |
[maxpool] | |
size=2 | |
stride=2 | |
[convolutional] | |
batch_normalize=1 | |
filters=128 | |
size=3 | |
stride=1 | |
pad=1 | |
activation=leaky | |
[route] | |
layers=-1 | |
groups=2 | |
group_id=1 | |
[convolutional] | |
batch_normalize=1 | |
filters=64 | |
size=3 | |
stride=1 | |
pad=1 | |
activation=leaky | |
[convolutional] | |
batch_normalize=1 | |
filters=64 | |
size=3 | |
stride=1 | |
pad=1 | |
activation=leaky | |
[route] | |
layers = -1,-2 | |
[convolutional] | |
batch_normalize=1 | |
filters=128 | |
size=1 | |
stride=1 | |
pad=1 | |
activation=leaky | |
[route] | |
layers = -6,-1 | |
[maxpool] | |
size=2 | |
stride=2 | |
[convolutional] | |
batch_normalize=1 | |
filters=256 | |
size=3 | |
stride=1 | |
pad=1 | |
activation=leaky | |
[route] | |
layers=-1 | |
groups=2 | |
group_id=1 | |
[convolutional] | |
batch_normalize=1 | |
filters=128 | |
size=3 | |
stride=1 | |
pad=1 | |
activation=leaky | |
[convolutional] | |
batch_normalize=1 | |
filters=128 | |
size=3 | |
stride=1 | |
pad=1 | |
activation=leaky | |
[route] | |
layers = -1,-2 | |
[convolutional] | |
batch_normalize=1 | |
filters=256 | |
size=1 | |
stride=1 | |
pad=1 | |
activation=leaky | |
[route] | |
layers = -6,-1 | |
[maxpool] | |
size=2 | |
stride=2 | |
[convolutional] | |
batch_normalize=1 | |
filters=512 | |
size=3 | |
stride=1 | |
pad=1 | |
activation=leaky | |
################################## | |
[convolutional] | |
batch_normalize=1 | |
filters=256 | |
size=1 | |
stride=1 | |
pad=1 | |
activation=leaky | |
[convolutional] | |
batch_normalize=1 | |
filters=512 | |
size=3 | |
stride=1 | |
pad=1 | |
activation=leaky | |
[convolutional] | |
size=1 | |
stride=1 | |
pad=1 | |
filters=18 | |
activation=linear | |
[yolo] | |
mask = 3,4,5 | |
anchors = 10,14, 23,27, 37,58, 81,82, 135,169, 344,319 | |
classes=1 | |
num=6 | |
jitter=.3 | |
scale_x_y = 1.05 | |
cls_normalizer=1.0 | |
iou_normalizer=0.07 | |
iou_loss=ciou | |
ignore_thresh = .7 | |
truth_thresh = 1 | |
random=0 | |
resize=1.5 | |
nms_kind=greedynms | |
beta_nms=0.6 | |
#new_coords=1 | |
#scale_x_y = 2.0 | |
[route] | |
layers = -4 | |
[convolutional] | |
batch_normalize=1 | |
filters=128 | |
size=1 | |
stride=1 | |
pad=1 | |
activation=leaky | |
[upsample] | |
stride=2 | |
[route] | |
layers = -1, 23 | |
[convolutional] | |
batch_normalize=1 | |
filters=256 | |
size=3 | |
stride=1 | |
pad=1 | |
activation=leaky | |
[convolutional] | |
size=1 | |
stride=1 | |
pad=1 | |
filters=18 | |
activation=linear | |
[yolo] | |
mask = 1,2,3 | |
anchors = 10,14, 23,27, 37,58, 81,82, 135,169, 344,319 | |
classes=1 | |
num=6 | |
jitter=.3 | |
scale_x_y = 1.05 | |
cls_normalizer=1.0 | |
iou_normalizer=0.07 | |
iou_loss=ciou | |
ignore_thresh = .7 | |
truth_thresh = 1 | |
random=0 | |
resize=1.5 | |
nms_kind=greedynms | |
beta_nms=0.6 | |
#new_coords=1 | |
#scale_x_y = 2.0 |
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