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  1. model/.gitignore +0 -3
  2. model/cfg/alexnet.cfg +96 -0
  3. model/cfg/cifar.cfg +121 -0
  4. model/cfg/cifar.test.cfg +117 -0
  5. model/cfg/coco.data +8 -0
  6. model/cfg/combine9k.data +10 -0
  7. model/cfg/darknet.cfg +120 -0
  8. model/cfg/darknet19.cfg +205 -0
  9. model/cfg/darknet19_448.cfg +197 -0
  10. model/cfg/darknet53.cfg +566 -0
  11. model/cfg/darknet53_448.cfg +559 -0
  12. model/cfg/darknet9000.cfg +205 -0
  13. model/cfg/densenet201.cfg +1951 -0
  14. model/cfg/extraction.cfg +209 -0
  15. model/cfg/extraction.conv.cfg +179 -0
  16. model/cfg/extraction22k.cfg +206 -0
  17. model/cfg/go.cfg +132 -0
  18. model/cfg/go.test.cfg +132 -0
  19. model/cfg/gru.cfg +29 -0
  20. model/cfg/imagenet1k.data +8 -0
  21. model/cfg/imagenet22k.dataset +9 -0
  22. model/cfg/imagenet9k.hierarchy.dataset +9 -0
  23. model/cfg/jnet-conv.cfg +118 -0
  24. model/cfg/openimages.data +8 -0
  25. model/cfg/resnet101.cfg +990 -0
  26. model/cfg/resnet152.cfg +1460 -0
  27. model/cfg/resnet18.cfg +228 -0
  28. model/cfg/resnet34.cfg +392 -0
  29. model/cfg/resnet50.cfg +510 -0
  30. model/cfg/resnext101-32x4d.cfg +1053 -0
  31. model/cfg/resnext152-32x4d.cfg +1562 -0
  32. model/cfg/resnext50.cfg +523 -0
  33. model/cfg/rnn.cfg +38 -0
  34. model/cfg/rnn.train.cfg +38 -0
  35. model/cfg/strided.cfg +182 -0
  36. model/cfg/t1.test.cfg +117 -0
  37. model/cfg/tiny.cfg +174 -0
  38. model/cfg/vgg-16.cfg +157 -0
  39. model/cfg/vgg-conv.cfg +121 -0
  40. model/cfg/voc.data +6 -0
  41. model/cfg/writing.cfg +41 -0
  42. model/cfg/yolo9000.cfg +218 -0
  43. model/cfg/yolov1-tiny.cfg +130 -0
  44. model/cfg/yolov1.cfg +261 -0
  45. model/cfg/yolov2-tiny-voc.cfg +138 -0
  46. model/cfg/yolov2-tiny.cfg +139 -0
  47. model/cfg/yolov2-voc.cfg +258 -0
  48. model/cfg/yolov2.cfg +258 -0
  49. model/cfg/yolov3-openimages.cfg +789 -0
  50. model/cfg/yolov3-spp.cfg +822 -0
model/.gitignore CHANGED
@@ -7,7 +7,6 @@
7
  *.pyc
8
  old/
9
  mnist/
10
- data/
11
  caffe/
12
  grasp/
13
  images/
@@ -15,8 +14,6 @@ opencv/
15
  convnet/
16
  decaf/
17
  submission/
18
- cfg/
19
- darknet
20
  .fuse*
21
 
22
  # OS Generated #
 
7
  *.pyc
8
  old/
9
  mnist/
 
10
  caffe/
11
  grasp/
12
  images/
 
14
  convnet/
15
  decaf/
16
  submission/
 
 
17
  .fuse*
18
 
19
  # OS Generated #
model/cfg/alexnet.cfg ADDED
@@ -0,0 +1,96 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [net]
2
+ # Training
3
+ # batch=128
4
+ # subdivisions=1
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+ # Testing
6
+ batch=1
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+ subdivisions=1
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+ height=227
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+ width=227
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+ channels=3
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+ momentum=0.9
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+ decay=0.0005
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+ max_crop=256
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+
15
+ learning_rate=0.01
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+ policy=poly
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+ power=4
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+ max_batches=800000
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+
20
+ angle=7
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+ hue = .1
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+ saturation=.75
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+ exposure=.75
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+ aspect=.75
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+
26
+ [convolutional]
27
+ filters=96
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+ size=11
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+ stride=4
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+ pad=0
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+ activation=relu
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+
33
+ [maxpool]
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+ size=3
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+ stride=2
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+ padding=0
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+
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+ [convolutional]
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+ filters=256
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+ size=5
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+ pad=1
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+ activation=relu
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+ stride=2
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+ [convolutional]
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+ pad=1
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+ activation=relu
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+
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+ [convolutional]
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+ filters=384
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+ size=3
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+ stride=1
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+ pad=1
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+ activation=relu
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+
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+ [convolutional]
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+ filters=256
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+ size=3
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+ stride=1
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+ pad=1
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+ activation=relu
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+
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+ [maxpool]
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+ size=3
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+ stride=2
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+ padding=0
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+
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+ [connected]
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+ output=4096
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+ activation=relu
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+
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+ [dropout]
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+ probability=.5
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+ [connected]
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+ output=4096
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+ activation=relu
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+
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+ [dropout]
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+ probability=.5
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+
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+ [connected]
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+ output=1000
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+ activation=linear
93
+
94
+ [softmax]
95
+ groups=1
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+
model/cfg/cifar.cfg ADDED
@@ -0,0 +1,121 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [net]
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+ batch=128
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+ subdivisions=1
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+ height=28
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+ width=28
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+ channels=3
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+ max_crop=32
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+ min_crop=32
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+
10
+ hue=.1
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+ saturation=.75
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+ exposure=.75
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+
14
+ learning_rate=0.4
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+ policy=poly
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+ power=4
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+ max_batches = 5000
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+ momentum=0.9
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+ decay=0.0005
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+
21
+
22
+ [convolutional]
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+ batch_normalize=1
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+ filters=128
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+ size=3
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+ stride=1
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+ pad=1
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+ activation=leaky
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+
30
+ [convolutional]
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+ batch_normalize=1
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+ filters=128
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+ size=3
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+ stride=1
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+ pad=1
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+ activation=leaky
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+
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+ [convolutional]
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+ batch_normalize=1
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+ filters=128
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+ size=3
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+ stride=1
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+ pad=1
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+ activation=leaky
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+
46
+ [maxpool]
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+ size=2
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+ stride=2
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+
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+ [dropout]
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+ probability=.5
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+
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+ [convolutional]
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+ batch_normalize=1
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+ filters=256
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+ size=3
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+ stride=1
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+ pad=1
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+ activation=leaky
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+ batch_normalize=1
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+ filters=256
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+ size=3
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+ stride=1
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+ pad=1
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+ activation=leaky
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+ [convolutional]
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+ batch_normalize=1
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+ filters=256
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+ size=3
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+ stride=1
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+ pad=1
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+ activation=leaky
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+
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+ [maxpool]
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+ size=2
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+ stride=2
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+
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+ [dropout]
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+ probability=.5
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+ [convolutional]
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+ batch_normalize=1
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+ filters=512
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+ size=3
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+ stride=1
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+ pad=1
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+ activation=leaky
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+ filters=512
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+ stride=1
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+ pad=1
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+ size=3
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+ pad=1
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+ [avgpool]
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+ [softmax]
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+ groups=1
model/cfg/cifar.test.cfg ADDED
@@ -0,0 +1,117 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [net]
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+ batch=128
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+ subdivisions=1
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+ height=32
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+ width=32
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+ channels=3
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+ momentum=0.9
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+ decay=0.0005
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+
10
+ learning_rate=0.4
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+ policy=poly
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+ power=4
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+ max_batches = 50000
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+
15
+
16
+ [convolutional]
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+ batch_normalize=1
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+ filters=128
