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resunet_report.txt
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resunet_report.txt
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Model: "model"
__________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
==================================================================================================
input_1 (InputLayer) [(None, 512, 512, 3) 0
__________________________________________________________________________________________________
conv2d (Conv2D) (None, 512, 512, 6) 78 input_1[0][0]
__________________________________________________________________________________________________
batch_normalization (BatchNorma (None, 512, 512, 6) 24 conv2d[0][0]
__________________________________________________________________________________________________
conv2d_2 (Conv2D) (None, 512, 512, 6) 24 input_1[0][0]
__________________________________________________________________________________________________
activation (Activation) (None, 512, 512, 6) 0 batch_normalization[0][0]
__________________________________________________________________________________________________
batch_normalization_1 (BatchNor (None, 512, 512, 6) 24 conv2d_2[0][0]
__________________________________________________________________________________________________
conv2d_1 (Conv2D) (None, 512, 512, 6) 150 activation[0][0]
__________________________________________________________________________________________________
activation_1 (Activation) (None, 512, 512, 6) 0 batch_normalization_1[0][0]
__________________________________________________________________________________________________
add (Add) (None, 512, 512, 6) 0 conv2d_1[0][0]
activation_1[0][0]
__________________________________________________________________________________________________
dropout (Dropout) (None, 512, 512, 6) 0 add[0][0]
__________________________________________________________________________________________________
batch_normalization_2 (BatchNor (None, 512, 512, 6) 24 dropout[0][0]
__________________________________________________________________________________________________
activation_2 (Activation) (None, 512, 512, 6) 0 batch_normalization_2[0][0]
__________________________________________________________________________________________________
conv2d_3 (Conv2D) (None, 256, 256, 12) 3540 activation_2[0][0]
__________________________________________________________________________________________________
dropout_1 (Dropout) (None, 256, 256, 12) 0 conv2d_3[0][0]
__________________________________________________________________________________________________
conv2d_5 (Conv2D) (None, 256, 256, 12) 84 add[0][0]
__________________________________________________________________________________________________
batch_normalization_3 (BatchNor (None, 256, 256, 12) 48 dropout_1[0][0]
__________________________________________________________________________________________________
batch_normalization_4 (BatchNor (None, 256, 256, 12) 48 conv2d_5[0][0]
__________________________________________________________________________________________________
activation_3 (Activation) (None, 256, 256, 12) 0 batch_normalization_3[0][0]
__________________________________________________________________________________________________
activation_4 (Activation) (None, 256, 256, 12) 0 batch_normalization_4[0][0]
__________________________________________________________________________________________________
conv2d_4 (Conv2D) (None, 256, 256, 12) 7068 activation_3[0][0]
__________________________________________________________________________________________________
add_1 (Add) (None, 256, 256, 12) 0 activation_4[0][0]
conv2d_4[0][0]
__________________________________________________________________________________________________
dropout_2 (Dropout) (None, 256, 256, 12) 0 add_1[0][0]
__________________________________________________________________________________________________
batch_normalization_5 (BatchNor (None, 256, 256, 12) 48 dropout_2[0][0]
__________________________________________________________________________________________________
activation_5 (Activation) (None, 256, 256, 12) 0 batch_normalization_5[0][0]
__________________________________________________________________________________________________
conv2d_6 (Conv2D) (None, 128, 128, 24) 14136 activation_5[0][0]
__________________________________________________________________________________________________
dropout_3 (Dropout) (None, 128, 128, 24) 0 conv2d_6[0][0]
__________________________________________________________________________________________________
conv2d_8 (Conv2D) (None, 128, 128, 24) 312 add_1[0][0]
__________________________________________________________________________________________________
batch_normalization_6 (BatchNor (None, 128, 128, 24) 96 dropout_3[0][0]
