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model.py
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model.py
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#!/usr/bin/python3
# __*__ coding: utf-8 __*__
'''
@Author: SimonWang00
@Os：Windows 10 x64
@Contact: simon_wang00@163.com
@Software: PY PyCharm
@File: settings.py
@Time: 2020/12/15 15:15
'''
# Copyright 2020 The SimonWang00. All Rights Reserved.
#
# @Desc:
# 1).build fpn + resnet model;
# 2).define dice loss;
# 3).define model train loss;
# 4).define total loss;
# 5).define average_gradients to update our weight;
# ==============================================================================
# LINT.IfChange
"""build FPN + ResNet model"""
'''
This model build by resnet50, using resnet FLOPS is: 48 Million
Model: "PseNet"
__________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
==================================================================================================
input_images (InputLayer) [(None, None, None, 0
__________________________________________________________________________________________________
zero_padding2d (ZeroPadding2D) (None, None, None, 3 0 input_images[0][0]
__________________________________________________________________________________________________
conv1 (Conv2D) (None, None, None, 6 9472 zero_padding2d[0][0]
__________________________________________________________________________________________________
bn_conv1 (BatchNormalization) (None, None, None, 6 256 conv1[0][0]
__________________________________________________________________________________________________
activation (Activation) (None, None, None, 6 0 bn_conv1[0][0]
__________________________________________________________________________________________________
max_pooling2d (MaxPooling2D) (None, None, None, 6 0 activation[0][0]
__________________________________________________________________________________________________
res2a_branch2a (Conv2D) (None, None, None, 6 4096 max_pooling2d[0][0]
__________________________________________________________________________________________________
bn2a_branch2a (BatchNormalizati (None, None, None, 6 256 res2a_branch2a[0][0]
__________________________________________________________________________________________________
activation_1 (Activation) (None, None, None, 6 0 bn2a_branch2a[0][0]
__________________________________________________________________________________________________
res2a_branch2b (Conv2D) (None, None, None, 6 36864 activation_1[0][0]
__________________________________________________________________________________________________
bn2a_branch2b (BatchNormalizati (None, None, None, 6 256 res2a_branch2b[0][0]
__________________________________________________________________________________________________
activation_2 (Activation) (None, None, None, 6 0 bn2a_branch2b[0][0]
__________________________________________________________________________________________________
res2a_branch2c (Conv2D) (None, None, None, 2 16384 activation_2[0][0]
__________________________________________________________________________________________________
res2a_branch1 (Conv2D) (None, None, None, 2 16384 max_pooling2d[0][0]
__________________________________________________________________________________________________
bn2a_branch2c (BatchNormalizati (None, None, None, 2 1024 res2a_branch2c[0][0]
__________________________________________________________________________________________________
bn2a_branch1 (BatchNormalizatio (None, None, None, 2 1024 res2a_branch1[0][0]
__________________________________________________________________________________________________
add (Add) (None, None, None, 2 0 bn2a_branch2c[0][0]
bn2a_branch1[0][0]
__________________________________________________________________________________________________
res2a_out (Activation) (None, None, None, 2 0 add[0][0]
__________________________________________________________________________________________________
res2b_branch2a (Conv2D) (None, None, None, 6 16384 res2a_out[0][0]
__________________________________________________________________________________________________
bn2b_branch2a (BatchNormalizati (None, None, None, 6 256 res2b_branch2a[0][0]
__________________________________________________________________________________________________
activation_3 (Activation) (None, None, None, 6 0 bn2b_branch2a[0][0]
__________________________________________________________________________________________________
res2b_branch2b (Conv2D) (None, None, None, 6 36864 activation_3[0][0]
__________________________________________________________________________________________________
bn2b_branch2b (BatchNormalizati (None, None, None, 6 256 res2b_branch2b[0][0]
__________________________________________________________________________________________________
activation_4 (Activation) (None, None, None, 6 0 bn2b_branch2b[0][0]
__________________________________________________________________________________________________
res2b_branch2c (Conv2D) (None, None, None, 2 16384 activation_4[0][0]
__________________________________________________________________________________________________
bn2b_branch2c (BatchNormalizati (None, None, None, 2 1024 res2b_branch2c[0][0]
