Datasets
Models
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[afa31e]:
/
unet_structure.xlsx
| # | __________________________________________________________________________________________________ |
|---|---|
| 1 | Layer (type) Output Shape Param # Connected to |
| 2 | ================================================================================================== |
| 3 | input_1 (InputLayer) [(None, 512, 512, 1)] 0 [] |
| 4 | |
| 5 | conv2d (Conv2D) (None, 512, 512, 64) 640 ['input_1[0][0]'] |
| 6 | |
| 7 | conv2d_1 (Conv2D) (None, 512, 512, 64) 36928 ['conv2d[0][0]'] |
| 8 | |
| 9 | max_pooling2d (MaxPooling2D) (None, 256, 256, 64) 0 ['conv2d_1[0][0]'] |
| 10 | |
| 11 | conv2d_2 (Conv2D) (None, 256, 256, 128) 73856 ['max_pooling2d[0][0]'] |
| 12 | |
| 13 | conv2d_3 (Conv2D) (None, 256, 256, 128) 147584 ['conv2d_2[0][0]'] |
| 14 | |
| 15 | max_pooling2d_1 (MaxPooling2D) (None, 128, 128, 128) 0 ['conv2d_3[0][0]'] |
| 16 | |
| 17 | conv2d_4 (Conv2D) (None, 128, 128, 256) 295168 ['max_pooling2d_1[0][0]'] |
| 18 | |
| 19 | conv2d_5 (Conv2D) (None, 128, 128, 256) 590080 ['conv2d_4[0][0]'] |
| 20 | |
| 21 | max_pooling2d_2 (MaxPooling2D) (None, 64, 64, 256) 0 ['conv2d_5[0][0]'] |
| 22 | |
| 23 | conv2d_6 (Conv2D) (None, 64, 64, 512) 1180160 ['max_pooling2d_2[0][0]'] |
| 24 | |
| 25 | conv2d_7 (Conv2D) (None, 64, 64, 512) 2359808 ['conv2d_6[0][0]'] |
| 26 | |
| 27 | max_pooling2d_3 (MaxPooling2D) (None, 32, 32, 512) 0 ['conv2d_7[0][0]'] |
| 28 | |
| 29 | conv2d_8 (Conv2D) (None, 32, 32, 1024) 4719616 ['max_pooling2d_3[0][0]'] |
| 30 | |
| 31 | conv2d_9 (Conv2D) (None, 32, 32, 1024) 9438208 ['conv2d_8[0][0]'] |
| 32 | |
| 33 | up_sampling2d (UpSampling2D) (None, 64, 64, 1024) 0 ['conv2d_9[0][0]'] |
| 34 | |
| 35 | concatenate (Concatenate) (None, 64, 64, 1536) 0 ['up_sampling2d[0][0]', |
| 36 | 'conv2d_7[0][0]'] |
| 37 | |
| 38 | conv2d_10 (Conv2D) (None, 64, 64, 512) 7078400 ['concatenate[0][0]'] |
| 39 | |
| 40 | conv2d_11 (Conv2D) (None, 64, 64, 512) 2359808 ['conv2d_10[0][0]'] |
| 41 | |
| 42 | up_sampling2d_1 (UpSampling2D) (None, 128, 128, 512) 0 ['conv2d_11[0][0]'] |
| 43 | |
| 44 | concatenate_1 (Concatenate) (None, 128, 128, 768) 0 ['up_sampling2d_1[0][0]', |
| 45 | 'conv2d_5[0][0]'] |
| 46 | |
| 47 | conv2d_12 (Conv2D) (None, 128, 128, 256) 1769728 ['concatenate_1[0][0]'] |
| 48 | |
| 49 | conv2d_13 (Conv2D) (None, 128, 128, 256) 590080 ['conv2d_12[0][0]'] |
| 50 | |
| 51 | up_sampling2d_2 (UpSampling2D) (None, 256, 256, 256) 0 ['conv2d_13[0][0]'] |
| 52 | |
| 53 | concatenate_2 (Concatenate) (None, 256, 256, 384) 0 ['up_sampling2d_2[0][0]', |
| 54 | 'conv2d_3[0][0]'] |
| 55 | |
| 56 | conv2d_14 (Conv2D) (None, 256, 256, 128) 442496 ['concatenate_2[0][0]'] |
| 57 | |
| 58 | conv2d_15 (Conv2D) (None, 256, 256, 128) 147584 ['conv2d_14[0][0]'] |
| 59 | |
| 60 | up_sampling2d_3 (UpSampling2D) (None, 512, 512, 128) 0 ['conv2d_15[0][0]'] |
| 61 | |
| 62 | concatenate_3 (Concatenate) (None, 512, 512, 192) 0 ['up_sampling2d_3[0][0]', |
| 63 | 'conv2d_1[0][0]'] |
| 64 | |
| 65 | conv2d_16 (Conv2D) (None, 512, 512, 64) 110656 ['concatenate_3[0][0]'] |
| 66 | |
| 67 | conv2d_17 (Conv2D) (None, 512, 512, 64) 36928 ['conv2d_16[0][0]'] |
| 68 | |
| 69 | conv2d_18 (Conv2D) (None, 512, 512, 1) 65 ['conv2d_17[0][0]'] |
| 70 | |
| 71 | ================================================================================================== |
| 72 | Total params: 31,377,793 |
| 73 | Trainable params: 31,377,793 |
| 74 | Non-trainable params: 0 |
| 75 | __________________________________________________________________________________________________ |
| 76 | nan |