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+ size=3
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+ stride=1
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+ pad=1
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+ activation=leaky
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+
24
+ [convolutional]
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+ batch_normalize=1
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+ filters=128
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+ size=3
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+ stride=1
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+ pad=1
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+ activation=leaky
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+
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+ [convolutional]
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+ batch_normalize=1
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+ filters=128
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+ size=3
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+ stride=1
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+ pad=1
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+ activation=leaky
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+
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+ [maxpool]
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+ size=2
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+ stride=2
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+
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+ [dropout]
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+ probability=.5
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+
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+ [convolutional]
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+ batch_normalize=1
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+ filters=256
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+ size=3
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+ stride=1
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+ pad=1
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+ activation=leaky
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+
55
+ [convolutional]
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+ batch_normalize=1
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+ filters=256
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+ size=3
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+ stride=1
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+ pad=1
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+ activation=leaky
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+
63
+ [convolutional]
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+ batch_normalize=1
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+ filters=256
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+ size=3
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+ stride=1
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+ pad=1
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+ activation=leaky
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+
71
+ [maxpool]
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+ size=2
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+ stride=2
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+
75
+ [dropout]
76
+ probability=.5
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+
78
+ [convolutional]
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+ batch_normalize=1
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+ filters=512
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+ size=3
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+ stride=1
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+ pad=1
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+ activation=leaky
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+
86
+ [convolutional]
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+ batch_normalize=1
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+ filters=512
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+ size=3
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+ stride=1
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+ pad=1
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+ activation=leaky
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+
94
+ [convolutional]
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+ batch_normalize=1
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+ filters=512
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+ size=3
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+ stride=1
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+ pad=1
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+ activation=leaky
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+
102
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+ probability=.5
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+
105
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106
+ filters=10
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+ size=1
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+ stride=1
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+ pad=1
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+ activation=leaky
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+
112
+ [avgpool]
113
+
114
+ [softmax]
115
+ groups=1
116
+ temperature=3
117
+
model/cfg/coco.data ADDED
@@ -0,0 +1,8 @@
 
 
 
 
 
 
 
 
 
1
+ classes= 80
2
+ train = /home/pjreddie/data/coco/trainvalno5k.txt
3
+ valid = coco_testdev
4
+ #valid = data/coco_val_5k.list
5
+ names = data/coco.names
6
+ backup = /home/pjreddie/backup/
7
+ eval=coco
8
+
model/cfg/combine9k.data ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
1
+ classes= 9418
2
+ #train = /home/pjreddie/data/coco/trainvalno5k.txt
3
+ train = data/combine9k.train.list
4
+ valid = /home/pjreddie/data/imagenet/det.val.files
5
+ labels = data/9k.labels
6
+ names = data/9k.names
7
+ backup = backup/
8
+ map = data/inet9k.map
9
+ eval = imagenet
10
+ results = results
model/cfg/darknet.cfg ADDED
@@ -0,0 +1,120 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [net]
2
+ # Training
3
+ # batch=128
4
+ # subdivisions=1
5
+ # Testing
6
+ batch=1
7
+ subdivisions=1
8
+ height=256
9
+ width=256
10
+ min_crop=128
11
+ max_crop=448
12
+ channels=3
13
+ momentum=0.9
14
+ decay=0.0005
15
+
16
+ burn_in=1000
17
+ learning_rate=0.1
18
+ policy=poly
19
+ power=4
20
+ max_batches=800000
21
+
22
+ angle=7
23
+ hue=.1
24
+ saturation=.75
25
+ exposure=.75
26
+ aspect=.75
27
+
28
+
29
+ [convolutional]
30
+ batch_normalize=1
31
+ filters=16
32
+ size=3
33
+ stride=1
34
+ pad=1
35
+ activation=leaky
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+
37
+ [maxpool]
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+ size=2
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+ stride=2
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+
41
+ [convolutional]
42
+ batch_normalize=1
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+ filters=32
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+ size=3
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+ stride=1
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+ pad=1
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+ activation=leaky
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+
49
+ [maxpool]
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+ size=2
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+ stride=2
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+
53
+ [convolutional]
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+ filters=64
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+ size=3
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+ stride=1
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+ pad=1
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+ activation=leaky
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+
61
+ [maxpool]
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+ size=2
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+ stride=2
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+
65
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+ filters=128
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+ stride=1
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+ pad=1
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73
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85
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+
97
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101
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+ stride=1
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+ pad=1
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+ activation=linear
117
+
118
+ [softmax]
119
+ groups=1
120
+
model/cfg/darknet19.cfg ADDED
@@ -0,0 +1,205 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [net]
2
+ # Training
3
+ #batch=128
4
+ #subdivisions=2
5
+
6
+ # Testing
7
+ batch=1
8
+ subdivisions=1
9
+
10
+ height=256
11
+ width=256
12
+ min_crop=128
13
+ max_crop=448
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+ channels=3
15
+ momentum=0.9
16
+ decay=0.0005
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+
18
+ burn_in=1000
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+ learning_rate=0.1
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+ policy=poly
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+ power=4
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+ max_batches=800000
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+
24
+ angle=7
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+ hue=.1
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+ saturation=.75
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+ exposure=.75
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+ aspect=.75
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+
30
+ [convolutional]
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+ batch_normalize=1
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+ filters=32
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+ size=3
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+ stride=1
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+ activation=leaky
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+
38
+ [maxpool]
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42
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+
50
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+
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+
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+ size=3
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+ stride=1
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+ activation=leaky
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+
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+ [maxpool]
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+
82
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+ stride=1
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+
90
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98
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134
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+
142
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+ stride=1
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+ pad=1
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+ activation=leaky
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+
150
+ [maxpool]
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+
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+ size=3
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+ filters=1024
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+ size=3
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+ stride=1
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+ pad=1
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+ activation=leaky
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+
178
+ [convolutional]
179
+ batch_normalize=1
180
+ filters=512
181
+ size=1
182
+ stride=1
183
+ pad=1
184
+ activation=leaky
185
+
186
+ [convolutional]
187
+ batch_normalize=1
188
+ filters=1024
189
+ size=3
190
+ stride=1
191
+ pad=1
192
+ activation=leaky
193
+
194
+ [convolutional]
195
+ filters=1000
196
+ size=1
197
+ stride=1
198
+ pad=1
199
+ activation=linear
200
+
201
+ [avgpool]
202
+
203
+ [softmax]
204
+ groups=1
205
+
model/cfg/darknet19_448.cfg ADDED
@@ -0,0 +1,197 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [net]
2
+ batch=128
3
+ subdivisions=4
4
+ height=448
5
+ width=448
6
+ max_crop=512
7
+ channels=3
8
+ momentum=0.9
9
+ decay=0.0005
10
+
11
+ learning_rate=0.001
12
+ policy=poly
13
+ power=4
14
+ max_batches=100000
15
+
16
+ angle=7
17
+ hue = .1
18
+ saturation=.75
19
+ exposure=.75
20
+ aspect=.75
21
+
22
+ [convolutional]
23
+ batch_normalize=1
24
+ filters=32
25
+ size=3
26
+ stride=1
27
+ pad=1
28
+ activation=leaky
29
+
30
+ [maxpool]
31
+ size=2
32
+ stride=2
33
+
34
+ [convolutional]
35
+ batch_normalize=1
36
+ filters=64
37
+ size=3
38
+ stride=1
39
+ pad=1
40
+ activation=leaky
41
+
42
+ [maxpool]
43
+ size=2
44
+ stride=2
45
+
46
+ [convolutional]
47
+ batch_normalize=1
48
+ filters=128
49
+ size=3
50
+ stride=1
51
+ pad=1
52
+ activation=leaky
53
+
54
+ [convolutional]
55
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56
+ filters=64
57
+ size=1
58
+ stride=1
59
+ pad=1
60
+ activation=leaky
61
+
62
+ [convolutional]
63
+ batch_normalize=1
64
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65
+ size=3
66
+ stride=1
67
+ pad=1
68
+ activation=leaky
69
+
70
+ [maxpool]
71
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72
+ stride=2
73
+
74
+ [convolutional]
75
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76
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77
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78
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79
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80
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81
+
82
+ [convolutional]
83
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84