__________________________________________________________________________________________________
add_1 (Add) (None, None, None, 2 0 bn2b_branch2c[0][0]
res2a_out[0][0]
__________________________________________________________________________________________________
res2b_out (Activation) (None, None, None, 2 0 add_1[0][0]
__________________________________________________________________________________________________
res2c_branch2a (Conv2D) (None, None, None, 6 16384 res2b_out[0][0]
__________________________________________________________________________________________________
bn2c_branch2a (BatchNormalizati (None, None, None, 6 256 res2c_branch2a[0][0]
__________________________________________________________________________________________________
activation_5 (Activation) (None, None, None, 6 0 bn2c_branch2a[0][0]
__________________________________________________________________________________________________
res2c_branch2b (Conv2D) (None, None, None, 6 36864 activation_5[0][0]
__________________________________________________________________________________________________
bn2c_branch2b (BatchNormalizati (None, None, None, 6 256 res2c_branch2b[0][0]
__________________________________________________________________________________________________
activation_6 (Activation) (None, None, None, 6 0 bn2c_branch2b[0][0]
__________________________________________________________________________________________________
res2c_branch2c (Conv2D) (None, None, None, 2 16384 activation_6[0][0]
__________________________________________________________________________________________________
bn2c_branch2c (BatchNormalizati (None, None, None, 2 1024 res2c_branch2c[0][0]
__________________________________________________________________________________________________
add_2 (Add) (None, None, None, 2 0 bn2c_branch2c[0][0]
res2b_out[0][0]
__________________________________________________________________________________________________
res2c_out (Activation) (None, None, None, 2 0 add_2[0][0]
__________________________________________________________________________________________________
res3a_branch2a (Conv2D) (None, None, None, 1 32768 res2c_out[0][0]
__________________________________________________________________________________________________
bn3a_branch2a (BatchNormalizati (None, None, None, 1 512 res3a_branch2a[0][0]
__________________________________________________________________________________________________
activation_7 (Activation) (None, None, None, 1 0 bn3a_branch2a[0][0]
__________________________________________________________________________________________________
res3a_branch2b (Conv2D) (None, None, None, 1 147456 activation_7[0][0]
__________________________________________________________________________________________________
bn3a_branch2b (BatchNormalizati (None, None, None, 1 512 res3a_branch2b[0][0]
__________________________________________________________________________________________________
activation_8 (Activation) (None, None, None, 1 0 bn3a_branch2b[0][0]
__________________________________________________________________________________________________
res3a_branch2c (Conv2D) (None, None, None, 5 65536 activation_8[0][0]
__________________________________________________________________________________________________
res3a_branch1 (Conv2D) (None, None, None, 5 131072 res2c_out[0][0]
__________________________________________________________________________________________________
bn3a_branch2c (BatchNormalizati (None, None, None, 5 2048 res3a_branch2c[0][0]
__________________________________________________________________________________________________
bn3a_branch1 (BatchNormalizatio (None, None, None, 5 2048 res3a_branch1[0][0]
__________________________________________________________________________________________________
add_3 (Add) (None, None, None, 5 0 bn3a_branch2c[0][0]
bn3a_branch1[0][0]
__________________________________________________________________________________________________
res3a_out (Activation) (None, None, None, 5 0 add_3[0][0]
__________________________________________________________________________________________________
res3b_branch2a (Conv2D) (None, None, None, 1 65536 res3a_out[0][0]
__________________________________________________________________________________________________
bn3b_branch2a (BatchNormalizati (None, None, None, 1 512 res3b_branch2a[0][0]
__________________________________________________________________________________________________
activation_9 (Activation) (None, None, None, 1 0 bn3b_branch2a[0][0]
__________________________________________________________________________________________________
res3b_branch2b (Conv2D) (None, None, None, 1 147456 activation_9[0][0]
__________________________________________________________________________________________________
bn3b_branch2b (BatchNormalizati (None, None, None, 1 512 res3b_branch2b[0][0]
__________________________________________________________________________________________________
activation_10 (Activation) (None, None, None, 1 0 bn3b_branch2b[0][0]
__________________________________________________________________________________________________
res3b_branch2c (Conv2D) (None, None, None, 5 65536 activation_10[0][0]
