TF之pix2pix：基于TF利用Facades数据集训练pix2pix模型、测试并进行生成过程全记录

TF之pix2pix：基于TF利用Facades数据集训练pix2pix模型、测试并进行生成过程全记录

 

 

目录

TB监控

1、SCALARS

2、IMAGES

3、GRAPHS

4、DISTRIBUTIONS

输出结果

训练代码运行过程全记录

测试代码全记录

---

 

 

 

TB监控

1、SCALARS

2、IMAGES

inputs_summary		outputs_summary
predict_fake_summary		predict_real_summary
targets_summary

 

3、GRAPHS

4、DISTRIBUTIONS

 

 

 

输出结果

 

 

训练代码运行过程全记录

2 epoch：2126~2218

开始训练
aspect_ratio = 1.0
batch_size = 1
beta1 = 0.5
checkpoint = None
display_freq = 0
flip = True
gan_weight = 1.0
input_dir = facades/train
l1_weight = 100.0
lab_colorization = False
lr = 0.0002
max_epochs = 200
max_steps = None
mode = train
ndf = 64
ngf = 64
output_dir = facades_train
output_filetype = png
progress_freq = 50
save_freq = 5000
scale_size = 286
seed = 407313043
summary_freq = 100
trace_freq = 0
which_direction = BtoA


2018-10-07 21:26:49.558601: 
parameter_count = 57183616
progress  epoch 1  step 50  image/sec 0.4  remaining 35m
discrim_loss 0.59409106
gen_loss_GAN 0.3667453
gen_loss_L1 0.14627346
recording summary
progress  epoch 1  step 100  image/sec 0.3  remaining 33m
discrim_loss 0.77973217
gen_loss_GAN 0.74193096
gen_loss_L1 0.21620709
progress  epoch 1  step 150  image/sec 0.4  remaining 30m
discrim_loss 0.7097481
gen_loss_GAN 1.2259353
gen_loss_L1 0.27181715
recording summary
progress  epoch 1  step 200  image/sec 0.4  remaining 28m
discrim_loss 0.6670909
gen_loss_GAN 1.5955695
gen_loss_L1 0.30515844
progress  epoch 1  step 250  image/sec 0.4  remaining 25m
discrim_loss 0.5505945
gen_loss_GAN 1.897398
gen_loss_L1 0.3195855
recording summary
progress  epoch 1  step 300  image/sec 0.4  remaining 23m
discrim_loss 0.54358536
gen_loss_GAN 2.1270702
gen_loss_L1 0.33635142
progress  epoch 1  step 350  image/sec 0.4  remaining 21m
discrim_loss 0.53915083
gen_loss_GAN 2.234504
gen_loss_L1 0.33556485
recording summary
progress  epoch 1  step 400  image/sec 0.4  remaining 18m
discrim_loss 0.5494336
gen_loss_GAN 2.349324
gen_loss_L1 0.33941123
progress  epoch 2  step 50  image/sec 0.4  remaining 16m
discrim_loss 0.5763757
gen_loss_GAN 2.3618762
gen_loss_L1 0.3413253
recording summary
progress  epoch 2  step 100  image/sec 0.4  remaining 14m
discrim_loss 0.63876843
gen_loss_GAN 2.2650375
gen_loss_L1 0.3409966
progress  epoch 2  step 150  image/sec 0.4  remaining 11m
discrim_loss 0.6011929
gen_loss_GAN 2.264903
gen_loss_L1 0.34726414
recording summary
progress  epoch 2  step 200  image/sec 0.4  remaining 9m
discrim_loss 0.59052
gen_loss_GAN 2.302569
gen_loss_L1 0.3522855
progress  epoch 2  step 250  image/sec 0.3  remaining 7m
discrim_loss 0.57109314
gen_loss_GAN 2.324084
gen_loss_L1 0.35149702
recording summary
progress  epoch 2  step 300  image/sec 0.3  remaining 4m
discrim_loss 0.4946928
gen_loss_GAN 2.5188313
gen_loss_L1 0.3564302
progress  epoch 2  step 350  image/sec 0.3  remaining 2m
discrim_loss 0.5365153
gen_loss_GAN 2.5414586
gen_loss_L1 0.35425124
recording summary
progress  epoch 2  step 400  image/sec 0.3  remaining 0m
discrim_loss 0.56210524
gen_loss_GAN 2.5018184
gen_loss_L1 0.35051015
saving model

 

测试代码全记录

开始测试
loaded lab_colorization = False
loaded ndf = 64
loaded ngf = 64
loaded which_direction = BtoA
aspect_ratio = 1.0
batch_size = 1
beta1 = 0.5
checkpoint = facades_train
display_freq = 0
flip = False
gan_weight = 1.0
input_dir = facades/val
l1_weight = 100.0
lab_colorization = False
lr = 0.0002
max_epochs = None
max_steps = None
mode = test
ndf = 64
ngf = 64
output_dir = facades_test
output_filetype = png
progress_freq = 50
save_freq = 5000
scale_size = 256
seed = 651085994
summary_freq = 100
trace_freq = 0
which_direction = BtoA

examples count = 100
parameter_count = 57183616
loading model from checkpoint
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wrote index at facades_test\index.html