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85
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86
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87
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89
+
90
+ [convolutional]
91
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92
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93
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94
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95
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96
+ activation=leaky
97
+
98
+ [maxpool]
99
+ size=2
100
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101
+
102
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103
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104
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105
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106
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107
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108
+ activation=leaky
109
+
110
+ [convolutional]
111
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112
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113
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114
+ stride=1
115
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116
+ activation=leaky
117
+
118
+ [convolutional]
119
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120
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121
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122
+ stride=1
123
+ pad=1
124
+ activation=leaky
125
+
126
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127
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128
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129
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130
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131
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132
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133
+
134
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135
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136
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137
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138
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139
+ pad=1
140
+ activation=leaky
141
+
142
+ [maxpool]
143
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144
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145
+
146
+ [convolutional]
147
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148
+ filters=1024
149
+ size=3
150
+ stride=1
151
+ pad=1
152
+ activation=leaky
153
+
154
+ [convolutional]
155
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156
+ filters=512
157
+ size=1
158
+ stride=1
159
+ pad=1
160
+ activation=leaky
161
+
162
+ [convolutional]
163
+ batch_normalize=1
164
+ filters=1024
165
+ size=3
166
+ stride=1
167
+ pad=1
168
+ activation=leaky
169
+
170
+ [convolutional]
171
+ batch_normalize=1
172
+ filters=512
173
+ size=1
174
+ stride=1
175
+ pad=1
176
+ activation=leaky
177
+
178
+ [convolutional]
179
+ batch_normalize=1
180
+ filters=1024
181
+ size=3
182
+ stride=1
183
+ pad=1
184
+ activation=leaky
185
+
186
+ [convolutional]
187
+ filters=1000
188
+ size=1
189
+ stride=1
190
+ pad=1
191
+ activation=linear
192
+
193
+ [avgpool]
194
+
195
+ [softmax]
196
+ groups=1
197
+
model/cfg/darknet53.cfg ADDED
@@ -0,0 +1,566 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [net]
2
+ # Training
3
+ # batch=128
4
+ # subdivisions=4
5
+
6
+ # Testing
7
+ batch=1
8
+ subdivisions=1
9
+
10
+ height=256
11
+ width=256
12
+ channels=3
13
+ min_crop=128
14
+ max_crop=448
15
+
16
+ burn_in=1000
17
+ learning_rate=0.1
18
+ policy=poly
19
+ power=4
20
+ max_batches=800000
21
+ momentum=0.9
22
+ decay=0.0005
23
+
24
+ angle=7
25
+ hue=.1
26
+ saturation=.75
27
+ exposure=.75
28
+ aspect=.75
29
+
30
+
31
+ [convolutional]
32
+ batch_normalize=1
33
+ filters=32
34
+ size=3
35
+ stride=1
36
+ pad=1
37
+ activation=leaky
38
+
39
+ # Downsample
40
+
41
+ [convolutional]
42
+ batch_normalize=1
43
+ filters=64
44
+ size=3
45
+ stride=2
46
+ pad=1
47
+ activation=leaky
48
+
49
+ [convolutional]
50
+ batch_normalize=1
51
+ filters=32
52
+ size=1
53
+ stride=1
54
+ pad=1
55
+ activation=leaky
56
+
57
+ [convolutional]
58
+ batch_normalize=1
59
+ filters=64
60
+ size=3
61
+ stride=1
62
+ pad=1
63
+ activation=leaky
64
+
65
+ [shortcut]
66
+ from=-3
67
+ activation=linear
68
+
69
+ # Downsample
70
+
71
+ [convolutional]
72
+ batch_normalize=1
73
+ filters=128
74
+ size=3
75
+ stride=2
76
+ pad=1
77
+ activation=leaky
78
+
79
+ [convolutional]
80
+ batch_normalize=1
81
+ filters=64
82
+ size=1
83
+ stride=1
84
+ pad=1
85
+ activation=leaky
86
+
87
+ [convolutional]
88
+ batch_normalize=1
89
+ filters=128
90
+ size=3
91
+ stride=1
92
+ pad=1
93
+ activation=leaky
94
+
95
+ [shortcut]
96
+ from=-3
97
+ activation=linear
98
+
99
+ [convolutional]
100
+ batch_normalize=1
101
+ filters=64
102
+ size=1
103
+ stride=1
104
+ pad=1
105
+ activation=leaky
106
+
107
+ [convolutional]
108
+ batch_normalize=1
109
+ filters=128
110
+ size=3
111
+ stride=1
112
+ pad=1
113
+ activation=leaky
114
+
115
+ [shortcut]
116
+ from=-3
117
+ activation=linear
118
+
119
+ # Downsample
120
+
121
+ [convolutional]
122
+ batch_normalize=1
123
+ filters=256
124
+ size=3
125
+ stride=2
126
+ pad=1
127
+ activation=leaky
128
+
129
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130
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131
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132
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133
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134
+ pad=1
135
+ activation=leaky
136
+
137
+ [convolutional]
138
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139
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140
+ size=3
141
+ stride=1
142
+ pad=1
143
+ activation=leaky
144
+
145
+ [shortcut]
146
+ from=-3
147
+ activation=linear
148
+
149
+ [convolutional]
150
+ batch_normalize=1
151
+ filters=128
152
+ size=1
153
+ stride=1
154
+ pad=1
155
+ activation=leaky
156
+
157
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158
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159
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160
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161
+ stride=1
162
+ pad=1
163
+ activation=leaky
164
+
165
+ [shortcut]
166
+ from=-3
167
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168
+
169
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170
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171
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172
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173
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174
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175
+ activation=leaky
176
+
177
+ [convolutional]
178
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179
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180
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181
+ stride=1
182
+ pad=1
183
+ activation=leaky
184
+
185
+ [shortcut]
186
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187
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188
+
189
+ [convolutional]
190
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191
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192
+ size=1
193
+ stride=1
194
+ pad=1
195
+ activation=leaky
196
+
197
+ [convolutional]
198
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199
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200
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201
+ stride=1
202
+ pad=1
203
+ activation=leaky
204
+
205
+ [shortcut]
206
+ from=-3
207
+ activation=linear
208
+
209
+
210
+ [convolutional]
211
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212
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213
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214
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215
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216
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217
+
218
+ [convolutional]
219
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220
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221
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222
+ stride=1
223
+ pad=1
224
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225
+
226
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227
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228
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229
+
230
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231
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232
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233
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234
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235
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236
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237
+
238
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239
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240
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241
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242
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243
+ pad=1
244
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245
+
246
+ [shortcut]
247
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248
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249
+
250
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251
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252
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253
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254
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255
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256
+ activation=leaky
257
+
258
+ [convolutional]
259
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260
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261
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262
+ stride=1
263
+ pad=1
264
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265
+
266
+ [shortcut]
267
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268
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269
+
270
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271
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272
+ filters=128
273
+ size=1
274
+ stride=1
275
+ pad=1
276
+ activation=leaky
277
+
278
+ [convolutional]
279
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280
+ filters=256
281
+ size=3
282
+ stride=1
283
+ pad=1
284
+ activation=leaky
285
+
286
+ [shortcut]
287
+ from=-3
288
+ activation=linear
289
+
290
+ # Downsample
291
+
292
+ [convolutional]
293
+ batch_normalize=1
294
+ filters=512
295
+ size=3
296
+ stride=2
297
+ pad=1
298
+ activation=leaky
299
+
300
+ [convolutional]
301
+ batch_normalize=1
302
+ filters=256
303
+ size=1
304
+ stride=1
305
+ pad=1
306
+ activation=leaky
307
+
308
+ [convolutional]
309
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310
+ filters=512
311
+ size=3
312
+ stride=1
313
+ pad=1
314
+ activation=leaky
315
+
316
+ [shortcut]
317
+ from=-3
318
+ activation=linear
319
+
320
+
321
+ [convolutional]
322
+ batch_normalize=1
323
+ filters=256
324
+ size=1
325
+ stride=1
326
+ pad=1
327
+ activation=leaky
328
+
329
+ [convolutional]
330
+ batch_normalize=1
331
+ filters=512
332
+ size=3
333
+ stride=1
334
+ pad=1
335
+ activation=leaky
336
+
337
+ [shortcut]
338
+ from=-3
339
+ activation=linear
340
+
341
+
342
+ [convolutional]
343
+ batch_normalize=1
344
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345
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346
+ stride=1
347
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348
+ activation=leaky
349
+
350
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351
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352
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353
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354
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355
+ pad=1
356
+ activation=leaky
357
+
358
+ [shortcut]
359
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360
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361
+
362
+
363
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364
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365
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366
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367
+ stride=1
368
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369
+ activation=leaky
370
+
371
+ [convolutional]
372
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373
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374
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375
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376
+ pad=1
377
+ activation=leaky
378
+
379
+ [shortcut]
380
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381
+ activation=linear
382
+
383
+ [convolutional]
384
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385
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386
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387
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388
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389
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390
+
391
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392
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393
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394
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395
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396
+ pad=1
397
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398
+
399
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400
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401
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402
+
403
+
404
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405
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406
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407
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408
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409
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410
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411
