Table 1.

DarkNet53 layer architecture.

Layer Type	Filters	Filter Size	Stride Size	Repeat	Output Size
Input	-	-	-	-	$224\times 256$
Convolutional	32	$3\times 3$	1	1	$256\times 256$
Convolutional	64	$3\times 3$	2	1	$128\times 128$
Convolutional	32	$1\times 1$	1	1
Convolutional	64	$3\times 3$	1
Residual					$128\times 128$
Convolutional	128	$3\times 3$	2	1	$64\times 64$
Convolutional	64	$1\times 1$	1	2
Convolutional	128	$3\times 3$	1
Residual					$64\times 64$
Convolutional	256	$3\times 3$	2	1	$32\times 32$
Convolutional	128	$1\times 1$	1	8
Convolutional	256	$3\times 3$	1
Residual					$32\times 32$
Convolutional	512	$3\times 3$	2	1	$16\times 16$
Convolutional	256	$1\times 1$	1	8
Convolutional	512	$3\times 3$	1
Residual					$16\times 16$
Convolutional	1024	$3\times 3$	2	1	$8\times 8$
Convolutional	512	$1\times 1$	1	4
Convolutional	1024	$3\times 3$	1
Residual					$8\times 8$
GlobalAvgPool
Fully Connected	1000
Softmax