1,inputImage,Image Input,256×256×3 images
2,conv_down_1,2-D Convolution,64 4×4×3 convolutions with stride [2 2] and padding 'same'
3,lrelu_down_1,Leaky ReLU,Leaky ReLU with scale 0.2
4,conv_down_2,2-D Convolution,128 4×4×64 convolutions with stride [2 2] and padding 'same'
5,bn_down_2,Batch Normalization,Batch normalization with 128 channels
6,lrelu_down_2,Leaky ReLU,Leaky ReLU with scale 0.2
7,conv_down_3,2-D Convolution,256 4×4×128 convolutions with stride [2 2] and padding 'same'
8,bn_down_3,Batch Normalization,Batch normalization with 256 channels
9,lrelu_down_3,Leaky ReLU,Leaky ReLU with scale 0.2
10,conv_down_4,2-D Convolution,512 4×4×256 convolutions with stride [2 2] and padding 'same'
11,bn_down_4,Batch Normalization,Batch normalization with 512 channels
12,lrelu_down_4,Leaky ReLU,Leaky ReLU with scale 0.2
13,conv_down_5,2-D Convolution,512 4×4×512 convolutions with stride [2 2] and padding 'same'
14,bn_down_5,Batch Normalization,Batch normalization with 512 channels
15,lrelu_down_5,Leaky ReLU,Leaky ReLU with scale 0.2
16,conv_down_6,2-D Convolution,512 4×4×512 convolutions with stride [2 2] and padding 'same'
17,bn_down_6,Batch Normalization,Batch normalization with 512 channels
18,lrelu_down_6,Leaky ReLU,Leaky ReLU with scale 0.2
19,conv_down_7,2-D Convolution,512 4×4×512 convolutions with stride [2 2] and padding 'same'
20,bn_down_7,Batch Normalization,Batch normalization with 512 channels
21,lrelu_down_7,Leaky ReLU,Leaky ReLU with scale 0.2
22,conv_up_7,2-D Transposed Convolution,512 4×4×1024 transposed convolutions with stride [2 2] and cropping 'same'
23,bn_up_7,Batch Normalization,Batch normalization with 512 channels
24,drop_up_7,Dropout,50% dropout
25,lrelu_up_7,Leaky ReLU,Leaky ReLU with scale 0.2
26,cat_up_7,Depth concatenation,Depth concatenation of 2 inputs
27,conv_up_6,2-D Transposed Convolution,512 4×4×1024 transposed convolutions with stride [2 2] and cropping 'same'
28,bn_up_6,Batch Normalization,Batch normalization with 512 channels
29,drop_up_6,Dropout,50% dropout
30,lrelu_up_6,Leaky ReLU,Leaky ReLU with scale 0.2
31,cat_up_6,Depth concatenation,Depth concatenation of 2 inputs
32,conv_up_5,2-D Transposed Convolution,512 4×4×1024 transposed convolutions with stride [2 2] and cropping 'same'
33,bn_up_5,Batch Normalization,Batch normalization with 512 channels
34,drop_up_5,Dropout,50% dropout
35,lrelu_up_5,Leaky ReLU,Leaky ReLU with scale 0.2
36,cat_up_5,Depth concatenation,Depth concatenation of 2 inputs
37,conv_up_4,2-D Transposed Convolution,512 4×4×1024 transposed convolutions with stride [2 2] and cropping 'same'
38,bn_up_4,Batch Normalization,Batch normalization with 512 channels
39,lrelu_up_4,Leaky ReLU,Leaky ReLU with scale 0.2
40,cat_up_4,Depth concatenation,Depth concatenation of 2 inputs
41,conv_up_3,2-D Transposed Convolution,256 4×4×768 transposed convolutions with stride [2 2] and cropping 'same'
42,bn_up_3,Batch Normalization,Batch normalization with 256 channels
43,lrelu_up_3,Leaky ReLU,Leaky ReLU with scale 0.2
44,cat_up_3,Depth concatenation,Depth concatenation of 2 inputs
45,conv_up_2,2-D Transposed Convolution,128 4×4×384 transposed convolutions with stride [2 2] and cropping 'same'
46,bn_up_2,Batch Normalization,Batch normalization with 128 channels
47,lrelu_up_2,Leaky ReLU,Leaky ReLU with scale 0.2
48,cat_up_2,Depth concatenation,Depth concatenation of 2 inputs
49,conv_up_1,2-D Transposed Convolution,64 4×4×192 transposed convolutions with stride [2 2] and cropping 'same'
50,bn_up_1,Batch Normalization,Batch normalization with 64 channels
51,lrelu_up_1,Leaky ReLU,Leaky ReLU with scale 0.2
52,cat_up_1,Depth concatenation,Depth concatenation of 2 inputs
53,Output,2-D Convolution,3 1×1×67 convolutions with stride [1 1] and padding 'same'