+
412
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413
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414
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415
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416
+ stride=1
417
+ pad=1
418
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419
+
420
+ [shortcut]
421
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422
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423
+
424
+
425
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427
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428
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429
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430
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431
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432
+
433
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434
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435
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436
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437
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438
+ pad=1
439
+ activation=leaky
440
+
441
+ [shortcut]
442
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443
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444
+
445
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446
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447
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448
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449
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450
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451
+ activation=leaky
452
+
453
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454
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455
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456
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457
+ stride=1
458
+ pad=1
459
+ activation=leaky
460
+
461
+ [shortcut]
462
+ from=-3
463
+ activation=linear
464
+
465
+ # Downsample
466
+
467
+ [convolutional]
468
+ batch_normalize=1
469
+ filters=1024
470
+ size=3
471
+ stride=2
472
+ pad=1
473
+ activation=leaky
474
+
475
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476
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477
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478
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479
+ stride=1
480
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481
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482
+
483
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484
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485
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486
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487
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488
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489
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490
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491
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492
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493
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494
+
495
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496
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497
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498
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499
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500
+ pad=1
501
+ activation=leaky
502
+
503
+ [convolutional]
504
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505
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506
+ size=3
507
+ stride=1
508
+ pad=1
509
+ activation=leaky
510
+
511
+ [shortcut]
512
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513
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514
+
515
+ [convolutional]
516
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517
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518
+ size=1
519
+ stride=1
520
+ pad=1
521
+ activation=leaky
522
+
523
+ [convolutional]
524
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525
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526
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527
+ stride=1
528
+ pad=1
529
+ activation=leaky
530
+
531
+ [shortcut]
532
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533
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534
+
535
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536
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537
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538
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539
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540
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541
+ activation=leaky
542
+
543
+ [convolutional]
544
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545
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546
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547
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548
+ pad=1
549
+ activation=leaky
550
+
551
+ [shortcut]
552
+ from=-3
553
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554
+
555
+ [avgpool]
556
+
557
+ [convolutional]
558
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559
+ size=1
560
+ stride=1
561
+ pad=1
562
+ activation=linear
563
+
564
+ [softmax]
565
+ groups=1
566
+
model/cfg/darknet53_448.cfg ADDED
@@ -0,0 +1,559 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [net]
2
+ # Training - start training with darknet53.weights
3
+ # batch=128
4
+ # subdivisions=8
5
+
6
+ # Testing
7
+ batch=1
8
+ subdivisions=1
9
+
10
+ height=448
11
+ width=448
12
+ channels=3
13
+ min_crop=448
14
+ max_crop=512
15
+
16
+ learning_rate=0.001
17
+ policy=poly
18
+ power=4
19
+ max_batches=100000
20
+ momentum=0.9
21
+ decay=0.0005
22
+
23
+
24
+ [convolutional]
25
+ batch_normalize=1
26
+ filters=32
27
+ size=3
28
+ stride=1
29
+ pad=1
30
+ activation=leaky
31
+
32
+ # Downsample
33
+
34
+ [convolutional]
35
+ batch_normalize=1
36
+ filters=64
37
+ size=3
38
+ stride=2
39
+ pad=1
40
+ activation=leaky
41
+
42
+ [convolutional]
43
+ batch_normalize=1
44
+ filters=32
45
+ size=1
46
+ stride=1
47
+ pad=1
48
+ activation=leaky
49
+
50
+ [convolutional]
51
+ batch_normalize=1
52
+ filters=64
53
+ size=3
54
+ stride=1
55
+ pad=1
56
+ activation=leaky
57
+
58
+ [shortcut]
59
+ from=-3
60
+ activation=linear
61
+
62
+ # Downsample
63
+
64
+ [convolutional]
65
+ batch_normalize=1
66
+ filters=128
67
+ size=3
68
+ stride=2
69
+ pad=1
70
+ activation=leaky
71
+
72
+ [convolutional]
73
+ batch_normalize=1
74
+ filters=64
75
+ size=1
76
+ stride=1
77
+ pad=1
78
+ activation=leaky
79
+
80
+ [convolutional]
81
+ batch_normalize=1
82
+ filters=128
83
+ size=3
84
+ stride=1
85
+ pad=1
86
+ activation=leaky
87
+
88
+ [shortcut]
89
+ from=-3
90
+ activation=linear
91
+
92
+ [convolutional]
93
+ batch_normalize=1
94
+ filters=64
95
+ size=1
96
+ stride=1
97
+ pad=1
98
+ activation=leaky
99
+
100
+ [convolutional]
101
+ batch_normalize=1
102
+ filters=128
103
+ size=3
104
+ stride=1
105
+ pad=1
106
+ activation=leaky
107
+
108
+ [shortcut]
109
+ from=-3
110
+ activation=linear
111
+
112
+ # Downsample
113
+
114
+ [convolutional]
115
+ batch_normalize=1
116
+ filters=256
117
+ size=3
118
+ stride=2
119
+ pad=1
120
+ activation=leaky
121
+
122
+ [convolutional]
123
+ batch_normalize=1
124
+ filters=128
125
+ size=1
126
+ stride=1
127
+ pad=1
128
+ activation=leaky
129
+
130
+ [convolutional]
131
+ batch_normalize=1
132
+ filters=256
133
+ size=3
134
+ stride=1
135
+ pad=1
136
+ activation=leaky
137
+
138
+ [shortcut]
139
+ from=-3
140
+ activation=linear
141
+
142
+ [convolutional]
143
+ batch_normalize=1
144
+ filters=128
145
+ size=1
146
+ stride=1
147
+ pad=1
148
+ activation=leaky
149
+
150
+ [convolutional]
151
+ batch_normalize=1
152
+ filters=256
153
+ size=3
154
+ stride=1
155
+ pad=1
156
+ activation=leaky
157
+
158
+ [shortcut]
159
+ from=-3
160
+ activation=linear
161
+
162
+ [convolutional]
163
+ batch_normalize=1
164
+ filters=128
165
+ size=1
166
+ stride=1
167
+ pad=1
168
+ activation=leaky
169
+
170
+ [convolutional]
171
+ batch_normalize=1
172
+ filters=256
173
+ size=3
174
+ stride=1
175
+ pad=1
176
+ activation=leaky
177
+
178
+ [shortcut]
179
+ from=-3
180
+ activation=linear
181
+
182
+ [convolutional]
183
+ batch_normalize=1
184
+ filters=128
185
+ size=1
186
+ stride=1
187
+ pad=1
188
+ activation=leaky
189
+
190
+ [convolutional]
191
+ batch_normalize=1
192
+ filters=256
193
+ size=3
194
+ stride=1
195
+ pad=1
196
+ activation=leaky
197
+
198
+ [shortcut]
199
+ from=-3
200
+ activation=linear
201
+
202
+
203
+ [convolutional]
204
+ batch_normalize=1
205
+ filters=128
206
+ size=1
207
+ stride=1
208
+ pad=1
209
+ activation=leaky
210
+
211
+ [convolutional]
212
+ batch_normalize=1
213
+ filters=256
214
+ size=3
215
+ stride=1
216
+ pad=1
217
+ activation=leaky
218
+
219
+ [shortcut]
220
+ from=-3
221
+ activation=linear
222
+
223
+ [convolutional]
224
+ batch_normalize=1
225
+ filters=128
226
+ size=1
227
+ stride=1
228
+ pad=1
229
+ activation=leaky
230
+
231
+ [convolutional]
232
+ batch_normalize=1
233
+ filters=256
234
+ size=3
235
+ stride=1
236
+ pad=1
237
+ activation=leaky
238
+
239
+ [shortcut]
240
+ from=-3
241
+ activation=linear
242
+
243
+ [convolutional]
244
+ batch_normalize=1
245
+ filters=128
246
+ size=1
247
+ stride=1
248
+ pad=1
249
+ activation=leaky
250
+
251
+ [convolutional]
252
+ batch_normalize=1
253
+ filters=256
254
+ size=3
255
+ stride=1
256
+ pad=1
257
+ activation=leaky
258
+
259
+ [shortcut]
260
+ from=-3
261
+ activation=linear
262
+
263
+ [convolutional]
264
+ batch_normalize=1
265
+ filters=128
266
+ size=1
267
+ stride=1
268
+ pad=1
269
+ activation=leaky
270
+
271
+ [convolutional]
272
+ batch_normalize=1
273
+ filters=256
274
+ size=3
275
+ stride=1
276
+ pad=1
277
+ activation=leaky
278
+
279
+ [shortcut]
280
+ from=-3
281
+ activation=linear
282
+
283
+ # Downsample
284
+
285
+ [convolutional]
286
+ batch_normalize=1
287
+ filters=512
288
+ size=3
289
+ stride=2
290
+ pad=1
291
+ activation=leaky
292
+
293
+ [convolutional]
294
+ batch_normalize=1
295
+ filters=256
296
+ size=1
297
+ stride=1
298
+ pad=1
299
+ activation=leaky
300
+
301
+ [convolutional]
302
+ batch_normalize=1
303
+ filters=512
304
+ size=3
305
+ stride=1
306
+ pad=1
307
+ activation=leaky
308
+
309
+ [shortcut]
310
+ from=-3
311
+ activation=linear
312
+
313
+
314
+ [convolutional]
315
+ batch_normalize=1
316
+ filters=256
317
+ size=1
318
+ stride=1
319
+ pad=1
320
+ activation=leaky
321
+
322
+ [convolutional]
323
+ batch_normalize=1
324
+ filters=512
325
+ size=3
326
+ stride=1
327
+ pad=1
328
+ activation=leaky
329
+
330
+ [shortcut]
331
+ from=-3
332
+ activation=linear
333
+
334
+
335
+ [convolutional]
336
+ batch_normalize=1
337
+ filters=256
338
+ size=1
339
+ stride=1
340
+ pad=1
341
+ activation=leaky
342
+
343
+ [convolutional]
344
+ batch_normalize=1
345
+ filters=512
346
+ size=3
347
+ stride=1
348
+ pad=1
349
+ activation=leaky
350
+
351
+ [shortcut]
352
+ from=-3
353
+ activation=linear
354
+
355
+
356
+ [convolutional]
357
+ batch_normalize=1
358
+ filters=256
359
+ size=1
360
+ stride=1
361
+ pad=1
362
+ activation=leaky
363
+
364
+ [convolutional]
365
+ batch_normalize=1
366
+ filters=512
367
+ size=3
368
+ stride=1
369
+ pad=1
370
+ activation=leaky
371
+
372
+ [shortcut]
373
+ from=-3
374
+ activation=linear
375
+
376
+ [convolutional]
377
+ batch_normalize=1
378
+ filters=256
379
+ size=1
380
+ stride=1
381
+ pad=1
382
+ activation=leaky
383
+
384
+ [convolutional]
385
+ batch_normalize=1
386
+ filters=512
387
+ size=3
388
+ stride=1
389
+ pad=1
390
+ activation=leaky
391
+
392
+ [shortcut]
393
+ from=-3
394
+ activation=linear
395
+
396
+
397
+ [convolutional]
398
+ batch_normalize=1
399
+ filters=256
400
+ size=1
401
+ stride=1
402
+ pad=1
403
+ activation=leaky
404
+
405
+ [convolutional]
406
+ batch_normalize=1
407
+ filters=512
408
+ size=3
409
+ stride=1
410
+ pad=1
411
+ activation=leaky
412
+
413
+ [shortcut]
414
+ from=-3
415
+ activation=linear
416
+
417
+
418
+ [convolutional]
419
+ batch_normalize=1
420
+ filters=256
421
+ size=1
422
+ stride=1
423
+ pad=1
424
+ activation=leaky
425
+
426
+ [convolutional]
427
+ batch_normalize=1
428
+ filters=512
429
+ size=3
430
+ stride=1
431
+ pad=1
432
+ activation=leaky
433
+
434
+ [shortcut]
435
+ from=-3
436
+ activation=linear
437
+
438
+ [convolutional]
439
+ batch_normalize=1
440
+ filters=256
441
+ size=1
442
+ stride=1
443
+ pad=1
444
+ activation=leaky
445
+
446
+ [convolutional]
447
+ batch_normalize=1
448
+ filters=512
449
+ size=3
450
+ stride=1
451
+ pad=1
452
+ activation=leaky
453
+
454
+ [shortcut]
455
+ from=-3
456
+ activation=linear
457
+
458
+ # Downsample
459
+
460
+ [convolutional]
461
+ batch_normalize=1
462
+ filters=1024
463
+ size=3
464
+ stride=2
465
+ pad=1
466
+ activation=leaky
467
+
468
+ [convolutional]
469
+ batch_normalize=1
470
+ filters=512
471
+ size=1
472
+ stride=1
473
+ pad=1
474
+ activation=leaky
475
+
476
+ [convolutional]
477
+ batch_normalize=1
478
+ filters=1024
479
+ size=3
480
+ stride=1
481
+ pad=1
482
+ activation=leaky
483
+
484
+ [shortcut]
485
+ from=-3
486
+ activation=linear
487
+
488
+ [convolutional]
489
+ batch_normalize=1
490
+ filters=512
491
+ size=1
492
+ stride=1
493
+ pad=1
494
+ activation=leaky
495
+
496
+ [convolutional]
497
+ batch_normalize=1
498
+ filters=1024
499
+ size=3
500
+ stride=1
501
+ pad=1
502
+ activation=leaky
503
+
504
+ [shortcut]
505
+ from=-3
506
+ activation=linear
507
+
508
+ [convolutional]
509
+ batch_normalize=1
510
+ filters=512
511
+ size=1
512
+ stride=1
513
+ pad=1
514
+ activation=leaky
515
+
516
+ [convolutional]
517
+ batch_normalize=1
518
+ filters=1024
519
+ size=3
520
+ stride=1
521
+ pad=1
522
+ activation=leaky
523
+
524
+ [shortcut]
525
+ from=-3
526
+ activation=linear
527
+
528
+ [convolutional]
529
+ batch_normalize=1
530
+ filters=512
531
+ size=1
532
+ stride=1
533
+ pad=1
534
+ activation=leaky
535
+
536
+ [convolutional]
537
+ batch_normalize=1
538
+ filters=1024
539
+ size=3
540
+ stride=1
541
+ pad=1
542
+ activation=leaky
543
+
544
+ [shortcut]
545
+ from=-3
546
+ activation=linear
547
+
548
+ [avgpool]
549
+
550
+ [convolutional]