__________________________________________________________________________________________________
batch_normalization_7 (BatchNor (None, 128, 128, 24) 96 conv2d_8[0][0]
__________________________________________________________________________________________________
activation_6 (Activation) (None, 128, 128, 24) 0 batch_normalization_6[0][0]
__________________________________________________________________________________________________
activation_7 (Activation) (None, 128, 128, 24) 0 batch_normalization_7[0][0]
__________________________________________________________________________________________________
conv2d_7 (Conv2D) (None, 128, 128, 24) 28248 activation_6[0][0]
__________________________________________________________________________________________________
add_2 (Add) (None, 128, 128, 24) 0 activation_7[0][0]
conv2d_7[0][0]
__________________________________________________________________________________________________
dropout_4 (Dropout) (None, 128, 128, 24) 0 add_2[0][0]
__________________________________________________________________________________________________
batch_normalization_8 (BatchNor (None, 128, 128, 24) 96 dropout_4[0][0]
__________________________________________________________________________________________________
activation_8 (Activation) (None, 128, 128, 24) 0 batch_normalization_8[0][0]
__________________________________________________________________________________________________
conv2d_9 (Conv2D) (None, 64, 64, 48) 56496 activation_8[0][0]
__________________________________________________________________________________________________
dropout_5 (Dropout) (None, 64, 64, 48) 0 conv2d_9[0][0]
__________________________________________________________________________________________________
conv2d_11 (Conv2D) (None, 64, 64, 48) 1200 add_2[0][0]
__________________________________________________________________________________________________
batch_normalization_9 (BatchNor (None, 64, 64, 48) 192 dropout_5[0][0]
__________________________________________________________________________________________________
batch_normalization_10 (BatchNo (None, 64, 64, 48) 192 conv2d_11[0][0]
__________________________________________________________________________________________________
activation_9 (Activation) (None, 64, 64, 48) 0 batch_normalization_9[0][0]
__________________________________________________________________________________________________
activation_10 (Activation) (None, 64, 64, 48) 0 batch_normalization_10[0][0]
__________________________________________________________________________________________________
conv2d_10 (Conv2D) (None, 64, 64, 48) 112944 activation_9[0][0]
__________________________________________________________________________________________________
add_3 (Add) (None, 64, 64, 48) 0 activation_10[0][0]
conv2d_10[0][0]
__________________________________________________________________________________________________
dropout_6 (Dropout) (None, 64, 64, 48) 0 add_3[0][0]
__________________________________________________________________________________________________
batch_normalization_11 (BatchNo (None, 64, 64, 48) 192 dropout_6[0][0]
__________________________________________________________________________________________________
activation_11 (Activation) (None, 64, 64, 48) 0 batch_normalization_11[0][0]
__________________________________________________________________________________________________
conv2d_12 (Conv2D) (None, 32, 32, 96) 225888 activation_11[0][0]
__________________________________________________________________________________________________
dropout_7 (Dropout) (None, 32, 32, 96) 0 conv2d_12[0][0]
__________________________________________________________________________________________________
conv2d_14 (Conv2D) (None, 32, 32, 96) 4704 add_3[0][0]
__________________________________________________________________________________________________
batch_normalization_12 (BatchNo (None, 32, 32, 96) 384 dropout_7[0][0]
__________________________________________________________________________________________________
batch_normalization_13 (BatchNo (None, 32, 32, 96) 384 conv2d_14[0][0]
__________________________________________________________________________________________________
activation_12 (Activation) (None, 32, 32, 96) 0 batch_normalization_12[0][0]
__________________________________________________________________________________________________
activation_13 (Activation) (None, 32, 32, 96) 0 batch_normalization_13[0][0]
__________________________________________________________________________________________________
conv2d_13 (Conv2D) (None, 32, 32, 96) 451680 activation_12[0][0]
__________________________________________________________________________________________________
add_4 (Add) (None, 32, 32, 96) 0 activation_13[0][0]
conv2d_13[0][0]
__________________________________________________________________________________________________
dropout_8 (Dropout) (None, 32, 32, 96) 0 add_4[0][0]