__________________________________________________________________________________________________
bn3b_branch2c (BatchNormalizati (None, None, None, 5 2048 res3b_branch2c[0][0]
__________________________________________________________________________________________________
add_4 (Add) (None, None, None, 5 0 bn3b_branch2c[0][0]
res3a_out[0][0]
__________________________________________________________________________________________________
res3b_out (Activation) (None, None, None, 5 0 add_4[0][0]
__________________________________________________________________________________________________
res3c_branch2a (Conv2D) (None, None, None, 1 65536 res3b_out[0][0]
__________________________________________________________________________________________________
bn3c_branch2a (BatchNormalizati (None, None, None, 1 512 res3c_branch2a[0][0]
__________________________________________________________________________________________________
activation_11 (Activation) (None, None, None, 1 0 bn3c_branch2a[0][0]
__________________________________________________________________________________________________
res3c_branch2b (Conv2D) (None, None, None, 1 147456 activation_11[0][0]
__________________________________________________________________________________________________
bn3c_branch2b (BatchNormalizati (None, None, None, 1 512 res3c_branch2b[0][0]
__________________________________________________________________________________________________
activation_12 (Activation) (None, None, None, 1 0 bn3c_branch2b[0][0]
__________________________________________________________________________________________________
res3c_branch2c (Conv2D) (None, None, None, 5 65536 activation_12[0][0]
__________________________________________________________________________________________________
bn3c_branch2c (BatchNormalizati (None, None, None, 5 2048 res3c_branch2c[0][0]
__________________________________________________________________________________________________
add_5 (Add) (None, None, None, 5 0 bn3c_branch2c[0][0]
res3b_out[0][0]
__________________________________________________________________________________________________
res3c_out (Activation) (None, None, None, 5 0 add_5[0][0]
__________________________________________________________________________________________________
res3d_branch2a (Conv2D) (None, None, None, 1 65536 res3c_out[0][0]
__________________________________________________________________________________________________
bn3d_branch2a (BatchNormalizati (None, None, None, 1 512 res3d_branch2a[0][0]
__________________________________________________________________________________________________
activation_13 (Activation) (None, None, None, 1 0 bn3d_branch2a[0][0]
__________________________________________________________________________________________________
res3d_branch2b (Conv2D) (None, None, None, 1 147456 activation_13[0][0]
__________________________________________________________________________________________________
bn3d_branch2b (BatchNormalizati (None, None, None, 1 512 res3d_branch2b[0][0]
__________________________________________________________________________________________________
activation_14 (Activation) (None, None, None, 1 0 bn3d_branch2b[0][0]
__________________________________________________________________________________________________
res3d_branch2c (Conv2D) (None, None, None, 5 65536 activation_14[0][0]
__________________________________________________________________________________________________
bn3d_branch2c (BatchNormalizati (None, None, None, 5 2048 res3d_branch2c[0][0]
__________________________________________________________________________________________________
add_6 (Add) (None, None, None, 5 0 bn3d_branch2c[0][0]
res3c_out[0][0]
__________________________________________________________________________________________________
res3d_out (Activation) (None, None, None, 5 0 add_6[0][0]
__________________________________________________________________________________________________
res4a_branch2a (Conv2D) (None, None, None, 2 131072 res3d_out[0][0]
__________________________________________________________________________________________________
bn4a_branch2a (BatchNormalizati (None, None, None, 2 1024 res4a_branch2a[0][0]
__________________________________________________________________________________________________
activation_15 (Activation) (None, None, None, 2 0 bn4a_branch2a[0][0]
__________________________________________________________________________________________________
res4a_branch2b (Conv2D) (None, None, None, 2 589824 activation_15[0][0]
__________________________________________________________________________________________________
bn4a_branch2b (BatchNormalizati (None, None, None, 2 1024 res4a_branch2b[0][0]
__________________________________________________________________________________________________
activation_16 (Activation) (None, None, None, 2 0 bn4a_branch2b[0][0]
__________________________________________________________________________________________________
res4a_branch2c (Conv2D) (None, None, None, 1 262144 activation_16[0][0]
__________________________________________________________________________________________________
res4a_branch1 (Conv2D) (None, None, None, 1 524288 res3d_out[0][0]