551
+ filters=1000
552
+ size=1
553
+ stride=1
554
+ pad=1
555
+ activation=linear
556
+
557
+ [softmax]
558
+ groups=1
559
+
model/cfg/darknet9000.cfg ADDED
@@ -0,0 +1,205 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [net]
2
+ # Training
3
+ # batch=128
4
+ # subdivisions=4
5
+ # Testing
6
+ batch = 1
7
+ subdivisions = 1
8
+ height=448
9
+ width=448
10
+ max_crop=512
11
+ channels=3
12
+ momentum=0.9
13
+ decay=0.0005
14
+
15
+ learning_rate=0.001
16
+ policy=poly
17
+ power=4
18
+ max_batches=100000
19
+
20
+ angle=7
21
+ hue=.1
22
+ saturation=.75
23
+ exposure=.75
24
+ aspect=.75
25
+
26
+ [convolutional]
27
+ batch_normalize=1
28
+ filters=32
29
+ size=3
30
+ stride=1
31
+ pad=1
32
+ activation=leaky
33
+
34
+ [maxpool]
35
+ size=2
36
+ stride=2
37
+
38
+ [convolutional]
39
+ batch_normalize=1
40
+ filters=64
41
+ size=3
42
+ stride=1
43
+ pad=1
44
+ activation=leaky
45
+
46
+ [maxpool]
47
+ size=2
48
+ stride=2
49
+
50
+ [convolutional]
51
+ batch_normalize=1
52
+ filters=128
53
+ size=3
54
+ stride=1
55
+ pad=1
56
+ activation=leaky
57
+
58
+ [convolutional]
59
+ batch_normalize=1
60
+ filters=64
61
+ size=1
62
+ stride=1
63
+ pad=1
64
+ activation=leaky
65
+
66
+ [convolutional]
67
+ batch_normalize=1
68
+ filters=128
69
+ size=3
70
+ stride=1
71
+ pad=1
72
+ activation=leaky
73
+
74
+ [maxpool]
75
+ size=2
76
+ stride=2
77
+
78
+ [convolutional]
79
+ batch_normalize=1
80
+ filters=256
81
+ size=3
82
+ stride=1
83
+ pad=1
84
+ activation=leaky
85
+
86
+ [convolutional]
87
+ batch_normalize=1
88
+ filters=128
89
+ size=1
90
+ stride=1
91
+ pad=1
92
+ activation=leaky
93
+
94
+ [convolutional]
95
+ batch_normalize=1
96
+ filters=256
97
+ size=3
98
+ stride=1
99
+ pad=1
100
+ activation=leaky
101
+
102
+ [maxpool]
103
+ size=2
104
+ stride=2
105
+
106
+ [convolutional]
107
+ batch_normalize=1
108
+ filters=512
109
+ size=3
110
+ stride=1
111
+ pad=1
112
+ activation=leaky
113
+
114
+ [convolutional]
115
+ batch_normalize=1
116
+ filters=256
117
+ size=1
118
+ stride=1
119
+ pad=1
120
+ activation=leaky
121
+
122
+ [convolutional]
123
+ batch_normalize=1
124
+ filters=512
125
+ size=3
126
+ stride=1
127
+ pad=1
128
+ activation=leaky
129
+
130
+ [convolutional]
131
+ batch_normalize=1
132
+ filters=256
133
+ size=1
134
+ stride=1
135
+ pad=1
136
+ activation=leaky
137
+
138
+ [convolutional]
139
+ batch_normalize=1
140
+ filters=512
141
+ size=3
142
+ stride=1
143
+ pad=1
144
+ activation=leaky
145
+
146
+ [maxpool]
147
+ size=2
148
+ stride=2
149
+
150
+ [convolutional]
151
+ batch_normalize=1
152
+ filters=1024
153
+ size=3
154
+ stride=1
155
+ pad=1
156
+ activation=leaky
157
+
158
+ [convolutional]
159
+ batch_normalize=1
160
+ filters=512
161
+ size=1
162
+ stride=1
163
+ pad=1
164
+ activation=leaky
165
+
166
+ [convolutional]
167
+ batch_normalize=1
168
+ filters=1024
169
+ size=3
170
+ stride=1
171
+ pad=1
172
+ activation=leaky
173
+
174
+ [convolutional]
175
+ batch_normalize=1
176
+ filters=512
177
+ size=1
178
+ stride=1
179
+ pad=1
180
+ activation=leaky
181
+
182
+ [convolutional]
183
+ batch_normalize=1
184
+ filters=1024
185
+ size=3
186
+ stride=1
187
+ pad=1
188
+ activation=leaky
189
+
190
+ [convolutional]
191
+ filters=9418
192
+ size=1
193
+ stride=1
194
+ pad=1
195
+ activation=linear
196
+
197
+ [avgpool]
198
+
199
+ [softmax]
200
+ groups=1
201
+ tree=data/9k.tree
202
+
203
+ [cost]
204
+ type=masked
205
+
model/cfg/densenet201.cfg ADDED
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+ [convolutional]
1492
+ batch_normalize=1
1493
+ filters=32
1494
+ size=3
1495
+ stride=1
1496
+ pad=1
1497
+ activation=leaky
1498
+
1499
+ [route]
1500
+ layers=-1,-3
1501
+
1502
+ [convolutional]
1503
+ batch_normalize=1
1504
+ filters=128
1505
+ size=1
1506
+ stride=1
1507
+ pad=1
1508
+ activation=leaky
1509
+
1510
+ [convolutional]
1511
+ batch_normalize=1
1512
+ filters=32
1513
+ size=3
1514
+ stride=1
1515
+ pad=1
1516
+ activation=leaky
1517
+
1518
+ [route]
1519
+ layers=-1,-3
1520
+
1521
+ [convolutional]
1522
+ batch_normalize=1
1523
+ filters=128
1524
+ size=1
1525
+ stride=1
1526
+ pad=1
1527
+ activation=leaky
1528
+
1529
+ [convolutional]
1530
+ batch_normalize=1
1531
+ filters=32
1532
+ size=3
1533
+ stride=1
1534
+ pad=1
1535
+ activation=leaky
1536
+
1537
+ [route]
1538
+ layers=-1,-3
1539
+
1540
+ [convolutional]
1541
+ batch_normalize=1
1542
+ filters=128
1543
+ size=1
1544
+ stride=1
1545
+ pad=1
1546
+ activation=leaky
1547
+
1548
+ [convolutional]
1549
+ batch_normalize=1
1550
+ filters=32
1551
+ size=3
1552
+ stride=1
1553
+ pad=1
1554
+ activation=leaky
1555
+
1556
+ [route]
1557
+ layers=-1,-3
1558
+
1559
+ [convolutional]
1560
+ batch_normalize=1
1561
+ filters=128
1562
+ size=1
1563
+ stride=1
1564
+ pad=1
1565
+ activation=leaky
1566
+
1567
+ [convolutional]
1568
+ batch_normalize=1
1569
+ filters=32
1570
+ size=3
1571
+ stride=1
1572
+ pad=1
1573
+ activation=leaky
1574
+
1575
+ [route]
1576
+ layers=-1,-3
1577
+
1578
+ [convolutional]
1579
+ batch_normalize=1
1580
+ filters=128
1581
+ size=1
1582
+ stride=1
1583
+ pad=1
1584
+ activation=leaky
1585
+
1586
+ [convolutional]
1587
+ batch_normalize=1
1588
+ filters=32
1589
+ size=3
1590
+ stride=1
1591
+ pad=1
1592
+ activation=leaky
1593
+
1594
+ [route]
1595
+ layers=-1,-3
1596
+
1597
+ [convolutional]
1598
+ batch_normalize=1
1599
+ filters=128
1600
+ size=1
1601
+ stride=1
1602
+ pad=1
1603
+ activation=leaky
1604
+
1605
+ [convolutional]
1606
+ batch_normalize=1
1607
+ filters=32
1608
+ size=3
1609
+ stride=1
1610
+ pad=1
1611
+ activation=leaky
1612
+
1613
+ [route]
1614
+ layers=-1,-3
1615
+
1616
+ [convolutional]
1617
+ batch_normalize=1
1618
+ filters=128
1619
+ size=1
1620
+ stride=1
1621
+ pad=1
1622
+ activation=leaky
1623
+
1624
+ [convolutional]
1625
+ batch_normalize=1
1626
+ filters=32
1627
+ size=3
1628
+ stride=1
1629
+ pad=1
1630
+ activation=leaky
1631
+
1632
+ [route]
1633
+ layers=-1,-3
1634
+
1635
+ [convolutional]
1636
+ batch_normalize=1
1637
+ filters=128
1638
+ size=1
1639
+ stride=1
1640
+ pad=1
1641
+ activation=leaky
1642
+
1643
+ [convolutional]
1644
+ batch_normalize=1
1645
+ filters=32
1646
+ size=3
1647
+ stride=1
1648
+ pad=1
1649
+ activation=leaky
1650
+
1651
+ [route]
1652
+ layers=-1,-3
1653
+
1654
+ [convolutional]
1655
+ batch_normalize=1
1656
+ filters=128
1657
+ size=1
1658
+ stride=1
1659
+ pad=1
1660
+ activation=leaky
1661
+
1662
+ [convolutional]
1663
+ batch_normalize=1
1664
+ filters=32
1665
+ size=3
1666
+ stride=1
1667
+ pad=1
1668
+ activation=leaky
1669
+
1670
+ [route]
1671
+ layers=-1,-3
1672
+
1673
+ [convolutional]
1674
+ batch_normalize=1
1675
+ filters=128
1676
+ size=1
1677
+ stride=1
1678
+ pad=1
1679
+ activation=leaky
1680
+
1681
+ [convolutional]
1682
+ batch_normalize=1
1683
+ filters=32
1684
+ size=3
1685
+ stride=1
1686
+ pad=1
1687
+ activation=leaky
1688
+
1689
+ [route]
1690
+ layers=-1,-3
1691
+
1692
+ [convolutional]
1693
+ batch_normalize=1
1694
+ filters=128
1695
+ size=1
1696
+ stride=1
1697
+ pad=1
1698
+ activation=leaky
1699
+
1700
+ [convolutional]
1701
+ batch_normalize=1
1702
+ filters=32
1703
+ size=3
1704
+ stride=1
1705
+ pad=1
1706
+ activation=leaky
1707
+
1708
+ [route]
1709
+ layers=-1,-3
1710
+
1711
+ [convolutional]
1712
+ batch_normalize=1
1713
+ filters=128
1714
+ size=1
1715
+ stride=1
1716
+ pad=1
1717
+ activation=leaky
1718
+
1719
+ [convolutional]
1720
+ batch_normalize=1
1721
+ filters=32
1722
+ size=3
1723
+ stride=1
1724
+ pad=1
1725
+ activation=leaky
1726
+
1727
+ [route]
1728
+ layers=-1,-3
1729
+
1730
+ [convolutional]
1731
+ batch_normalize=1
1732
+ filters=128
1733
+ size=1
1734
+ stride=1
1735
+ pad=1
1736
+ activation=leaky
1737
+
1738
+ [convolutional]
1739
+ batch_normalize=1
1740
+ filters=32
1741
+ size=3
1742
+ stride=1
1743
+ pad=1
1744
+ activation=leaky
1745
+
1746
+ [route]
1747
+ layers=-1,-3
1748
+
1749
+ [convolutional]
1750
+ batch_normalize=1
1751
+ filters=128
1752
+ size=1
1753
+ stride=1
1754
+ pad=1
1755
+ activation=leaky
1756
+
1757
+ [convolutional]
1758
+ batch_normalize=1
1759
+ filters=32
1760
+ size=3
1761
+ stride=1
1762
+ pad=1
1763
+ activation=leaky
1764
+
1765
+ [route]
1766
+ layers=-1,-3
1767
+
1768
+ [convolutional]
1769
+ batch_normalize=1
1770
+ filters=128
1771
+ size=1
1772
+ stride=1
1773
+ pad=1
1774
+ activation=leaky
1775
+
1776
+ [convolutional]
1777
+ batch_normalize=1
1778
+ filters=32
1779
+ size=3
1780
+ stride=1
1781
+ pad=1
1782
+ activation=leaky
1783
+
1784
+ [route]
1785
+ layers=-1,-3
1786
+
1787
+ [convolutional]
1788
+ batch_normalize=1
1789
+ filters=128
1790
+ size=1
1791
+ stride=1
1792
+ pad=1
1793
+ activation=leaky
1794
+
1795
+ [convolutional]
1796
+ batch_normalize=1
1797
+ filters=32
1798
+ size=3
1799
+ stride=1
1800
+ pad=1
1801
+ activation=leaky
1802
+
1803
+ [route]
1804
+ layers=-1,-3
1805
+
1806
+ [convolutional]
1807
+ batch_normalize=1
1808
+ filters=128
1809
+ size=1
1810
+ stride=1
1811
+ pad=1
1812
+ activation=leaky
1813
+
1814
+ [convolutional]
1815
+ batch_normalize=1
1816
+ filters=32
1817
+ size=3
1818
+ stride=1
1819
+ pad=1
1820
+ activation=leaky
1821
+
1822
+ [route]
1823
+ layers=-1,-3
1824
+
1825
+ [convolutional]
1826
+ batch_normalize=1
1827
+ filters=128
1828
+ size=1
1829
+ stride=1
1830
+ pad=1
1831
+ activation=leaky
1832
+
1833
+ [convolutional]
1834
+ batch_normalize=1
1835
+ filters=32
1836
+ size=3
1837
+ stride=1
1838
+ pad=1
1839
+ activation=leaky
1840
+
1841
+ [route]
1842
+ layers=-1,-3
1843
+
1844
+ [convolutional]
1845
+ batch_normalize=1
1846
+ filters=128
1847
+ size=1
1848
+ stride=1
1849
+ pad=1
1850
+ activation=leaky
1851
+
1852
+ [convolutional]
1853
+ batch_normalize=1
1854
+ filters=32
1855
+ size=3
1856
+ stride=1
1857
+ pad=1
1858
+ activation=leaky
1859
+
1860
+ [route]
1861
+ layers=-1,-3
1862
+
1863
+ [convolutional]
1864
+ batch_normalize=1
1865
+ filters=128
1866
+ size=1
1867
+ stride=1
1868
+ pad=1
1869
+ activation=leaky
1870
+
1871
+ [convolutional]
1872
+ batch_normalize=1
1873
+ filters=32
1874
+ size=3
1875
+ stride=1
1876
+ pad=1
1877
+ activation=leaky
1878
+
1879
+ [route]
1880
+ layers=-1,-3
1881
+
1882
+ [convolutional]
1883
+ batch_normalize=1
1884
+ filters=128
1885
+ size=1
1886
+ stride=1
1887
+ pad=1
1888
+ activation=leaky
1889
+
1890
+ [convolutional]
1891
+ batch_normalize=1
1892
+ filters=32
1893
+ size=3
1894
+ stride=1
1895
+ pad=1
1896
+ activation=leaky
1897
+
1898
+ [route]
1899
+ layers=-1,-3
1900
+
1901
+ [convolutional]
1902
+ batch_normalize=1
1903
+ filters=128
1904
+ size=1
1905
+ stride=1
1906
+ pad=1
1907
+ activation=leaky
1908
+
1909
+ [convolutional]
1910
+ batch_normalize=1
1911
+ filters=32
1912
+ size=3
1913
+ stride=1
1914
+ pad=1
1915
+ activation=leaky
1916
+
1917
+ [route]
1918
+ layers=-1,-3
1919
+
1920
+ [convolutional]
1921
+ batch_normalize=1
1922
+ filters=128
1923
+ size=1
1924
+ stride=1
1925
+ pad=1
1926
+ activation=leaky
1927
+
1928
+ [convolutional]
1929
+ batch_normalize=1
1930
+ filters=32
1931
+ size=3
1932
+ stride=1
1933
+ pad=1
1934
+ activation=leaky
1935
+
1936
+ [route]
1937
+ layers=-1,-3
1938
+
1939
+
1940
+ [convolutional]
1941
+ filters=1000
1942
+ size=1
1943
+ stride=1
1944
+ pad=1
1945
+ activation=linear
1946
+
1947
+ [avgpool]
1948
+
1949
+ [softmax]
1950
+ groups=1
1951
+
model/cfg/extraction.cfg ADDED
@@ -0,0 +1,209 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [net]
2
+ # Training
3
+ # batch=128
4
+ # subdivisions=4
5
+
6
+ # Testing
7
+ batch=1
8
+ subdivisions=1
9
+
10
+ height=224
11
+ width=224
12
+ max_crop=320
13
+ channels=3
14
+ momentum=0.9
15
+ decay=0.0005
16
+
17
+ learning_rate=0.1
18
+ policy=poly
19
+ power=4
20
+ max_batches=1600000
21
+
22
+ [convolutional]
23
+ batch_normalize=1
24
+ filters=64
25
+ size=7
26
+ stride=2
27
+ pad=1
28
+ activation=leaky
29
+
30
+ [maxpool]
31
+ size=2
32
+ stride=2
33
+
34
+ [convolutional]
35
+ batch_normalize=1
36
+ filters=192
37
+ size=3
38
+ stride=1
39
+ pad=1
40
+ activation=leaky
41
+
42
+ [maxpool]
43
+ size=2
44
+ stride=2
45
+
46
+ [convolutional]
47
+ batch_normalize=1
48
+ filters=128
49
+ size=1
50
+ stride=1
51
+ pad=1
52
+ activation=leaky
53
+
54
+ [convolutional]
55
+ batch_normalize=1
56
+ filters=256
57
+ size=3
58
+ stride=1
59
+ pad=1
60
+ activation=leaky
61
+
62
+ [convolutional]
63
+ batch_normalize=1
64
+ filters=256
65
+ size=1
66
+ stride=1
67
+ pad=1
68
+ activation=leaky
69
+
70
+ [convolutional]
71
+ batch_normalize=1
72
+ filters=512
73
+ size=3
74
+ stride=1
75
+ pad=1
76
+ activation=leaky
77
+
78
+ [maxpool]
79
+ size=2
80
+ stride=2
81
+
82
+ [convolutional]
83
+ batch_normalize=1
84
+ filters=256
85
+ size=1
86
+ stride=1
87
+ pad=1
88
+ activation=leaky
89
+
90
+ [convolutional]
91
+ batch_normalize=1
92
+ filters=512
93
+ size=3
94
+ stride=1
95
+ pad=1
96
+ activation=leaky
97
+
98
+ [convolutional]
99
+ batch_normalize=1
100
+ filters=256
101
+ size=1
102
+ stride=1
103
+ pad=1
104
+ activation=leaky
105
+
106
+ [convolutional]
107
+ batch_normalize=1
108
+ filters=512
109
+ size=3
110
+ stride=1
111
+ pad=1
112
+ activation=leaky
113
+
114
+ [convolutional]
115
+ batch_normalize=1
116
+ filters=256
117
+ size=1
118
+ stride=1
119
+ pad=1
120
+ activation=leaky
121
+
122
+ [convolutional]
123
+ batch_normalize=1
124
+ filters=512
125
+ size=3
126
+ stride=1
127
+ pad=1
128
+ activation=leaky
129
+
130
+ [convolutional]
131
+ batch_normalize=1
132
+ filters=256
133
+ size=1
134
+ stride=1
135
+ pad=1
136
+ activation=leaky
137
+
138
+ [convolutional]
139
+ batch_normalize=1
140
+ filters=512
141
+ size=3
142
+ stride=1
143
+ pad=1
144
+ activation=leaky
145
+
146
+ [convolutional]
147
+ batch_normalize=1
148
+ filters=512
149
+ size=1
150
+ stride=1
151
+ pad=1
152
+ activation=leaky
153
+
154
+ [convolutional]
155
+ batch_normalize=1
156
+ filters=1024
157
+ size=3
158
+ stride=1
159
+ pad=1
160
+ activation=leaky
161
+
162
+ [maxpool]
163
+ size=2
164
+ stride=2
165
+
166
+ [convolutional]
167
+ batch_normalize=1
168
+ filters=512
169
+ size=1
170
+ stride=1
171
+ pad=1
172
+ activation=leaky
173
+
174
+ [convolutional]
175
+ batch_normalize=1
176
+ filters=1024
177
+ size=3
178
+ stride=1
179
+ pad=1
180
+ activation=leaky
181
+
182
+ [convolutional]
183
+ batch_normalize=1
184
+ filters=512
185
+ size=1
186
+ stride=1
187
+ pad=1