__________________________________________________________________________________________________
batch_normalization_14 (BatchNo (None, 32, 32, 96) 384 dropout_8[0][0]
__________________________________________________________________________________________________
activation_14 (Activation) (None, 32, 32, 96) 0 batch_normalization_14[0][0]
__________________________________________________________________________________________________
conv2d_15 (Conv2D) (None, 32, 32, 96) 451680 activation_14[0][0]
__________________________________________________________________________________________________
dropout_9 (Dropout) (None, 32, 32, 96) 0 conv2d_15[0][0]
__________________________________________________________________________________________________
batch_normalization_15 (BatchNo (None, 32, 32, 96) 384 dropout_9[0][0]
__________________________________________________________________________________________________
activation_15 (Activation) (None, 32, 32, 96) 0 batch_normalization_15[0][0]
__________________________________________________________________________________________________
conv2d_16 (Conv2D) (None, 32, 32, 96) 451680 activation_15[0][0]
__________________________________________________________________________________________________
up_sampling2d (UpSampling2D) (None, 64, 64, 96) 0 conv2d_16[0][0]
__________________________________________________________________________________________________
concatenate (Concatenate) (None, 64, 64, 144) 0 up_sampling2d[0][0]
add_3[0][0]
__________________________________________________________________________________________________
batch_normalization_16 (BatchNo (None, 64, 64, 144) 576 concatenate[0][0]
__________________________________________________________________________________________________
activation_16 (Activation) (None, 64, 64, 144) 0 batch_normalization_16[0][0]
__________________________________________________________________________________________________
conv2d_17 (Conv2D) (None, 64, 64, 96) 677472 activation_16[0][0]
__________________________________________________________________________________________________
conv2d_19 (Conv2D) (None, 64, 64, 96) 13920 concatenate[0][0]
__________________________________________________________________________________________________
batch_normalization_17 (BatchNo (None, 64, 64, 96) 384 conv2d_17[0][0]
__________________________________________________________________________________________________
batch_normalization_18 (BatchNo (None, 64, 64, 96) 384 conv2d_19[0][0]
__________________________________________________________________________________________________
activation_17 (Activation) (None, 64, 64, 96) 0 batch_normalization_17[0][0]
__________________________________________________________________________________________________
activation_18 (Activation) (None, 64, 64, 96) 0 batch_normalization_18[0][0]
__________________________________________________________________________________________________
conv2d_18 (Conv2D) (None, 64, 64, 96) 451680 activation_17[0][0]
__________________________________________________________________________________________________
add_5 (Add) (None, 64, 64, 96) 0 activation_18[0][0]
conv2d_18[0][0]
__________________________________________________________________________________________________
up_sampling2d_1 (UpSampling2D) (None, 128, 128, 96) 0 add_5[0][0]
__________________________________________________________________________________________________
concatenate_1 (Concatenate) (None, 128, 128, 120 0 up_sampling2d_1[0][0]
add_2[0][0]
__________________________________________________________________________________________________
batch_normalization_19 (BatchNo (None, 128, 128, 120 480 concatenate_1[0][0]
__________________________________________________________________________________________________
activation_19 (Activation) (None, 128, 128, 120 0 batch_normalization_19[0][0]
__________________________________________________________________________________________________
conv2d_20 (Conv2D) (None, 128, 128, 48) 282288 activation_19[0][0]
__________________________________________________________________________________________________
conv2d_22 (Conv2D) (None, 128, 128, 48) 5808 concatenate_1[0][0]
__________________________________________________________________________________________________
batch_normalization_20 (BatchNo (None, 128, 128, 48) 192 conv2d_20[0][0]
__________________________________________________________________________________________________
batch_normalization_21 (BatchNo (None, 128, 128, 48) 192 conv2d_22[0][0]
__________________________________________________________________________________________________
activation_20 (Activation) (None, 128, 128, 48) 0 batch_normalization_20[0][0]
__________________________________________________________________________________________________
activation_21 (Activation) (None, 128, 128, 48) 0 batch_normalization_21[0][0]
