Tiny-yolo网络修改记录

本文主要记录训练一类网络，修改网络参数，引起网络性能的变化

0.最原始的tiny-yolo

  • 网络结构如下
[net]
#test
batch=1
subdivisions=1
#train

#batch=64
#subdivisions=4


width=416
height=416
channels=3
momentum=0.9
decay=0.0005
angle=0
saturation = 1.5
exposure = 1.5
hue=.1

learning_rate=0.001
max_batches = 40200
policy=steps
steps=-1,100,20000,30000
scales=.1,10,.1,.1

[convolutional]
batch_normalize=1
filters=16
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=32
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=1

[convolutional]
batch_normalize=1
filters=1024
size=3
stride=1
pad=1
activation=leaky

###########

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=1024
activation=leaky

[convolutional]
size=1
stride=1
pad=1
filters=30
activation=linear

[region]
anchors = 1.08,1.19,  3.42,4.41,  6.63,11.38,  9.42,5.11,  16.62,10.52
bias_match=1
classes=1
coords=4
num=5
softmax=1
jitter=.2
rescore=1

object_scale=5
noobject_scale=1
class_scale=1
coord_scale=1

absolute=1
thresh = .6
random=1
  • Evaluate Recall
  252   656   690       RPs/Img: 21.57  IOU: 75.29%     Recall:95.07%
  253   658   692       RPs/Img: 21.50  IOU: 75.30%     Recall:95.09%
  254   660   694       RPs/Img: 21.50  IOU: 75.33%     Recall:95.10%
  255   663   697       RPs/Img: 21.43  IOU: 75.40%     Recall:95.12%
  256   663   697       RPs/Img: 21.41  IOU: 75.40%     Recall:95.12%
  257   663   697       RPs/Img: 21.38  IOU: 75.40%     Recall:95.12%
  258   665   699       RPs/Img: 21.36  IOU: 75.41%     Recall:95.14%
  259   667   701       RPs/Img: 21.35  IOU: 75.40%     Recall:95.15%
  260   669   703       RPs/Img: 21.33  IOU: 75.42%     Recall:95.16%
  261   671   705       RPs/Img: 21.31  IOU: 75.42%     Recall:95.18%
  262   673   707       RPs/Img: 21.33  IOU: 75.43%     Recall:95.19%
  263   673   707       RPs/Img: 21.32  IOU: 75.43%     Recall:95.19%
  264   673   707       RPs/Img: 21.35  IOU: 75.43%     Recall:95.19%
  265   675   709       RPs/Img: 21.31  IOU: 75.43%     Recall:95.20%
  266   676   710       RPs/Img: 21.27  IOU: 75.41%     Recall:95.21%
  267   678   712       RPs/Img: 21.25  IOU: 75.41%     Recall:95.22%
  268   682   716       RPs/Img: 21.25  IOU: 75.44%     Recall:95.25%
  269   683   717       RPs/Img: 21.22  IOU: 75.44%     Recall:95.26%
  270   685   719       RPs/Img: 21.25  IOU: 75.46%     Recall:95.27%
  271   687   721       RPs/Img: 21.22  IOU: 75.48%     Recall:95.28%
  272   689   723       RPs/Img: 21.21  IOU: 75.47%     Recall:95.30%
  273   689   723       RPs/Img: 21.25  IOU: 75.47%     Recall:95.30%