188
+ activation=leaky
189
+
190
+ [convolutional]
191
+ batch_normalize=1
192
+ filters=1024
193
+ size=3
194
+ stride=1
195
+ pad=1
196
+ activation=leaky
197
+
198
+ [convolutional]
199
+ filters=1000
200
+ size=1
201
+ stride=1
202
+ pad=1
203
+ activation=leaky
204
+
205
+ [avgpool]
206
+
207
+ [softmax]
208
+ groups=1
209
+
model/cfg/extraction.conv.cfg ADDED
@@ -0,0 +1,179 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [net]
2
+ batch=1
3
+ subdivisions=1
4
+ height=256
5
+ width=256
6
+ channels=3
7
+ momentum=0.9
8
+ decay=0.0005
9
+
10
+ learning_rate=0.5
11
+ policy=poly
12
+ power=6
13
+ max_batches=500000
14
+
15
+ [convolutional]
16
+ filters=64
17
+ size=7
18
+ stride=2
19
+ pad=1
20
+ activation=leaky
21
+
22
+ [maxpool]
23
+ size=2
24
+ stride=2
25
+
26
+ [convolutional]
27
+ filters=192
28
+ size=3
29
+ stride=1
30
+ pad=1
31
+ activation=leaky
32
+
33
+ [maxpool]
34
+ size=2
35
+ stride=2
36
+
37
+ [convolutional]
38
+ filters=128
39
+ size=1
40
+ stride=1
41
+ pad=1
42
+ activation=leaky
43
+
44
+ [convolutional]
45
+ filters=256
46
+ size=3
47
+ stride=1
48
+ pad=1
49
+ activation=leaky
50
+
51
+ [convolutional]
52
+ filters=256
53
+ size=1
54
+ stride=1
55
+ pad=1
56
+ activation=leaky
57
+
58
+ [convolutional]
59
+ filters=512
60
+ size=3
61
+ stride=1
62
+ pad=1
63
+ activation=leaky
64
+
65
+ [maxpool]
66
+ size=2
67
+ stride=2
68
+
69
+ [convolutional]
70
+ filters=256
71
+ size=1
72
+ stride=1
73
+ pad=1
74
+ activation=leaky
75
+
76
+ [convolutional]
77
+ filters=512
78
+ size=3
79
+ stride=1
80
+ pad=1
81
+ activation=leaky
82
+
83
+ [convolutional]
84
+ filters=256
85
+ size=1
86
+ stride=1
87
+ pad=1
88
+ activation=leaky
89
+
90
+ [convolutional]
91
+ filters=512
92
+ size=3
93
+ stride=1
94
+ pad=1
95
+ activation=leaky
96
+
97
+ [convolutional]
98
+ filters=256
99
+ size=1
100
+ stride=1
101
+ pad=1
102
+ activation=leaky
103
+
104
+ [convolutional]
105
+ filters=512
106
+ size=3
107
+ stride=1
108
+ pad=1
109
+ activation=leaky
110
+
111
+ [convolutional]
112
+ filters=256
113
+ size=1
114
+ stride=1
115
+ pad=1
116
+ activation=leaky
117
+
118
+ [convolutional]
119
+ filters=512
120
+ size=3
121
+ stride=1
122
+ pad=1
123
+ activation=leaky
124
+
125
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model/cfg/go.cfg ADDED
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model/cfg/go.test.cfg ADDED
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model/cfg/gru.cfg ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
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model/cfg/imagenet1k.data ADDED
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1
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model/cfg/imagenet22k.dataset ADDED
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1
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8
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model/cfg/imagenet9k.hierarchy.dataset ADDED
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1
+ classes=9418
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model/cfg/jnet-conv.cfg ADDED
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model/cfg/openimages.data ADDED
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1
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+
model/cfg/resnet101.cfg ADDED
@@ -0,0 +1,990 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [net]
2
+ # Training
3
+ # batch=128
4
+ # subdivisions=2
5
+
6
+ # Testing
7
+ batch=1
8
+ subdivisions=1
9
+
10
+ height=256
11
+ width=256
12
+ channels=3
13
+ min_crop=128
14
+ max_crop=448
15
+
16
+ burn_in=1000
17
+ learning_rate=0.1
18
+ policy=poly
19
+ power=4
20
+ max_batches=800000
21
+ momentum=0.9
22
+ decay=0.0005
23
+
24
+ angle=7
25
+ hue=.1
26
+ saturation=.75
27
+ exposure=.75
28
+ aspect=.75
29
+
30
+
31
+
32
+ [convolutional]
33
+ batch_normalize=1
34
+ filters=64
35
+ size=7
36
+ stride=2
37
+ pad=1
38
+ activation=leaky
39
+
40
+ [maxpool]
41
+ size=2
42
+ stride=2
43
+
44
+ [convolutional]
45
+ batch_normalize=1
46
+ filters=64
47
+ size=1
48
+ stride=1
49
+ pad=1
50
+ activation=leaky
51
+
52
+ [convolutional]
53
+ batch_normalize=1
54
+ filters=64
55
+ size=3
56
+ stride=1
57
+ pad=1
58
+ activation=leaky
59
+
60
+ [convolutional]
61
+ batch_normalize=1
62
+ filters=256
63
+ size=1
64
+ stride=1
65
+ pad=1
66
+ activation=linear
67
+
68
+ [shortcut]
69
+ from=-4
70
+ activation=leaky
71
+
72
+ [convolutional]
73
+ batch_normalize=1
74
+ filters=64
75
+ size=1
76
+ stride=1
77
+ pad=1
78
+ activation=leaky
79
+
80
+ [convolutional]
81
+ batch_normalize=1
82
+ filters=64
83
+ size=3
84
+ stride=1
85
+ pad=1
86
+ activation=leaky
87
+
88
+ [convolutional]
89
+ batch_normalize=1
90
+ filters=256
91
+ size=1
92
+ stride=1
93
+ pad=1
94
+ activation=linear
95
+
96
+ [shortcut]
97
+ from=-4
98
+ activation=leaky
99
+
100
+ [convolutional]
101
+ batch_normalize=1
102
+ filters=64
103
+ size=1
104
+ stride=1
105
+ pad=1
106
+ activation=leaky
107
+
108
+ [convolutional]
109
+ batch_normalize=1
110
+ filters=64
111
+ size=3
112
+ stride=1
113
+ pad=1
114
+ activation=leaky
115
+
116
+ [convolutional]
117
+ batch_normalize=1
118
+ filters=256
119
+ size=1
120
+ stride=1
121
+ pad=1
122
+ activation=linear
123
+
124
+ [shortcut]
125
+ from=-4
126
+ activation=leaky
127
+
128
+ [convolutional]
129
+ batch_normalize=1
130
+ filters=128
131
+ size=1
132
+ stride=1
133
+ pad=1
134
+ activation=leaky
135
+
136
+ [convolutional]
137
+ batch_normalize=1
138
+ filters=128
139
+ size=3
140
+ stride=2
141
+ pad=1
142
+ activation=leaky
143
+
144
+ [convolutional]
145
+ batch_normalize=1
146
+ filters=512
147
+ size=1
148
+ stride=1
149
+ pad=1
150
+ activation=linear
151
+
152
+ [shortcut]
153
+ from=-4
154
+ activation=leaky
155
+
156
+ [convolutional]
157
+ batch_normalize=1
158
+ filters=128
159
+ size=1
160
+ stride=1
161
+ pad=1
162
+ activation=leaky
163
+
164
+ [convolutional]
165
+ batch_normalize=1
166
+ filters=128
167
+ size=3
168
+ stride=1
169
+ pad=1
170
+ activation=leaky
171
+
172
+ [convolutional]
173
+ batch_normalize=1
174
+ filters=512
175
+ size=1
176
+ stride=1
177
+ pad=1
178
+ activation=linear
179
+
180
+ [shortcut]
181
+ from=-4
182
+ activation=leaky
183
+
184
+ [convolutional]
185
+ batch_normalize=1
186
+ filters=128
187
+ size=1
188
+ stride=1
189
+ pad=1
190
+ activation=leaky
191
+
192
+ [convolutional]
193
+ batch_normalize=1
194
+ filters=128
195
+ size=3
196
+ stride=1
197
+ pad=1
198
+ activation=leaky
199
+
200
+ [convolutional]
201
+ batch_normalize=1
202
+ filters=512
203
+ size=1
204
+ stride=1
205
+ pad=1
206
+ activation=linear
207
+
208
+ [shortcut]
209
+ from=-4
210
+ activation=leaky
211
+
212
+ [convolutional]
213
+ batch_normalize=1
214
+ filters=128
215
+ size=1
216
+ stride=1
217
+ pad=1
218
+ activation=leaky
219
+
220
+ [convolutional]
221
+ batch_normalize=1
222
+ filters=128
223
+ size=3
224
+ stride=1
225
+ pad=1
226
+ activation=leaky
227
+
228
+ [convolutional]
229
+ batch_normalize=1
230
+ filters=512
231
+ size=1
232
+ stride=1
233
+ pad=1
234
+ activation=linear
235
+
236
+ [shortcut]
237
+ from=-4
238
+ activation=leaky
239
+
240
+
241
+ # Conv 4
242
+ [convolutional]
243
+ batch_normalize=1
244
+ filters=256
245
+ size=1
246
+ stride=1
247
+ pad=1
248
+ activation=leaky
249
+
250
+ [convolutional]
251
+ batch_normalize=1
252
+ filters=256
253
+ size=3
254
+ stride=2
255
+ pad=1
256
+ activation=leaky
257
+
258
+ [convolutional]
259
+ batch_normalize=1
260
+ filters=1024
261
+ size=1
262
+ stride=1
263
+ pad=1
264
+ activation=linear
265
+
266
+ [shortcut]
267
+ from=-4
268
+ activation=leaky
269
+
270
+ [convolutional]
271
+ batch_normalize=1
272
+ filters=256
273
+ size=1
274
+ stride=1
275
+ pad=1
276
+ activation=leaky
277
+
278
+ [convolutional]
279
+ batch_normalize=1
280
+ filters=256
281
+ size=3
282
+ stride=1
283
+ pad=1
284
+ activation=leaky
285
+
286
+ [convolutional]
287
+ batch_normalize=1
288
+ filters=1024
289
+ size=1
290
+ stride=1
291
+ pad=1
292
+ activation=linear
293
+
294
+ [shortcut]
295
+ from=-4
296
+ activation=leaky
297
+
298
+ [convolutional]
299
+ batch_normalize=1
300
+ filters=256
301
+ size=1
302
+ stride=1
303
+ pad=1
304
+ activation=leaky
305
+
306
+ [convolutional]
307
+ batch_normalize=1
308
+ filters=256
309
+ size=3
310
+ stride=1
311
+ pad=1
312
+ activation=leaky
313
+
314
+ [convolutional]
315
+ batch_normalize=1
316
+ filters=1024
317
+ size=1
318
+ stride=1
319
+ pad=1
320
+ activation=linear
321
+
322
+ [shortcut]
323
+ from=-4
324
+ activation=leaky
325
+
326
+ [convolutional]
327
+ batch_normalize=1
328
+ filters=256
329
+ size=1
330
+ stride=1
331
+ pad=1
332
+ activation=leaky
333
+
334
+ [convolutional]
335
+ batch_normalize=1
336
+ filters=256
337
+ size=3
338
+ stride=1
339
+ pad=1
340
+ activation=leaky
341
+
342
+ [convolutional]
343
+ batch_normalize=1
344
+ filters=1024
345
+ size=1
346
+ stride=1
347
+ pad=1
348
+ activation=linear
349
+
350
+ [shortcut]
351
+ from=-4
352
+ activation=leaky
353
+
354
+ [convolutional]
355
+ batch_normalize=1
356
+ filters=256
357
+ size=1
358
+ stride=1
359
+ pad=1
360
+ activation=leaky
361
+
362
+ [convolutional]
363
+ batch_normalize=1
364
+ filters=256
365
+ size=3
366
+ stride=1
367
+ pad=1
368
+ activation=leaky
369
+
370
+ [convolutional]
371
+ batch_normalize=1
372
+ filters=1024
373
+ size=1
374
+ stride=1
375
+ pad=1
376
+ activation=linear
377
+
378
+ [shortcut]
379
+ from=-4
380
+ activation=leaky
381
+
382
+ [convolutional]
383
+ batch_normalize=1
384
+ filters=256
385
+ size=1
386
+ stride=1
387
+ pad=1
388
+ activation=leaky
389
+
390
+ [convolutional]
391
+ batch_normalize=1
392
+ filters=256
393
+ size=3
394
+ stride=1
395
+ pad=1
396
+ activation=leaky
397
+
398
+ [convolutional]
399
+ batch_normalize=1
400
+ filters=1024
401
+ size=1
402
+ stride=1
403
+ pad=1
404
+ activation=linear
405
+
406
+ [shortcut]
407
+ from=-4
408
+ activation=leaky
409
+
410
+ [convolutional]
411
+ batch_normalize=1
412
+ filters=256
413
+ size=1
414
+ stride=1
415
+ pad=1
416
+ activation=leaky
417
+
418
+ [convolutional]
419
+ batch_normalize=1
420
+ filters=256
421
+ size=3
422
+ stride=1
423
+ pad=1
424
+ activation=leaky
425
+
426
+ [convolutional]
427
+ batch_normalize=1
428
+ filters=1024
429
+ size=1
430
+ stride=1
431
+ pad=1
432
+ activation=linear
433
+
434
+ [shortcut]
435
+ from=-4
436
+ activation=leaky
437
+
438
+ [convolutional]
439
+ batch_normalize=1
440
+ filters=256
441
+ size=1
442
+ stride=1
443
+ pad=1
444
+ activation=leaky
445
+
446
+ [convolutional]
447
+ batch_normalize=1
448
+ filters=256
449
+ size=3
450
+ stride=1
451
+ pad=1
452
+ activation=leaky
453
+
454
+ [convolutional]
455
+ batch_normalize=1
456
+ filters=1024
457
+ size=1
458
+ stride=1
459
+ pad=1
460
+ activation=linear
461
+
462
+ [shortcut]
463
+ from=-4
464
+ activation=leaky
465
+
466
+ [convolutional]
467
+ batch_normalize=1
468
+ filters=256
469
+ size=1
470
+ stride=1
471
+ pad=1
472
+ activation=leaky
473
+
474
+ [convolutional]
475
+ batch_normalize=1
476
+ filters=256
477
+ size=3
478
+ stride=1
479
+ pad=1
480
+ activation=leaky
481
+
482
+ [convolutional]
483
+ batch_normalize=1
484
+ filters=1024
485
+ size=1
486
+ stride=1
487
+ pad=1
488
+ activation=linear
489
+
490
+ [shortcut]
491
+ from=-4
492
+ activation=leaky
493
+
494
+ [convolutional]
495
+ batch_normalize=1
496
+ filters=256
497
+ size=1
498
+ stride=1
499
+ pad=1
500
+ activation=leaky
501
+
502
+ [convolutional]
503
+ batch_normalize=1
504
+ filters=256
505
+ size=3
506
+ stride=1
507
+ pad=1
508
+ activation=leaky
509
+
510
+ [convolutional]
511
+ batch_normalize=1
512
+ filters=1024
513
+ size=1
514
+ stride=1
515
+ pad=1
516
+ activation=linear
517
+
518
+ [shortcut]
519
+ from=-4
520
+ activation=leaky
521
+
522
+ [convolutional]
523
+ batch_normalize=1
524
+ filters=256
525
+ size=1
526
+ stride=1
527
+ pad=1
528
+ activation=leaky
529
+
530
+ [convolutional]
531
+ batch_normalize=1
532
+ filters=256
533
+ size=3
534
+ stride=1
535
+ pad=1
536
+ activation=leaky
537
+
538
+ [convolutional]
539
+ batch_normalize=1
540
+ filters=1024
541
+ size=1
542
+ stride=1
543
+ pad=1
544
+ activation=linear
545
+
546
+ [shortcut]
547
+ from=-4
548
+ activation=leaky
549
+
550
+ [convolutional]
551
+ batch_normalize=1
552
+ filters=256
553
+ size=1
554
+ stride=1
555
+ pad=1
556
+ activation=leaky
557
+
558
+ [convolutional]
559
+ batch_normalize=1
560
+ filters=256
561
+ size=3
562
+ stride=1
563
+ pad=1
564
+ activation=leaky
565
+
566
+ [convolutional]
567
+ batch_normalize=1
568
+ filters=1024
569
+ size=1
570
+ stride=1
571
+ pad=1
572
+ activation=linear
573
+
574
+ [shortcut]
575
+ from=-4
576
+ activation=leaky
577
+
578
+ [convolutional]
579
+ batch_normalize=1
580
+ filters=256
581
+ size=1
582
+ stride=1
583
+ pad=1
584
+ activation=leaky
585
+
586
+ [convolutional]
587
+ batch_normalize=1
588
+ filters=256
589
+ size=3
590
+ stride=1
591
+ pad=1
592
+ activation=leaky
593
+
594
+ [convolutional]
595
+ batch_normalize=1
596
+ filters=1024
597
+ size=1
598
+ stride=1
599
+ pad=1
600
+ activation=linear
601
+
602
+ [shortcut]
603
+ from=-4
604
+ activation=leaky
605
+
606
+ [convolutional]
607
+ batch_normalize=1
608
+ filters=256
609
+ size=1
610
+ stride=1
611
+ pad=1
612
+ activation=leaky
613
+
614
+ [convolutional]
615
+ batch_normalize=1
616
+ filters=256
617
+ size=3
618
+ stride=1
619
+ pad=1
620
+ activation=leaky
621
+
622
+ [convolutional]
623
+ batch_normalize=1
624
+ filters=1024
625
+ size=1
626
+ stride=1
627
+ pad=1
628
+ activation=linear
629
+
630
+ [shortcut]
631
+ from=-4
632
+ activation=leaky
633
+
634
+ [convolutional]
635
+ batch_normalize=1
636
+ filters=256
637
+ size=1
638
+ stride=1
639
+ pad=1
640
+ activation=leaky
641
+
642
+ [convolutional]
643
+ batch_normalize=1
644
+ filters=256
645
+ size=3
646
+ stride=1
647
+ pad=1
648
+ activation=leaky
649
+
650
+ [convolutional]
651
+ batch_normalize=1
652
+ filters=1024
653
+ size=1
654
+ stride=1
655
+ pad=1
656
+ activation=linear
657
+
658
+ [shortcut]
659
+ from=-4
660
+ activation=leaky
661
+
662
+ [convolutional]
663
+ batch_normalize=1
664
+ filters=256
665
+ size=1
666
+ stride=1
667
+ pad=1
668
+ activation=leaky
669
+
670
+ [convolutional]
671
+ batch_normalize=1
672
+ filters=256
673
+ size=3