__________________________________________________________________________________________________
conv2d_21 (Conv2D) (None, 128, 128, 48) 112944 activation_20[0][0]
__________________________________________________________________________________________________
add_6 (Add) (None, 128, 128, 48) 0 activation_21[0][0]
conv2d_21[0][0]
__________________________________________________________________________________________________
up_sampling2d_2 (UpSampling2D) (None, 256, 256, 48) 0 add_6[0][0]
__________________________________________________________________________________________________
concatenate_2 (Concatenate) (None, 256, 256, 60) 0 up_sampling2d_2[0][0]
add_1[0][0]
__________________________________________________________________________________________________
batch_normalization_22 (BatchNo (None, 256, 256, 60) 240 concatenate_2[0][0]
__________________________________________________________________________________________________
activation_22 (Activation) (None, 256, 256, 60) 0 batch_normalization_22[0][0]
__________________________________________________________________________________________________
conv2d_23 (Conv2D) (None, 256, 256, 24) 70584 activation_22[0][0]
__________________________________________________________________________________________________
conv2d_25 (Conv2D) (None, 256, 256, 24) 1464 concatenate_2[0][0]
__________________________________________________________________________________________________
batch_normalization_23 (BatchNo (None, 256, 256, 24) 96 conv2d_23[0][0]
__________________________________________________________________________________________________
batch_normalization_24 (BatchNo (None, 256, 256, 24) 96 conv2d_25[0][0]
__________________________________________________________________________________________________
activation_23 (Activation) (None, 256, 256, 24) 0 batch_normalization_23[0][0]
__________________________________________________________________________________________________
activation_24 (Activation) (None, 256, 256, 24) 0 batch_normalization_24[0][0]
__________________________________________________________________________________________________
conv2d_24 (Conv2D) (None, 256, 256, 24) 28248 activation_23[0][0]
__________________________________________________________________________________________________
add_7 (Add) (None, 256, 256, 24) 0 activation_24[0][0]
conv2d_24[0][0]
__________________________________________________________________________________________________
up_sampling2d_3 (UpSampling2D) (None, 512, 512, 24) 0 add_7[0][0]
__________________________________________________________________________________________________
concatenate_3 (Concatenate) (None, 512, 512, 30) 0 up_sampling2d_3[0][0]
add[0][0]
__________________________________________________________________________________________________
batch_normalization_25 (BatchNo (None, 512, 512, 30) 120 concatenate_3[0][0]
__________________________________________________________________________________________________
activation_25 (Activation) (None, 512, 512, 30) 0 batch_normalization_25[0][0]
__________________________________________________________________________________________________
conv2d_26 (Conv2D) (None, 512, 512, 12) 17652 activation_25[0][0]
__________________________________________________________________________________________________
conv2d_28 (Conv2D) (None, 512, 512, 12) 372 concatenate_3[0][0]
__________________________________________________________________________________________________
batch_normalization_26 (BatchNo (None, 512, 512, 12) 48 conv2d_26[0][0]
__________________________________________________________________________________________________
batch_normalization_27 (BatchNo (None, 512, 512, 12) 48 conv2d_28[0][0]
__________________________________________________________________________________________________
activation_26 (Activation) (None, 512, 512, 12) 0 batch_normalization_26[0][0]
__________________________________________________________________________________________________
activation_27 (Activation) (None, 512, 512, 12) 0 batch_normalization_27[0][0]
__________________________________________________________________________________________________
conv2d_27 (Conv2D) (None, 512, 512, 12) 7068 activation_26[0][0]
__________________________________________________________________________________________________
add_8 (Add) (None, 512, 512, 12) 0 activation_27[0][0]
conv2d_27[0][0]
__________________________________________________________________________________________________
conv2d_29 (Conv2D) (None, 512, 512, 2) 26 add_8[0][0]
==================================================================================================
Total params: 3,484,910
Trainable params: 3,482,174
Non-trainable params: 2,736
__________________________________________________________________________________________________