__________________________________________________________________________________________________
bn4a_branch2c (BatchNormalizati (None, None, None, 1 4096 res4a_branch2c[0][0]
__________________________________________________________________________________________________
bn4a_branch1 (BatchNormalizatio (None, None, None, 1 4096 res4a_branch1[0][0]
__________________________________________________________________________________________________
add_7 (Add) (None, None, None, 1 0 bn4a_branch2c[0][0]
bn4a_branch1[0][0]
__________________________________________________________________________________________________
res4a_out (Activation) (None, None, None, 1 0 add_7[0][0]
__________________________________________________________________________________________________
res4b_branch2a (Conv2D) (None, None, None, 2 262144 res4a_out[0][0]
__________________________________________________________________________________________________
bn4b_branch2a (BatchNormalizati (None, None, None, 2 1024 res4b_branch2a[0][0]
__________________________________________________________________________________________________
activation_17 (Activation) (None, None, None, 2 0 bn4b_branch2a[0][0]
__________________________________________________________________________________________________
res4b_branch2b (Conv2D) (None, None, None, 2 589824 activation_17[0][0]
__________________________________________________________________________________________________
bn4b_branch2b (BatchNormalizati (None, None, None, 2 1024 res4b_branch2b[0][0]
__________________________________________________________________________________________________
activation_18 (Activation) (None, None, None, 2 0 bn4b_branch2b[0][0]
__________________________________________________________________________________________________
res4b_branch2c (Conv2D) (None, None, None, 1 262144 activation_18[0][0]
__________________________________________________________________________________________________
bn4b_branch2c (BatchNormalizati (None, None, None, 1 4096 res4b_branch2c[0][0]
__________________________________________________________________________________________________
add_8 (Add) (None, None, None, 1 0 bn4b_branch2c[0][0]
res4a_out[0][0]
__________________________________________________________________________________________________
res4b_out (Activation) (None, None, None, 1 0 add_8[0][0]
__________________________________________________________________________________________________
res4c_branch2a (Conv2D) (None, None, None, 2 262144 res4b_out[0][0]
__________________________________________________________________________________________________
bn4c_branch2a (BatchNormalizati (None, None, None, 2 1024 res4c_branch2a[0][0]
__________________________________________________________________________________________________
activation_19 (Activation) (None, None, None, 2 0 bn4c_branch2a[0][0]
__________________________________________________________________________________________________
res4c_branch2b (Conv2D) (None, None, None, 2 589824 activation_19[0][0]
__________________________________________________________________________________________________
bn4c_branch2b (BatchNormalizati (None, None, None, 2 1024 res4c_branch2b[0][0]
__________________________________________________________________________________________________
activation_20 (Activation) (None, None, None, 2 0 bn4c_branch2b[0][0]
__________________________________________________________________________________________________
res4c_branch2c (Conv2D) (None, None, None, 1 262144 activation_20[0][0]
__________________________________________________________________________________________________
bn4c_branch2c (BatchNormalizati (None, None, None, 1 4096 res4c_branch2c[0][0]
__________________________________________________________________________________________________
add_9 (Add) (None, None, None, 1 0 bn4c_branch2c[0][0]
res4b_out[0][0]
__________________________________________________________________________________________________
res4c_out (Activation) (None, None, None, 1 0 add_9[0][0]
__________________________________________________________________________________________________
res4d_branch2a (Conv2D) (None, None, None, 2 262144 res4c_out[0][0]
__________________________________________________________________________________________________
bn4d_branch2a (BatchNormalizati (None, None, None, 2 1024 res4d_branch2a[0][0]
__________________________________________________________________________________________________
activation_21 (Activation) (None, None, None, 2 0 bn4d_branch2a[0][0]
__________________________________________________________________________________________________
res4d_branch2b (Conv2D) (None, None, None, 2 589824 activation_21[0][0]
__________________________________________________________________________________________________
bn4d_branch2b (BatchNormalizati (None, None, None, 2 1024 res4d_branch2b[0][0]
__________________________________________________________________________________________________
activation_22 (Activation) (None, None, None, 2 0 bn4d_branch2b[0][0]