674
+ stride=1
675
+ pad=1
676
+ activation=leaky
677
+
678
+ [convolutional]
679
+ batch_normalize=1
680
+ filters=1024
681
+ size=1
682
+ stride=1
683
+ pad=1
684
+ activation=linear
685
+
686
+ [shortcut]
687
+ from=-4
688
+ activation=leaky
689
+
690
+ [convolutional]
691
+ batch_normalize=1
692
+ filters=256
693
+ size=1
694
+ stride=1
695
+ pad=1
696
+ activation=leaky
697
+
698
+ [convolutional]
699
+ batch_normalize=1
700
+ filters=256
701
+ size=3
702
+ stride=1
703
+ pad=1
704
+ activation=leaky
705
+
706
+ [convolutional]
707
+ batch_normalize=1
708
+ filters=1024
709
+ size=1
710
+ stride=1
711
+ pad=1
712
+ activation=linear
713
+
714
+ [shortcut]
715
+ from=-4
716
+ activation=leaky
717
+
718
+ [convolutional]
719
+ batch_normalize=1
720
+ filters=256
721
+ size=1
722
+ stride=1
723
+ pad=1
724
+ activation=leaky
725
+
726
+ [convolutional]
727
+ batch_normalize=1
728
+ filters=256
729
+ size=3
730
+ stride=1
731
+ pad=1
732
+ activation=leaky
733
+
734
+ [convolutional]
735
+ batch_normalize=1
736
+ filters=1024
737
+ size=1
738
+ stride=1
739
+ pad=1
740
+ activation=linear
741
+
742
+ [shortcut]
743
+ from=-4
744
+ activation=leaky
745
+
746
+ [convolutional]
747
+ batch_normalize=1
748
+ filters=256
749
+ size=1
750
+ stride=1
751
+ pad=1
752
+ activation=leaky
753
+
754
+ [convolutional]
755
+ batch_normalize=1
756
+ filters=256
757
+ size=3
758
+ stride=1
759
+ pad=1
760
+ activation=leaky
761
+
762
+ [convolutional]
763
+ batch_normalize=1
764
+ filters=1024
765
+ size=1
766
+ stride=1
767
+ pad=1
768
+ activation=linear
769
+
770
+ [shortcut]
771
+ from=-4
772
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773
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798
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802
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826
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830
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838
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854
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858
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866
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882
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886
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887
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890
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903
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911
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915
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923
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931
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939
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943
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951
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952
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959
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967
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971
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972
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973
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974
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975
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976
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977
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978
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979
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980
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981
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982
+
983
+ [avgpool]
984
+
985
+ [softmax]
986
+ groups=1
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+
988
+ [cost]
989
+ type=sse
990
+
model/cfg/resnet152.cfg ADDED
@@ -0,0 +1,1460 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [net]
2
+ # Training
3
+ # batch=128
4
+ # subdivisions=8
5
+
6
+ # Testing
7
+ batch=1
8
+ subdivisions=1
9
+
10
+ height=256
11
+ width=256
12
+ max_crop=448
13
+ channels=3
14
+ momentum=0.9
15
+ decay=0.0005
16
+
17
+ burn_in=1000
18
+ learning_rate=0.1
19
+ policy=poly
20
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21
+ max_batches=1600000
22
+
23
+ angle=7
24
+ hue=.1
25
+ saturation=.75
26
+ exposure=.75
27
+ aspect=.75
28
+
29
+ [convolutional]
30
+ batch_normalize=1
31
+ filters=64
32
+ size=7
33
+ stride=2
34
+ pad=1
35
+ activation=leaky
36
+
37
+ [maxpool]
38
+ size=2
39
+ stride=2
40
+
41
+ [convolutional]
42
+ batch_normalize=1
43
+ filters=64
44
+ size=1
45
+ stride=1
46
+ pad=1
47
+ activation=leaky
48
+
49
+ [convolutional]
50
+ batch_normalize=1
51
+ filters=64
52
+ size=3
53
+ stride=1
54
+ pad=1
55
+ activation=leaky
56
+
57
+ [convolutional]
58
+ batch_normalize=1
59
+ filters=256
60
+ size=1
61
+ stride=1
62
+ pad=1
63
+ activation=linear
64
+
65
+ [shortcut]
66
+ from=-4
67
+ activation=leaky
68
+
69
+ [convolutional]
70
+ batch_normalize=1
71
+ filters=64
72
+ size=1
73
+ stride=1
74
+ pad=1
75
+ activation=leaky
76
+
77
+ [convolutional]
78
+ batch_normalize=1
79
+ filters=64
80
+ size=3
81
+ stride=1
82
+ pad=1
83
+ activation=leaky
84
+
85
+ [convolutional]
86
+ batch_normalize=1
87
+ filters=256
88
+ size=1
89
+ stride=1
90
+ pad=1
91
+ activation=linear
92
+
93
+ [shortcut]
94
+ from=-4
95
+ activation=leaky
96
+
97
+ [convolutional]
98
+ batch_normalize=1
99
+ filters=64
100
+ size=1
101
+ stride=1
102
+ pad=1
103
+ activation=leaky
104
+
105
+ [convolutional]
106
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107
+ filters=64
108
+ size=3
109
+ stride=1
110
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111
+ activation=leaky
112
+
113
+ [convolutional]
114
+ batch_normalize=1
115
+ filters=256
116
+ size=1
117
+ stride=1
118
+ pad=1
119
+ activation=linear
120
+
121
+ [shortcut]
122
+ from=-4
123
+ activation=leaky
124
+
125
+ [convolutional]
126
+ batch_normalize=1
127
+ filters=128
128
+ size=1
129
+ stride=1
130
+ pad=1
131
+ activation=leaky
132
+
133
+ [convolutional]
134
+ batch_normalize=1
135
+ filters=128
136
+ size=3
137
+ stride=2
138
+ pad=1
139
+ activation=leaky
140
+
141
+ [convolutional]
142
+ batch_normalize=1
143
+ filters=512
144
+ size=1
145
+ stride=1
146
+ pad=1
147
+ activation=linear
148
+
149
+ [shortcut]
150
+ from=-4
151
+ activation=leaky
152
+
153
+ [convolutional]
154
+ batch_normalize=1
155
+ filters=128
156
+ size=1
157
+ stride=1
158
+ pad=1
159
+ activation=leaky
160
+
161
+ [convolutional]
162
+ batch_normalize=1
163
+ filters=128
164
+ size=3
165
+ stride=1
166
+ pad=1
167
+ activation=leaky
168
+
169
+ [convolutional]
170
+ batch_normalize=1
171
+ filters=512
172
+ size=1
173
+ stride=1
174
+ pad=1
175
+ activation=linear
176
+
177
+ [shortcut]
178
+ from=-4
179
+ activation=leaky
180
+
181
+ [convolutional]
182
+ batch_normalize=1
183
+ filters=128
184
+ size=1
185
+ stride=1
186
+ pad=1
187
+ activation=leaky
188
+
189
+ [convolutional]
190
+ batch_normalize=1
191
+ filters=128
192
+ size=3
193
+ stride=1
194
+ pad=1
195
+ activation=leaky
196
+
197
+ [convolutional]
198
+ batch_normalize=1
199
+ filters=512
200
+ size=1
201
+ stride=1
202
+ pad=1
203
+ activation=linear
204
+
205
+ [shortcut]
206
+ from=-4
207
+ activation=leaky
208
+
209
+ [convolutional]
210
+ batch_normalize=1
211
+ filters=128
212
+ size=1
213
+ stride=1
214
+ pad=1
215
+ activation=leaky
216
+
217
+ [convolutional]
218
+ batch_normalize=1
219
+ filters=128
220
+ size=3
221
+ stride=1
222
+ pad=1
223
+ activation=leaky
224
+
225
+ [convolutional]
226
+ batch_normalize=1
227
+ filters=512
228
+ size=1
229
+ stride=1
230
+ pad=1
231
+ activation=linear
232
+
233
+ [shortcut]
234
+ from=-4
235
+ activation=leaky
236
+
237
+ [convolutional]
238
+ batch_normalize=1
239
+ filters=128
240
+ size=1
241
+ stride=1
242
+ pad=1
243
+ activation=leaky
244
+
245
+ [convolutional]
246
+ batch_normalize=1
247
+ filters=128
248
+ size=3
249
+ stride=1
250
+ pad=1
251
+ activation=leaky
252
+
253
+ [convolutional]
254
+ batch_normalize=1
255
+ filters=512
256
+ size=1
257
+ stride=1
258
+ pad=1
259
+ activation=linear
260
+
261
+ [shortcut]
262
+ from=-4
263
+ activation=leaky
264
+
265
+ [convolutional]
266
+ batch_normalize=1
267
+ filters=128
268
+ size=1
269
+ stride=1
270
+ pad=1
271
+ activation=leaky
272
+
273
+ [convolutional]
274
+ batch_normalize=1
275
+ filters=128
276
+ size=3
277
+ stride=1
278
+ pad=1
279
+ activation=leaky
280
+
281
+ [convolutional]
282
+ batch_normalize=1
283
+ filters=512
284
+ size=1
285
+ stride=1
286
+ pad=1
287
+ activation=linear
288
+
289
+ [shortcut]
290
+ from=-4
291
+ activation=leaky
292
+
293
+ [convolutional]
294
+ batch_normalize=1
295
+ filters=128
296
+ size=1
297
+ stride=1
298
+ pad=1
299
+ activation=leaky
300
+
301
+ [convolutional]
302
+ batch_normalize=1
303
+ filters=128
304
+ size=3
305
+ stride=1
306
+ pad=1
307
+ activation=leaky
308
+
309
+ [convolutional]
310
+ batch_normalize=1
311
+ filters=512
312
+ size=1
313
+ stride=1
314
+ pad=1
315
+ activation=linear
316
+
317
+ [shortcut]
318
+ from=-4
319
+ activation=leaky
320
+
321
+ [convolutional]
322
+ batch_normalize=1
323
+ filters=128
324
+ size=1
325
+ stride=1
326
+ pad=1
327
+ activation=leaky
328
+
329
+ [convolutional]
330
+ batch_normalize=1
331
+ filters=128
332
+ size=3
333
+ stride=1
334
+ pad=1
335
+ activation=leaky
336
+
337
+ [convolutional]
338
+ batch_normalize=1
339
+ filters=512
340
+ size=1
341
+ stride=1
342
+ pad=1
343
+ activation=linear
344
+
345
+ [shortcut]
346
+ from=-4
347
+ activation=leaky
348
+
349
+
350
+ # Conv 4
351
+ [convolutional]
352
+ batch_normalize=1
353
+ filters=256
354
+ size=1
355
+ stride=1
356
+ pad=1
357
+ activation=leaky
358
+
359
+ [convolutional]
360
+ batch_normalize=1
361
+ filters=256
362
+ size=3
363
+ stride=2
364
+ pad=1
365
+ activation=leaky
366
+
367
+ [convolutional]
368
+ batch_normalize=1
369
+ filters=1024
370
+ size=1
371
+ stride=1
372
+ pad=1
373
+ activation=linear
374
+
375
+ [shortcut]
376
+ from=-4
377
+ activation=leaky
378
+
379
+ [convolutional]
380
+ batch_normalize=1
381
+ filters=256
382
+ size=1
383
+ stride=1
384
+ pad=1
385
+ activation=leaky
386
+
387
+ [convolutional]
388
+ batch_normalize=1
389
+ filters=256
390
+ size=3
391
+ stride=1
392
+ pad=1
393
+ activation=leaky
394
+
395
+ [convolutional]
396
+ batch_normalize=1
397
+ filters=1024
398
+ size=1
399
+ stride=1
400
+ pad=1
401
+ activation=linear
402
+
403
+ [shortcut]
404
+ from=-4
405
+ activation=leaky
406
+
407
+ [convolutional]
408
+ batch_normalize=1
409
+ filters=256
410
+ size=1
411
+ stride=1
412
+ pad=1
413
+ activation=leaky
414
+
415
+ [convolutional]
416
+ batch_normalize=1
417
+ filters=256
418
+ size=3
419
+ stride=1
420
+ pad=1
421
+ activation=leaky
422
+
423
+ [convolutional]
424
+ batch_normalize=1
425
+ filters=1024
426
+ size=1
427
+ stride=1
428
+ pad=1
429
+ activation=linear
430
+
431
+ [shortcut]
432
+ from=-4
433
+ activation=leaky
434
+
435
+ [convolutional]
436
+ batch_normalize=1
437
+ filters=256
438
+ size=1
439
+ stride=1
440
+ pad=1
441
+ activation=leaky
442
+
443
+ [convolutional]
444
+ batch_normalize=1
445
+ filters=256
446
+ size=3
447
+ stride=1
448
+ pad=1
449
+ activation=leaky
450
+
451
+ [convolutional]
452
+ batch_normalize=1
453
+ filters=1024
454
+ size=1
455
+ stride=1
456
+ pad=1
457
+ activation=linear
458
+
459
+ [shortcut]
460
+ from=-4
461
+ activation=leaky
462
+
463
+ [convolutional]
464
+ batch_normalize=1
465
+ filters=256
466
+ size=1
467
+ stride=1
468
+ pad=1
469
+ activation=leaky
470
+
471
+ [convolutional]
472
+ batch_normalize=1
473
+ filters=256
474
+ size=3
475
+ stride=1
476
+ pad=1
477
+ activation=leaky
478
+
479
+ [convolutional]
480
+ batch_normalize=1
481
+ filters=1024
482
+ size=1
483
+ stride=1
484
+ pad=1
485
+ activation=linear
486
+
487
+ [shortcut]
488
+ from=-4
489
+ activation=leaky
490
+
491
+ [convolutional]
492
+ batch_normalize=1
493
+ filters=256
494
+ size=1
495
+ stride=1
496
+ pad=1
497
+ activation=leaky
498
+
499
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1337
+ activation=leaky
1338
+
1339
+ [convolutional]
1340
+ batch_normalize=1
1341
+ filters=256
1342
+ size=3
1343
+ stride=1
1344
+ pad=1
1345
+ activation=leaky
1346
+
1347
+ [convolutional]
1348
+ batch_normalize=1
1349
+ filters=1024
1350
+ size=1
1351
+ stride=1
1352
+ pad=1
1353
+ activation=linear
1354
+
1355
+ [shortcut]
1356
+ from=-4
1357
+ activation=leaky
1358
+
1359
+ #Conv 5
1360
+ [convolutional]
1361
+ batch_normalize=1
1362
+ filters=512
1363
+ size=1
1364
+ stride=1
1365
+ pad=1
1366
+ activation=leaky
1367
+
1368
+ [convolutional]
1369
+ batch_normalize=1
1370
+ filters=512
1371
+ size=3
1372
+ stride=2
1373
+ pad=1
1374
+ activation=leaky
1375
+
1376
+ [convolutional]
1377
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1378
+ filters=2048
1379
+ size=1
1380
+ stride=1
1381
+ pad=1
1382
+ activation=linear
1383
+
1384
+ [shortcut]
1385
+ from=-4
1386
+ activation=leaky
1387
+
1388
+ [convolutional]
1389
+ batch_normalize=1
1390
+ filters=512
1391
+ size=1
1392
+ stride=1
1393
+ pad=1
1394
+ activation=leaky
1395
+
1396
+ [convolutional]
1397
+ batch_normalize=1
1398
+ filters=512
1399
+ size=3
1400
+ stride=1
1401
+ pad=1
1402
+ activation=leaky
1403
+
1404
+ [convolutional]
1405
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1406
+ filters=2048
1407
+ size=1
1408
+ stride=1
1409
+ pad=1
1410
+ activation=linear
1411
+
1412
+ [shortcut]
1413
+ from=-4
1414
+ activation=leaky
1415
+
1416
+ [convolutional]
1417
+ batch_normalize=1
1418
+ filters=512
1419
+ size=1
1420
+ stride=1
1421
+ pad=1
1422
+ activation=leaky
1423
+
1424
+ [convolutional]
1425
+ batch_normalize=1
1426
+ filters=512
1427
+ size=3
1428
+ stride=1
1429
+ pad=1
1430
+ activation=leaky
1431
+
1432
+ [convolutional]
1433
+ batch_normalize=1
1434
+ filters=2048
1435
+ size=1
1436
+ stride=1
1437
+ pad=1
1438
+ activation=linear
1439
+
1440
+ [shortcut]
1441
+ from=-4
1442
+ activation=leaky
1443
+
1444
+
1445
+
1446
+
1447
+
1448
+
1449
+ [convolutional]
1450
+ filters=1000
1451
+ size=1
1452
+ stride=1
1453
+ pad=1
1454
+ activation=linear
1455
+
1456
+ [avgpool]
1457
+
1458
+ [softmax]
1459
+ groups=1
1460
+
model/cfg/resnet18.cfg ADDED