  274   691   725       RPs/Img: 21.24  IOU: 75.50%     Recall:95.31%
  275   691   725       RPs/Img: 21.32  IOU: 75.50%     Recall:95.31%
  276   691   725       RPs/Img: 21.36  IOU: 75.50%     Recall:95.31%
  277   692   726       RPs/Img: 21.35  IOU: 75.52%     Recall:95.32%
  278   694   728       RPs/Img: 21.37  IOU: 75.50%     Recall:95.33%
  279   696   730       RPs/Img: 21.37  IOU: 75.51%     Recall:95.34%
  280   699   734       RPs/Img: 21.37  IOU: 75.46%     Recall:95.23%
  281   702   738       RPs/Img: 21.39  IOU: 75.37%     Recall:95.12%
  282   704   740       RPs/Img: 21.41  IOU: 75.37%     Recall:95.14%
  283   706   742       RPs/Img: 21.41  IOU: 75.41%     Recall:95.15%
  284   706   742       RPs/Img: 21.40  IOU: 75.41%     Recall:95.15%
  285   708   744       RPs/Img: 21.37  IOU: 75.41%     Recall:95.16%
  286   708   744       RPs/Img: 21.38  IOU: 75.41%     Recall:95.16%
  287   708   744       RPs/Img: 21.34  IOU: 75.41%     Recall:95.16%
  288   708   744       RPs/Img: 21.33  IOU: 75.41%     Recall:95.16%
  289   710   746       RPs/Img: 21.33  IOU: 75.44%     Recall:95.17%
  290   711   748       RPs/Img: 21.34  IOU: 75.38%     Recall:95.05%
  291   713   750       RPs/Img: 21.32  IOU: 75.41%     Recall:95.07%
  292   715   752       RPs/Img: 21.37  IOU: 75.37%     Recall:95.08%
  293   717   754       RPs/Img: 21.33  IOU: 75.40%     Recall:95.09%
  294   719   756       RPs/Img: 21.32  IOU: 75.42%     Recall:95.11%
  295   721   758       RPs/Img: 21.32  IOU: 75.41%     Recall:95.12%
  296   722   759       RPs/Img: 21.28  IOU: 75.42%     Recall:95.13%
  297   722   759       RPs/Img: 21.36  IOU: 75.42%     Recall:95.13%
  298   722   759       RPs/Img: 21.42  IOU: 75.42%     Recall:95.13%
  299   724   761       RPs/Img: 21.41  IOU: 75.44%     Recall:95.14%
  300   725   762       RPs/Img: 21.43  IOU: 75.44%     Recall:95.14%
  301   727   764       RPs/Img: 21.42  IOU: 75.48%     Recall:95.16%
  302   728   765       RPs/Img: 21.43  IOU: 75.46%     Recall:95.16%
  303   728   765       RPs/Img: 21.40  IOU: 75.46%     Recall:95.16%
  304   730   767       RPs/Img: 21.40  IOU: 75.48%     Recall:95.18%
  305   734   771       RPs/Img: 21.42  IOU: 75.50%     Recall:95.20%
  306   746   783       RPs/Img: 21.45  IOU: 75.59%     Recall:95.27%
  307   748   785       RPs/Img: 21.43  IOU: 75.62%     Recall:95.29%
  308   750   787       RPs/Img: 21.42  IOU: 75.59%     Recall:95.30%
  309   752   789       RPs/Img: 21.43  IOU: 75.62%     Recall:95.31%
  310   754   791       RPs/Img: 21.44  IOU: 75.63%     Recall:95.32%