__________________________________________________________________________________________________
res4d_branch2c (Conv2D) (None, None, None, 1 262144 activation_22[0][0]
__________________________________________________________________________________________________
bn4d_branch2c (BatchNormalizati (None, None, None, 1 4096 res4d_branch2c[0][0]
__________________________________________________________________________________________________
add_10 (Add) (None, None, None, 1 0 bn4d_branch2c[0][0]
res4c_out[0][0]
__________________________________________________________________________________________________
res4d_out (Activation) (None, None, None, 1 0 add_10[0][0]
__________________________________________________________________________________________________
res4e_branch2a (Conv2D) (None, None, None, 2 262144 res4d_out[0][0]
__________________________________________________________________________________________________
bn4e_branch2a (BatchNormalizati (None, None, None, 2 1024 res4e_branch2a[0][0]
__________________________________________________________________________________________________
activation_23 (Activation) (None, None, None, 2 0 bn4e_branch2a[0][0]
__________________________________________________________________________________________________
res4e_branch2b (Conv2D) (None, None, None, 2 589824 activation_23[0][0]
__________________________________________________________________________________________________
bn4e_branch2b (BatchNormalizati (None, None, None, 2 1024 res4e_branch2b[0][0]
__________________________________________________________________________________________________
activation_24 (Activation) (None, None, None, 2 0 bn4e_branch2b[0][0]
__________________________________________________________________________________________________
res4e_branch2c (Conv2D) (None, None, None, 1 262144 activation_24[0][0]
__________________________________________________________________________________________________
bn4e_branch2c (BatchNormalizati (None, None, None, 1 4096 res4e_branch2c[0][0]
__________________________________________________________________________________________________
add_11 (Add) (None, None, None, 1 0 bn4e_branch2c[0][0]
res4d_out[0][0]
__________________________________________________________________________________________________
res4e_out (Activation) (None, None, None, 1 0 add_11[0][0]
__________________________________________________________________________________________________
res4f_branch2a (Conv2D) (None, None, None, 2 262144 res4e_out[0][0]
__________________________________________________________________________________________________
bn4f_branch2a (BatchNormalizati (None, None, None, 2 1024 res4f_branch2a[0][0]
__________________________________________________________________________________________________
activation_25 (Activation) (None, None, None, 2 0 bn4f_branch2a[0][0]
__________________________________________________________________________________________________
res4f_branch2b (Conv2D) (None, None, None, 2 589824 activation_25[0][0]
__________________________________________________________________________________________________
bn4f_branch2b (BatchNormalizati (None, None, None, 2 1024 res4f_branch2b[0][0]
__________________________________________________________________________________________________
activation_26 (Activation) (None, None, None, 2 0 bn4f_branch2b[0][0]
__________________________________________________________________________________________________
res4f_branch2c (Conv2D) (None, None, None, 1 262144 activation_26[0][0]
__________________________________________________________________________________________________
bn4f_branch2c (BatchNormalizati (None, None, None, 1 4096 res4f_branch2c[0][0]
__________________________________________________________________________________________________
add_12 (Add) (None, None, None, 1 0 bn4f_branch2c[0][0]
res4e_out[0][0]
__________________________________________________________________________________________________
res4f_out (Activation) (None, None, None, 1 0 add_12[0][0]
__________________________________________________________________________________________________
res5a_branch2a (Conv2D) (None, None, None, 5 524288 res4f_out[0][0]
__________________________________________________________________________________________________
bn5a_branch2a (BatchNormalizati (None, None, None, 5 2048 res5a_branch2a[0][0]
__________________________________________________________________________________________________
activation_27 (Activation) (None, None, None, 5 0 bn5a_branch2a[0][0]
__________________________________________________________________________________________________
res5a_branch2b (Conv2D) (None, None, None, 5 2359296 activation_27[0][0]
__________________________________________________________________________________________________
bn5a_branch2b (BatchNormalizati (None, None, None, 5 2048 res5a_branch2b[0][0]
__________________________________________________________________________________________________
activation_28 (Activation) (None, None, None, 5 0 bn5a_branch2b[0][0]
__________________________________________________________________________________________________
res5a_branch2c (Conv2D) (None, None, None, 2 1048576 activation_28[0][0]