1.第一次修改

  • 网络结构如下
[net]
#test
batch=1
subdivisions=1
#train

#batch=64
#subdivisions=4


width=416
height=416
channels=3
momentum=0.9
decay=0.0005
angle=0
saturation = 1.5
exposure = 1.5
hue=.1

learning_rate=0.001
max_batches = 40200
policy=steps
steps=-1,100,20000,30000
scales=.1,10,.1,.1

[convolutional]
batch_normalize=1
filters=16
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=32
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=1

[convolutional]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky

###########

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=512
activation=leaky

[convolutional]
size=1
stride=1
pad=1
filters=30
activation=linear

[region]
anchors = 1.08,1.19,  3.42,4.41,  6.63,11.38,  9.42,5.11,  16.62,10.52
bias_match=1
classes=1
coords=4
num=5
softmax=1
jitter=.2
rescore=1

object_scale=5
noobject_scale=1
class_scale=1
coord_scale=1

absolute=1
thresh = .6
random=1
  • Loss-iter Curve如下
image.png
  • Evaluate Recall
  252   604   690       RPs/Img: 92.45  IOU: 66.21%     Recall:87.54%
  253   605   692       RPs/Img: 92.43  IOU: 66.18%     Recall:87.43%
  254   607   694       RPs/Img: 92.44  IOU: 66.17%     Recall:87.46%
  255   610   697       RPs/Img: 92.37  IOU: 66.22%     Recall:87.52%
  256   610   697       RPs/Img: 92.28  IOU: 66.22%     Recall:87.52%
  257   610   697       RPs/Img: 92.21  IOU: 66.22%     Recall:87.52%
  258   611   699       RPs/Img: 92.13  IOU: 66.21%     Recall:87.41%
  259   612   701       RPs/Img: 92.07  IOU: 66.16%     Recall:87.30%
  260   614   703       RPs/Img: 91.99  IOU: 66.22%     Recall:87.34%
  261   616   705       RPs/Img: 92.05  IOU: 66.23%     Recall:87.38%
  262   618   707       RPs/Img: 92.05  IOU: 66.24%     Recall:87.41%
  263   618   707       RPs/Img: 92.20  IOU: 66.24%     Recall:87.41%
  264   618   707       RPs/Img: 92.20  IOU: 66.24%     Recall:87.41%
  265   620   709       RPs/Img: 92.12  IOU: 66.23%     Recall:87.45%
  266   621   710       RPs/Img: 92.27  IOU: 66.22%     Recall:87.46%
  267   623   712       RPs/Img: 92.22  IOU: 66.27%     Recall:87.50%
  268   624   716       RPs/Img: 92.25  IOU: 66.21%     Recall:87.15%
  269   625   717       RPs/Img: 92.29  IOU: 66.22%     Recall:87.17%
  270   627   719       RPs/Img: 92.26  IOU: 66.24%     Recall:87.20%
  271   629   721       RPs/Img: 92.26  IOU: 66.25%     Recall:87.24%
  272   631   723       RPs/Img: 92.18  IOU: 66.27%     Recall:87.28%
  273   631   723       RPs/Img: 92.32  IOU: 66.27%     Recall:87.28%
  274   633   725       RPs/Img: 92.29  IOU: 66.26%     Recall:87.31%
  275   633   725       RPs/Img: 92.35  IOU: 66.26%     Recall:87.31%
  276   633   725       RPs/Img: 92.28  IOU: 66.26%     Recall:87.31%
  277   634   726       RPs/Img: 92.26  IOU: 66.26%     Recall:87.33%
  278   636   728       RPs/Img: 92.18  IOU: 66.29%     Recall:87.36%
  279   637   730       RPs/Img: 92.23  IOU: 66.25%     Recall:87.26%
  280   640   734       RPs/Img: 92.23  IOU: 66.22%     Recall:87.19%
  281   642   738       RPs/Img: 92.19  IOU: 66.16%     Recall:86.99%
  282   644   740       RPs/Img: 92.32  IOU: 66.20%     Recall:87.03%
  283   646   742       RPs/Img: 92.23  IOU: 66.23%     Recall:87.06%
  284   646   742       RPs/Img: 92.24  IOU: 66.23%     Recall:87.06%
  285   648   744       RPs/Img: 92.09  IOU: 66.24%     Recall:87.10%
  286   648   744       RPs/Img: 92.00  IOU: 66.24%     Recall:87.10%
  287   648   744       RPs/Img: 92.06  IOU: 66.24%     Recall:87.10%
  288   648   744       RPs/Img: 92.02  IOU: 66.24%     Recall:87.10%
  289   650   746       RPs/Img: 92.13  IOU: 66.23%     Recall:87.13%
  290   650   748       RPs/Img: 92.23  IOU: 66.17%     Recall:86.90%
  291   652   750       RPs/Img: 92.15  IOU: 66.22%     Recall:86.93%
  292   652   752       RPs/Img: 92.14  IOU: 66.17%     Recall:86.70%
  293   654   754       RPs/Img: 92.12  IOU: 66.22%     Recall:86.74%
  294   656   756       RPs/Img: 92.14  IOU: 66.23%     Recall:86.77%
  295   657   758       RPs/Img: 92.16  IOU: 66.21%     Recall:86.68%
  296   658   759       RPs/Img: 92.16  IOU: 66.20%     Recall:86.69%
  297   658   759       RPs/Img: 92.36  IOU: 66.20%     Recall:86.69%
  298   658   759       RPs/Img: 92.43  IOU: 66.20%     Recall:86.69%
  299   660   761       RPs/Img: 92.35  IOU: 66.24%     Recall:86.73%
  300   660   762       RPs/Img: 92.35  IOU: 66.21%     Recall:86.61%
  301   662   764       RPs/Img: 92.34  IOU: 66.24%     Recall:86.65%
  302   663   765       RPs/Img: 92.36  IOU: 66.24%     Recall:86.67%
  303   663   765       RPs/Img: 92.20  IOU: 66.24%     Recall:86.67%
  304   665   767       RPs/Img: 92.06  IOU: 66.29%     Recall:86.70%
  305   669   771       RPs/Img: 92.07  IOU: 66.34%     Recall:86.77%
  306   681   783       RPs/Img: 92.02  IOU: 66.32%     Recall:86.97%
  307   683   785       RPs/Img: 91.98  IOU: 66.32%     Recall:87.01%
  308   685   787       RPs/Img: 92.00  IOU: 66.33%     Recall:87.04%
  309   687   789       RPs/Img: 92.01  IOU: 66.35%     Recall:87.07%
  310   689   791       RPs/Img: 91.99  IOU: 66.38%     Recall:87.10%