__________________________________________________________________________________________________
res5a_branch1 (Conv2D) (None, None, None, 2 2097152 res4f_out[0][0]
__________________________________________________________________________________________________
bn5a_branch2c (BatchNormalizati (None, None, None, 2 8192 res5a_branch2c[0][0]
__________________________________________________________________________________________________
bn5a_branch1 (BatchNormalizatio (None, None, None, 2 8192 res5a_branch1[0][0]
__________________________________________________________________________________________________
add_13 (Add) (None, None, None, 2 0 bn5a_branch2c[0][0]
bn5a_branch1[0][0]
__________________________________________________________________________________________________
res5a_out (Activation) (None, None, None, 2 0 add_13[0][0]
__________________________________________________________________________________________________
res5b_branch2a (Conv2D) (None, None, None, 5 1048576 res5a_out[0][0]
__________________________________________________________________________________________________
bn5b_branch2a (BatchNormalizati (None, None, None, 5 2048 res5b_branch2a[0][0]
__________________________________________________________________________________________________
activation_29 (Activation) (None, None, None, 5 0 bn5b_branch2a[0][0]
__________________________________________________________________________________________________
res5b_branch2b (Conv2D) (None, None, None, 5 2359296 activation_29[0][0]
__________________________________________________________________________________________________
bn5b_branch2b (BatchNormalizati (None, None, None, 5 2048 res5b_branch2b[0][0]
__________________________________________________________________________________________________
activation_30 (Activation) (None, None, None, 5 0 bn5b_branch2b[0][0]
__________________________________________________________________________________________________
res5b_branch2c (Conv2D) (None, None, None, 2 1048576 activation_30[0][0]
__________________________________________________________________________________________________
bn5b_branch2c (BatchNormalizati (None, None, None, 2 8192 res5b_branch2c[0][0]
__________________________________________________________________________________________________
add_14 (Add) (None, None, None, 2 0 bn5b_branch2c[0][0]
res5a_out[0][0]
__________________________________________________________________________________________________
res5b_out (Activation) (None, None, None, 2 0 add_14[0][0]
__________________________________________________________________________________________________
res5c_branch2a (Conv2D) (None, None, None, 5 1048576 res5b_out[0][0]
__________________________________________________________________________________________________
bn5c_branch2a (BatchNormalizati (None, None, None, 5 2048 res5c_branch2a[0][0]
__________________________________________________________________________________________________
activation_31 (Activation) (None, None, None, 5 0 bn5c_branch2a[0][0]
__________________________________________________________________________________________________
res5c_branch2b (Conv2D) (None, None, None, 5 2359296 activation_31[0][0]
__________________________________________________________________________________________________
bn5c_branch2b (BatchNormalizati (None, None, None, 5 2048 res5c_branch2b[0][0]
__________________________________________________________________________________________________
activation_32 (Activation) (None, None, None, 5 0 bn5c_branch2b[0][0]
__________________________________________________________________________________________________
res5c_branch2c (Conv2D) (None, None, None, 2 1048576 activation_32[0][0]
__________________________________________________________________________________________________
bn5c_branch2c (BatchNormalizati (None, None, None, 2 8192 res5c_branch2c[0][0]
__________________________________________________________________________________________________
add_15 (Add) (None, None, None, 2 0 bn5c_branch2c[0][0]
res5b_out[0][0]
__________________________________________________________________________________________________
res5c_out (Activation) (None, None, None, 2 0 add_15[0][0]
__________________________________________________________________________________________________
fpn_c5p5 (Conv2D) (None, None, None, 2 524544 res5c_out[0][0]
__________________________________________________________________________________________________
fpn_p5upsampled (UpSampling2D) (None, None, None, 2 0 fpn_c5p5[0][0]
__________________________________________________________________________________________________
fpn_c4p4 (Conv2D) (None, None, None, 2 262400 res4f_out[0][0]
__________________________________________________________________________________________________
fpn_p4add (Add) (None, None, None, 2 0 fpn_p5upsampled[0][0]
fpn_c4p4[0][0]
__________________________________________________________________________________________________
fpn_p4upsampled (UpSampling2D) (None, None, None, 2 0 fpn_p4add[0][0]
__________________________________________________________________________________________________
fpn_c3p3 (Conv2D) (None, None, None, 2 131328 res3d_out[0][0]