2.第二次修改

  • 网络结构如下
[net]
#test
#batch=1
#subdivisions=1
#train
batch=64
subdivisions=4
width=416
height=416
channels=3
momentum=0.9
decay=0.0005
angle=0
saturation = 1.5
exposure = 1.5
hue=.1

learning_rate=0.001
max_batches = 40200
policy=steps
steps=-1,100,20000,30000
scales=.1,10,.1,.1

[convolutional]
batch_normalize=1
filters=16
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=32
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=1

[convolutional]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky

###########

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=512
activation=leaky
###New layer add ###
[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=512
activation=leaky

[convolutional]
size=1
stride=1
pad=1
filters=30
activation=linear

[region]
anchors = 1.08,1.19,  3.42,4.41,  6.63,11.38,  9.42,5.11,  16.62,10.52
bias_match=1
classes=1
coords=4
num=5
softmax=1
jitter=.2
rescore=1

object_scale=5
noobject_scale=1
class_scale=1
coord_scale=1

absolute=1
thresh = .6
random=1
  • Evaluate Recall
  252   639   690       RPs/Img: 33.14  IOU: 73.85%     Recall:92.61%
  253   640   692       RPs/Img: 33.11  IOU: 73.83%     Recall:92.49%
  254   642   694       RPs/Img: 33.09  IOU: 73.86%     Recall:92.51%
  255   645   697       RPs/Img: 33.05  IOU: 73.93%     Recall:92.54%
  256   645   697       RPs/Img: 33.03  IOU: 73.93%     Recall:92.54%
  257   645   697       RPs/Img: 33.02  IOU: 73.93%     Recall:92.54%
  258   647   699       RPs/Img: 32.93  IOU: 73.96%     Recall:92.56%
  259   648   701       RPs/Img: 32.95  IOU: 73.93%     Recall:92.44%
  260   650   703       RPs/Img: 32.91  IOU: 73.95%     Recall:92.46%
  261   652   705       RPs/Img: 32.92  IOU: 73.97%     Recall:92.48%
  262   654   707       RPs/Img: 32.92  IOU: 73.98%     Recall:92.50%
  263   654   707       RPs/Img: 32.91  IOU: 73.98%     Recall:92.50%
  264   654   707       RPs/Img: 32.91  IOU: 73.98%     Recall:92.50%
  265   656   709       RPs/Img: 32.90  IOU: 73.98%     Recall:92.52%
  266   656   710       RPs/Img: 32.82  IOU: 73.94%     Recall:92.39%
  267   658   712       RPs/Img: 32.80  IOU: 73.94%     Recall:92.42%
  268   662   716       RPs/Img: 32.84  IOU: 73.98%     Recall:92.46%
  269   663   717       RPs/Img: 32.80  IOU: 73.99%     Recall:92.47%
  270   664   719       RPs/Img: 32.83  IOU: 73.95%     Recall:92.35%
  271   666   721       RPs/Img: 32.80  IOU: 73.97%     Recall:92.37%
  272   668   723       RPs/Img: 32.79  IOU: 73.97%     Recall:92.39%
  273   668   723       RPs/Img: 32.89  IOU: 73.97%     Recall:92.39%
  274   670   725       RPs/Img: 32.83  IOU: 74.00%     Recall:92.41%