__________________________________________________________________________________________________
fpn_p3add (Add) (None, None, None, 2 0 fpn_p4upsampled[0][0]
fpn_c3p3[0][0]
__________________________________________________________________________________________________
fpn_p3upsampled (UpSampling2D) (None, None, None, 2 0 fpn_p3add[0][0]
__________________________________________________________________________________________________
fpn_c2p2 (Conv2D) (None, None, None, 2 65792 res2c_out[0][0]
__________________________________________________________________________________________________
fpn_p2add (Add) (None, None, None, 2 0 fpn_p3upsampled[0][0]
fpn_c2p2[0][0]
__________________________________________________________________________________________________
fpn_p3 (Conv2D) (None, None, None, 2 590080 fpn_p3add[0][0]
__________________________________________________________________________________________________
fpn_p4 (Conv2D) (None, None, None, 2 590080 fpn_p4add[0][0]
__________________________________________________________________________________________________
fpn_p5 (Conv2D) (None, None, None, 2 590080 fpn_c5p5[0][0]
__________________________________________________________________________________________________
fpn_p2 (Conv2D) (None, None, None, 2 590080 fpn_p2add[0][0]
__________________________________________________________________________________________________
up_sampling2d (UpSampling2D) (None, None, None, 2 0 fpn_p3[0][0]
__________________________________________________________________________________________________
up_sampling2d_1 (UpSampling2D) (None, None, None, 2 0 fpn_p4[0][0]
__________________________________________________________________________________________________
up_sampling2d_2 (UpSampling2D) (None, None, None, 2 0 fpn_p5[0][0]
__________________________________________________________________________________________________
concatenate (Concatenate) (None, None, None, 1 0 fpn_p2[0][0]
up_sampling2d[0][0]
up_sampling2d_1[0][0]
up_sampling2d_2[0][0]
__________________________________________________________________________________________________
build_feature_pyramid (Conv2D) (None, None, None, 2 2359552 concatenate[0][0]
__________________________________________________________________________________________________
batch_normalization (BatchNorma (None, None, None, 2 1024 build_feature_pyramid[0][0]
__________________________________________________________________________________________________
activation_33 (Activation) (None, None, None, 2 0 batch_normalization[0][0]
__________________________________________________________________________________________________
conv2d (Conv2D) (None, None, None, 6 1542 activation_33[0][0]
__________________________________________________________________________________________________
activation_34 (Activation) (None, None, None, 6 0 conv2d[0][0]
==================================================================================================
Total params: 29,267,718
Trainable params: 29,214,086
Non-trainable params: 53,632
__________________________________________________________________________________________________
'''
import tensorflow as tf
from typing import Tuple
from tensorflow.keras.layers import Conv2D, Input, Activation
from tensorflow.keras import Model, Sequential
from feature_pyramid import build_feature_pyramid
from settings import OUTPUTS, BATCH_LOSS, RATE_OHEM, SN, RATE_LC_LS, METRIC_IOU_BATCH
def __model() -> Model:
'''
define the model, we use tf2's implemention of resnet
Parameters
----------
outputs : default 6, if none, outputs=6
Returns
-------
'''
input_images = Input([None, None, 3], name='input_images')
F = build_feature_pyramid(input_images) #(None, 160, 160, 256)
S = Conv2D(OUTPUTS, (1,1))(F) #(None, 160, 160, 6)
seg_s_pred = Activation("sigmoid")(S) #(None, 160, 160, 6)
# model initilizer
model = Model(inputs=input_images, outputs=seg_s_pred, name="PseNet")
# model.summary()
return model
def build_loss(y_true,y_pred) -> float:
'''
build psenet loss
References from : https://zhuanlan.zhihu.com/p/91019893?from_voters_page=true
Parameters
----------
y_true :
y_pred :
Returns
-------
'''
y_true = tf.cast(y_true, tf.float32)
y_pred = tf.cast(y_pred, tf.float32)
total_loss = 0.0
Lc_loss = 0.0
Ls_loss = 0.0
y_true_Lc = y_true[:, :, :, -1:]
y_pred_Lc = y_pred[:, :, :, -1:]
# 缩放
y_true_Ls = y_true[:, :, :, :-1]
y_pred_Ls = y_pred[:, :, :, :-1]
# adopt ohem to Lc
M = ohem_batch(y_true_Lc, y_pred_Lc)
Lc_loss = 1 - dice_loss(y_true_Lc * M, y_pred_Lc * M)
# ignore the pixels of non-text region
# in the segmentation result Sn to avoid a certain redundancy.
W = y_pred_Lc > 0.5
pos_mask = tf.cast(y_true_Lc, tf.bool)
W = tf.logical_or(pos_mask, W)
W = tf.cast(W, tf.float32)
for i in range(SN - 1):
Ls_loss += dice_loss(y_true_Ls[:, :, :, i:i + 1] * W, y_pred_Ls[:, :, :, i:i + 1] * W)
Ls_loss = 1.0 - Ls_loss / (SN - 1)
# Ls_loss = tf.print(Ls_loss,['lc_loss.->',Lc_loss,'ls_loss->',Ls_loss])
# λ balances the importance between Lc and Ls.
total_loss = RATE_LC_LS * Lc_loss + (1 - RATE_LC_LS) * Ls_loss
return total_loss
def ohem_batch(y_true_Lc, y_pred_Lc ):
'''
It is a high-order function that repeatedly applies the callable function fn to the sequence of elems elements.