  275   670   725       RPs/Img: 32.88  IOU: 74.00%     Recall:92.41%
  276   670   725       RPs/Img: 32.87  IOU: 74.00%     Recall:92.41%
  277   671   726       RPs/Img: 32.81  IOU: 74.00%     Recall:92.42%
  278   673   728       RPs/Img: 32.80  IOU: 74.03%     Recall:92.45%
  279   674   730       RPs/Img: 32.85  IOU: 74.00%     Recall:92.33%
  280   677   734       RPs/Img: 32.89  IOU: 73.93%     Recall:92.23%
  281   679   738       RPs/Img: 32.90  IOU: 73.87%     Recall:92.01%
  282   681   740       RPs/Img: 32.92  IOU: 73.90%     Recall:92.03%
  283   683   742       RPs/Img: 32.90  IOU: 73.92%     Recall:92.05%
  284   683   742       RPs/Img: 32.90  IOU: 73.92%     Recall:92.05%
  285   685   744       RPs/Img: 32.87  IOU: 73.94%     Recall:92.07%
  286   685   744       RPs/Img: 32.82  IOU: 73.94%     Recall:92.07%
  287   685   744       RPs/Img: 32.77  IOU: 73.94%     Recall:92.07%
  288   685   744       RPs/Img: 32.74  IOU: 73.94%     Recall:92.07%
  289   687   746       RPs/Img: 32.81  IOU: 73.91%     Recall:92.09%
  290   689   748       RPs/Img: 32.84  IOU: 73.89%     Recall:92.11%
  291   691   750       RPs/Img: 32.82  IOU: 73.91%     Recall:92.13%
  292   693   752       RPs/Img: 32.86  IOU: 73.86%     Recall:92.15%
  293   695   754       RPs/Img: 32.84  IOU: 73.87%     Recall:92.18%
  294   697   756       RPs/Img: 32.89  IOU: 73.87%     Recall:92.20%
  295   699   758       RPs/Img: 32.91  IOU: 73.86%     Recall:92.22%
  296   700   759       RPs/Img: 32.83  IOU: 73.86%     Recall:92.23%
  297   700   759       RPs/Img: 32.84  IOU: 73.86%     Recall:92.23%
  298   700   759       RPs/Img: 32.89  IOU: 73.86%     Recall:92.23%
  299   702   761       RPs/Img: 32.86  IOU: 73.90%     Recall:92.25%
  300   703   762       RPs/Img: 32.83  IOU: 73.90%     Recall:92.26%
  301   705   764       RPs/Img: 32.84  IOU: 73.93%     Recall:92.28%
  302   706   765       RPs/Img: 32.82  IOU: 73.92%     Recall:92.29%
  303   706   765       RPs/Img: 32.81  IOU: 73.92%     Recall:92.29%
  304   708   767       RPs/Img: 32.76  IOU: 73.94%     Recall:92.31%
  305   712   771       RPs/Img: 32.78  IOU: 73.98%     Recall:92.35%
  306   724   783       RPs/Img: 32.81  IOU: 74.08%     Recall:92.46%
  307   726   785       RPs/Img: 32.81  IOU: 74.11%     Recall:92.48%
  308   728   787       RPs/Img: 32.79  IOU: 74.11%     Recall:92.50%
  309   730   789       RPs/Img: 32.81  IOU: 74.13%     Recall:92.52%
  310   732   791       RPs/Img: 32.84  IOU: 74.17%     Recall:92.54%
最后编辑于 ：
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