批量
Parameters
----------
y_true_Lc :
y_pred_Lc :
Returns
-------
'''
M = tf.map_fn(ohem_single, (y_true_Lc, y_pred_Lc), dtype=tf.float32)
return tf.stack(M)
def ohem_single(s_Lc:Tuple):
'''
在线难例挖掘，调整网络学习难样本
Parameters
----------
s_Lc : tuple , (s_y_ture_Lc, s_y_pred_Lc)
Returns
-------
'''
s_y_ture_Lc, s_y_pred_Lc = s_Lc
n_pos = tf.reduce_sum(s_y_ture_Lc)
# n_pos = tf.print(n_pos,['n_pos->',n_pos])
def has_pos():
n_max_neg = tf.reduce_sum(tf.cast(s_y_ture_Lc > -1.0, tf.int32))
# n_max_neg = tf.print(n_max_neg,['n_max_neg',n_max_neg])
n_neg = n_pos * RATE_OHEM
n_neg = tf.cast(n_neg, tf.int32)
n_neg = tf.minimum(n_neg, n_max_neg)
pos_mask = tf.cast(s_y_ture_Lc, tf.bool)
neg_mask = tf.cast(tf.equal(pos_mask, False), tf.float32)
neg = neg_mask * s_y_pred_Lc
vals, _ = tf.nn.top_k(tf.reshape(neg, (1, -1)), k=n_neg)
threshold = vals[0][-1]
# threshold = tf.print(threshold,['threshold->',threshold,
# 'n_neg>threshold->',tf.reduce_sum(tf.cast(neg>0,tf.int32)),
# 's_y_pred_Lc',tf.reduce_sum(tf.cast(s_y_pred_Lc>0.0,tf.int32)),
# 'neg->',neg,
# 'neg shape->',tf.shape(neg)])
mask = tf.logical_or(pos_mask, neg > threshold)
return tf.cast(mask, tf.float32)
def no_pos():
mask = tf.zeros_like(s_y_ture_Lc)
return tf.cast(mask, tf.float32)
return tf.cond(n_pos > 0, has_pos, no_pos)
def dice_loss(y_true, y_pred, smooth=1.0):
'''
相似熵，你可以直接考虑为F值的计算，理解请参考：
https://zhuanlan.zhihu.com/p/91019893?from_voters_page=true
Parameters
----------
y_true :
y_pred :
smooth :
Returns
-------
'''
loss = 0.0
if (BATCH_LOSS):
intersection = tf.reduce_sum(y_true * y_pred)
loss = tf.reduce_mean((2.0 * intersection + smooth) / (tf.reduce_sum(y_true) + tf.reduce_sum(y_pred) + smooth))
else:
intersection = tf.reduce_sum(y_true * y_pred, axis=(1, 2, 3))
loss = tf.reduce_mean(
(2.0 * intersection + smooth) / (tf.reduce_sum(y_true, axis=(1, 2, 3)) + tf.reduce_sum(y_pred, axis=(1, 2, 3)) + smooth))
return loss
def iou(y_true, y_pred, label: int):
'''
Parameters
----------
y_true :
y_pred :
label :
Returns the intersection over union for a given label.
-------
'''
y_true = y_true[:, :, :, -1:]
y_pred = y_pred[:, :, :, -1:]
label = tf.cast(label, tf.float32)
y_true = tf.cast(tf.equal(y_true, label), tf.float32)
y_pred = y_pred > 0.5
y_pred = tf.cast(y_pred, tf.float32)
y_pred = tf.cast(tf.equal(y_pred, label), tf.float32)
if (METRIC_IOU_BATCH):
intersecion = tf.reduce_sum(y_true * y_pred)
union = tf.reduce_sum(y_true) + tf.reduce_sum(y_pred) - intersecion
else:
intersecion = tf.reduce_sum(y_true * y_pred, axis=(1, 2, 3))
union = tf.reduce_sum(y_true, axis=(1, 2, 3)) + tf.reduce_sum(y_pred, axis=(1, 2, 3)) - intersecion
return tf.reduce_mean((intersecion + 1e-5) / (union + 1e-5))
def build_iou(label: int or Tuple, name: str or Tuple):
"""
build an intersection over union metric for labels list or label
Args:
label:a label list or label int
name: an optional name for label
Returns:
a keras metric to evaluate Iou for the given label
Note:
label and name support list inputs for multiple labels
"""
if isinstance(label, list):
if (isinstance(name, list)):
return [build_iou(l, n) for (l, n) in zip(label, name)]
return [build_iou for i in label]
def label_iou(y_true, y_pred):
return iou(y_true, y_pred, label)
if name is None:
name = label
label_iou.__name__ = 'iou_{}'.format(name)
return label_iou
# @tf.function
def mean_iou(y_true, y_pred, total_iou):
'''
compute mean iou
Parameters
----------
y_true :
y_pred :
Returns
References bug: tf.function-decorated function tried to create variables on non-first call.
-------
'''
num_labels = y_pred.get_shape()[-1]
for label in range(num_labels):
total_iou = total_iou + iou(y_true, y_pred, label)
num_labels = tf.cast(num_labels, dtype=tf.float32)
return total_iou / num_labels, total_iou