@@ -0,0 +1,228 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [net]
2
+ # Training
3
+ # batch=128
4
+ # subdivisions=1
5
+
6
+ # Testing
7
+ batch=1
8
+ subdivisions=1
9
+
10
+ height=256
11
+ width=256
12
+ channels=3
13
+ min_crop=128
14
+ max_crop=448
15
+
16
+ burn_in=1000
17
+ learning_rate=0.1
18
+ policy=poly
19
+ power=4
20
+ max_batches=800000
21
+ momentum=0.9
22
+ decay=0.0005
23
+
24
+ angle=7
25
+ hue=.1
26
+ saturation=.75
27
+ exposure=.75
28
+ aspect=.75
29
+
30
+
31
+ [convolutional]
32
+ batch_normalize=1
33
+ filters=64
34
+ size=7
35
+ stride=2
36
+ pad=1
37
+ activation=leaky
38
+
39
+ [maxpool]
40
+ size=2
41
+ stride=2
42
+
43
+
44
+ # Residual Block
45
+ [convolutional]
46
+ batch_normalize=1
47
+ filters=64
48
+ size=3
49
+ stride=1
50
+ pad=1
51
+ activation=leaky
52
+
53
+ [convolutional]
54
+ batch_normalize=1
55
+ filters=64
56
+ size=3
57
+ stride=1
58
+ pad=1
59
+ activation=linear
60
+
61
+ [shortcut]
62
+ activation=leaky
63
+ from=-3
64
+
65
+ # Residual Block
66
+ [convolutional]
67
+ batch_normalize=1
68
+ filters=64
69
+ size=3
70
+ stride=1
71
+ pad=1
72
+ activation=leaky
73
+
74
+ [convolutional]
75
+ batch_normalize=1
76
+ filters=64
77
+ size=3
78
+ stride=1
79
+ pad=1
80
+ activation=linear
81
+
82
+ [shortcut]
83
+ activation=leaky
84
+ from=-3
85
+
86
+ # Strided Residual Block
87
+ [convolutional]
88
+ batch_normalize=1
89
+ filters=128
90
+ size=3
91
+ stride=2
92
+ pad=1
93
+ activation=leaky
94
+
95
+ [convolutional]
96
+ batch_normalize=1
97
+ filters=128
98
+ size=3
99
+ stride=1
100
+ pad=1
101
+ activation=linear
102
+
103
+ [shortcut]
104
+ activation=leaky
105
+ from=-3
106
+
107
+ # Residual Block
108
+ [convolutional]
109
+ batch_normalize=1
110
+ filters=128
111
+ size=3
112
+ stride=1
113
+ pad=1
114
+ activation=leaky
115
+
116
+ [convolutional]
117
+ batch_normalize=1
118
+ filters=128
119
+ size=3
120
+ stride=1
121
+ pad=1
122
+ activation=linear
123
+
124
+ [shortcut]
125
+ activation=leaky
126
+ from=-3
127
+
128
+
129
+ # Strided Residual Block
130
+ [convolutional]
131
+ batch_normalize=1
132
+ filters=256
133
+ size=3
134
+ stride=2
135
+ pad=1
136
+ activation=leaky
137
+
138
+ [convolutional]
139
+ batch_normalize=1
140
+ filters=256
141
+ size=3
142
+ stride=1
143
+ pad=1
144
+ activation=linear
145
+
146
+ [shortcut]
147
+ activation=leaky
148
+ from=-3
149
+
150
+ # Residual Block
151
+ [convolutional]
152
+ batch_normalize=1
153
+ filters=256
154
+ size=3
155
+ stride=1
156
+ pad=1
157
+ activation=leaky
158
+
159
+ [convolutional]
160
+ batch_normalize=1
161
+ filters=256
162
+ size=3
163
+ stride=1
164
+ pad=1
165
+ activation=linear
166
+
167
+ [shortcut]
168
+ activation=leaky
169
+ from=-3
170
+
171
+
172
+ # Strided Residual Block
173
+ [convolutional]
174
+ batch_normalize=1
175
+ filters=512
176
+ size=3
177
+ stride=2
178
+ pad=1
179
+ activation=leaky
180
+
181
+ [convolutional]
182
+ batch_normalize=1
183
+ filters=512
184
+ size=3
185
+ stride=1
186
+ pad=1
187
+ activation=linear
188
+
189
+ [shortcut]
190
+ activation=leaky
191
+ from=-3
192
+
193
+ # Residual Block
194
+ [convolutional]
195
+ batch_normalize=1
196
+ filters=512
197
+ size=3
198
+ stride=1
199
+ pad=1
200
+ activation=leaky
201
+
202
+ [convolutional]
203
+ batch_normalize=1
204
+ filters=512
205
+ size=3
206
+ stride=1
207
+ pad=1
208
+ activation=linear
209
+
210
+ [shortcut]
211
+ activation=leaky
212
+ from=-3
213
+
214
+
215
+
216
+
217
+ [avgpool]
218
+
219
+ [convolutional]
220
+ filters=1000
221
+ size=1
222
+ stride=1
223
+ pad=1
224
+ activation=linear
225
+
226
+ [softmax]
227
+ groups=1
228
+
model/cfg/resnet34.cfg ADDED
@@ -0,0 +1,392 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [net]
2
+ # Training
3
+ # batch=128
4
+ # subdivisions=2
5
+
6
+ # Testing
7
+ batch=1
8
+ subdivisions=1
9
+
10
+ height=256
11
+ width=256
12
+ channels=3
13
+ min_crop=128
14
+ max_crop=448
15
+
16
+ burn_in=1000
17
+ learning_rate=0.1
18
+ policy=poly
19
+ power=4
20
+ max_batches=800000
21
+ momentum=0.9
22
+ decay=0.0005
23
+
24
+ angle=7
25
+ hue=.1
26
+ saturation=.75
27
+ exposure=.75
28
+ aspect=.75
29
+
30
+
31
+ [convolutional]
32
+ batch_normalize=1
33
+ filters=64
34
+ size=7
35
+ stride=2
36
+ pad=1
37
+ activation=leaky
38
+
39
+ [maxpool]
40
+ size=2
41
+ stride=2
42
+
43
+ # Residual Block
44
+ [convolutional]
45
+ batch_normalize=1
46
+ filters=64
47
+ size=3
48
+ stride=1
49
+ pad=1
50
+ activation=leaky
51
+
52
+ [convolutional]
53
+ batch_normalize=1
54
+ filters=64
55
+ size=3
56
+ stride=1
57
+ pad=1
58
+ activation=linear
59
+
60
+ [shortcut]
61
+ activation=leaky
62
+ from=-3
63
+
64
+ # Residual Block
65
+ [convolutional]
66
+ batch_normalize=1
67
+ filters=64
68
+ size=3
69
+ stride=1
70
+ pad=1
71
+ activation=leaky
72
+
73
+ [convolutional]
74
+ batch_normalize=1
75
+ filters=64
76
+ size=3
77
+ stride=1
78
+ pad=1
79
+ activation=linear
80
+
81
+ [shortcut]
82
+ activation=leaky
83
+ from=-3
84
+
85
+ # Residual Block
86
+ [convolutional]
87
+ batch_normalize=1
88
+ filters=64
89
+ size=3
90
+ stride=1
91
+ pad=1
92
+ activation=leaky
93
+
94
+ [convolutional]
95
+ batch_normalize=1
96
+ filters=64
97
+ size=3
98
+ stride=1
99
+ pad=1
100
+ activation=linear
101
+
102
+ [shortcut]
103
+ activation=leaky
104
+ from=-3
105
+
106
+ # Strided Residual Block
107
+ [convolutional]
108
+ batch_normalize=1
109
+ filters=128
110
+ size=3
111
+ stride=2
112
+ pad=1
113
+ activation=leaky
114
+
115
+ [convolutional]
116
+ batch_normalize=1
117
+ filters=128
118
+ size=3
119
+ stride=1
120
+ pad=1
121
+ activation=linear
122
+
123
+ [shortcut]
124
+ activation=leaky
125
+ from=-3
126
+
127
+ # Residual Block
128
+ [convolutional]
129
+ batch_normalize=1
130
+ filters=128
131
+ size=3
132
+ stride=1
133
+ pad=1
134
+ activation=leaky
135
+
136
+ [convolutional]
137
+ batch_normalize=1
138
+ filters=128
139
+ size=3
140
+ stride=1
141
+ pad=1
142
+ activation=linear
143
+
144
+ [shortcut]
145
+ activation=leaky
146
+ from=-3
147
+
148
+ # Residual Block
149
+ [convolutional]
150
+ batch_normalize=1
151
+ filters=128
152
+ size=3
153
+ stride=1
154
+ pad=1
155
+ activation=leaky
156
+
157
+ [convolutional]
158
+ batch_normalize=1
159
+ filters=128
160
+ size=3
161
+ stride=1
162
+ pad=1
163
+ activation=linear
164
+
165
+ [shortcut]
166
+ activation=leaky
167
+ from=-3
168
+
169
+ # Residual Block
170
+ [convolutional]
171
+ batch_normalize=1
172
+ filters=128
173
+ size=3
174
+ stride=1
175
+ pad=1
176
+ activation=leaky
177
+
178
+ [convolutional]
179
+ batch_normalize=1
180
+ filters=128
181
+ size=3
182
+ stride=1
183
+ pad=1
184
+ activation=linear
185
+
186
+ [shortcut]
187
+ activation=leaky
188
+ from=-3
189
+
190
+ # Strided Residual Block
191
+ [convolutional]
192
+ batch_normalize=1
193
+ filters=256
194
+ size=3
195
+ stride=2
196
+ pad=1
197
+ activation=leaky
198
+
199
+ [convolutional]
200
+ batch_normalize=1
201
+ filters=256
202
+ size=3
203
+ stride=1
204
+ pad=1
205
+ activation=linear
206
+
207
+ [shortcut]
208
+ activation=leaky
209
+ from=-3
210
+
211
+ # Residual Block
212
+ [convolutional]
213
+ batch_normalize=1
214
+ filters=256
215
+ size=3
216
+ stride=1
217
+ pad=1
218
+ activation=leaky
219
+
220
+ [convolutional]
221
+ batch_normalize=1
222
+ filters=256
223
+ size=3
224
+ stride=1
225
+ pad=1
226
+ activation=linear
227
+
228
+ [shortcut]
229
+ activation=leaky
230
+ from=-3
231
+
232
+ # Residual Block
233
+ [convolutional]
234
+ batch_normalize=1
235
+ filters=256
236
+ size=3
237
+ stride=1
238
+ pad=1
239
+ activation=leaky
240
+
241
+ [convolutional]
242
+ batch_normalize=1
243
+ filters=256
244
+ size=3
245
+ stride=1
246
+ pad=1
247
+ activation=linear
248
+
249
+ [shortcut]
250
+ activation=leaky
251
+ from=-3
252
+
253
+ # Residual Block
254
+ [convolutional]
255
+ batch_normalize=1
256
+ filters=256
257
+ size=3
258
+ stride=1
259
+ pad=1
260
+ activation=leaky
261
+
262
+ [convolutional]
263
+ batch_normalize=1
264
+ filters=256
265
+ size=3
266
+ stride=1
267
+ pad=1
268
+ activation=linear
269
+
270
+ [shortcut]
271
+ activation=leaky
272
+ from=-3
273
+
274
+ # Residual Block
275
+ [convolutional]
276
+ batch_normalize=1
277
+ filters=256
278
+ size=3
279
+ stride=1
280
+ pad=1
281
+ activation=leaky
282
+
283
+ [convolutional]
284
+ batch_normalize=1
285
+ filters=256
286
+ size=3
287
+ stride=1
288
+ pad=1
289
+ activation=linear
290
+
291
+ [shortcut]
292
+ activation=leaky
293
+ from=-3
294
+
295
+ # Residual Block
296
+ [convolutional]
297
+ batch_normalize=1
298
+ filters=256
299
+ size=3
300
+ stride=1
301
+ pad=1
302
+ activation=leaky
303
+
304
+ [convolutional]
305
+ batch_normalize=1
306
+ filters=256
307
+ size=3
308
+ stride=1
309
+ pad=1
310
+ activation=linear
311
+
312
+ [shortcut]
313
+ activation=leaky
314
+ from=-3
315
+
316
+ # Residual Block
317
+ [convolutional]
318
+ batch_normalize=1
319
+ filters=512
320
+ size=3
321
+ stride=2
322
+ pad=1
323
+ activation=leaky
324
+
325
+ [convolutional]
326
+ batch_normalize=1
327
+ filters=512
328
+ size=3
329
+ stride=1
330
+ pad=1
331
+ activation=linear
332
+
333
+ [shortcut]
334
+ activation=leaky
335
+ from=-3
336
+
337
+ # Residual Block
338
+ [convolutional]
339
+ batch_normalize=1
340
+ filters=512
341
+ size=3
342
+ stride=1
343
+ pad=1
344
+ activation=leaky
345
+
346
+ [convolutional]
347
+ batch_normalize=1
348
+ filters=512
349
+ size=3
350
+ stride=1
351
+ pad=1
352
+ activation=linear
353
+
354
+ [shortcut]
355
+ activation=leaky
356
+ from=-3
357
+
358
+ # Residual Block
359
+ [convolutional]
360
+ batch_normalize=1
361
+ filters=512
362
+ size=3
363
+ stride=1
364
+ pad=1
365
+ activation=leaky
366
+
367
+ [convolutional]
368
+ batch_normalize=1
369
+ filters=512
370
+ size=3
371
+ stride=1
372
+ pad=1
373
+ activation=linear
374
+
375
+ [shortcut]
376
+ activation=leaky
377
+ from=-3
378
+
379
+
380
+
381
+ [avgpool]
382
+
383
+ [convolutional]
384
+ filters=1000
385
+ size=1
386
+ stride=1
387
+ pad=1
388
+ activation=linear
389
+
390
+ [softmax]
391
+ groups=1
392
+
model/cfg/resnet50.cfg ADDED
@@ -0,0 +1,510 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [net]
2
+ # Training
3
+ # batch=128
4
+ # subdivisions=4
5
+
6
+ # Testing
7
+ batch=1
8
+ subdivisions=1
9
+
10
+ height=256
11
+ width=256
12
+ channels=3
13
+ min_crop=128
14
+ max_crop=448
15
+
16
+ burn_in=1000
17
+ learning_rate=0.1
18
+ policy=poly
19
+ power=4
20
+ max_batches=800000
21
+ momentum=0.9
22
+ decay=0.0005
23
+
24
+ angle=7
25
+ hue=.1
26
+ saturation=.75
27
+ exposure=.75
28
+ aspect=.75
29
+
30
+
31
+ [convolutional]
32
+ batch_normalize=1
33
+ filters=64
34
+ size=7
35
+ stride=2
36
+ pad=1
37
+ activation=leaky
38
+
39
+ [maxpool]
40
+ size=2
41
+ stride=2
42
+
43
+ [convolutional]
44
+ batch_normalize=1
45
+ filters=64
46
+ size=1
47
+ stride=1
48
+ pad=1
49
+ activation=leaky
50
+
51
+ [convolutional]
52
+ batch_normalize=1
53
+ filters=64
54
+ size=3
55
+ stride=1
56
+ pad=1
57
+ activation=leaky
58
+
59
+ [convolutional]
60
+ batch_normalize=1
61
+ filters=256
62
+ size=1
63
+ stride=1
64
+ pad=1
65
+ activation=linear
66
+
67
+ [shortcut]
68
+ from=-4
69
+ activation=leaky
70
+
71
+ [convolutional]
72
+ batch_normalize=1
73
+ filters=64
74
+ size=1
75
+ stride=1
76
+ pad=1
77
+ activation=leaky
78
+
79
+ [convolutional]
80
+ batch_normalize=1
81
+ filters=64
82
+ size=3
83
+ stride=1
84
+ pad=1
85
+ activation=leaky
86
+
87
+ [convolutional]
88
+ batch_normalize=1
89
+ filters=256
90
+ size=1
91
+ stride=1
92
+ pad=1
93
+ activation=linear
94
+
95
+ [shortcut]
96
+ from=-4
97
+ activation=leaky
98
+
99
+ [convolutional]
100
+ batch_normalize=1
101
+ filters=64
102
+ size=1
103
+ stride=1
104
+ pad=1
105
+ activation=leaky
106
+
107
+ [convolutional]
108
+ batch_normalize=1
109
+ filters=64
110
+ size=3
111
+ stride=1
112
+ pad=1
113
+ activation=leaky
114
+
115
+ [convolutional]
116
+ batch_normalize=1
117
+ filters=256
118
+ size=1
119
+ stride=1
120
+ pad=1
121
+ activation=linear
122
+
123
+ [shortcut]
124
+ from=-4
125
+ activation=leaky
126
+
127
+ [convolutional]
128
+ batch_normalize=1
129
+ filters=128
130
+ size=1
131
+ stride=1
132
+ pad=1
133
+ activation=leaky
134
+
135
+ [convolutional]
136
+ batch_normalize=1
137
+ filters=128
138
+ size=3
139
+ stride=2
140
+ pad=1
141
+ activation=leaky
142
+
143
+ [convolutional]
144
+ batch_normalize=1
145
+ filters=512
146
+ size=1
147
+ stride=1
148
+ pad=1
149
+ activation=linear
150
+
151
+ [shortcut]
152
+ from=-4
153
+ activation=leaky
154
+
155
+ [convolutional]
156
+ batch_normalize=1
157
+ filters=128
158
+ size=1
159
+ stride=1
160
+ pad=1
161
+ activation=leaky
162
+
163
+ [convolutional]
164
+ batch_normalize=1
165
+ filters=128
166
+ size=3
167
+ stride=1
168
+ pad=1
169
+ activation=leaky
170
+
171
+ [convolutional]
172
+ batch_normalize=1
173
+ filters=512
174
+ size=1
175
+ stride=1
176
+ pad=1
177
+ activation=linear
178
+
179
+ [shortcut]
180
+ from=-4
181
+ activation=leaky
182
+
183
+ [convolutional]
184
+ batch_normalize=1
185
+ filters=128
186
+ size=1
187
+ stride=1
188
+ pad=1
189
+ activation=leaky
190
+
191
+ [convolutional]
192
+ batch_normalize=1
193
+ filters=128
194
+ size=3
195
+ stride=1
196
+ pad=1
197
+ activation=leaky
198
+
199
+ [convolutional]
200
+ batch_normalize=1
201
+ filters=512
202
+ size=1
203
+ stride=1
204
+ pad=1
205
+ activation=linear
206
+
207
+ [shortcut]
208
+ from=-4
209
+ activation=leaky
210
+
211
+ [convolutional]
212
+ batch_normalize=1
213
+ filters=128
214
+ size=1
215
+ stride=1
216
+ pad=1
217
+ activation=leaky
218
+
219
+ [convolutional]
220
+ batch_normalize=1
221
+ filters=128
222
+ size=3
223
+ stride=1
224
+ pad=1
225
+ activation=leaky
226
+
227
+ [convolutional]
228
+ batch_normalize=1
229
+ filters=512
230
+ size=1
231
+ stride=1
232
+ pad=1
233
+ activation=linear
234
+
235
+ [shortcut]
236
+ from=-4
237
+ activation=leaky
238
+
239
+
240
+ # Conv 4
241
+ [convolutional]
242
+ batch_normalize=1
243
+ filters=256
244
+ size=1
245
+ stride=1
246
+ pad=1
247
+ activation=leaky
248
+
249
+ [convolutional]
250
+ batch_normalize=1
251
+ filters=256
252
+ size=3
253
+ stride=2
254
+ pad=1
255
+ activation=leaky
256
+
257
+ [convolutional]
258
+ batch_normalize=1
259
+ filters=1024
260
+ size=1
261
+ stride=1
262
+ pad=1
263
+ activation=linear
264
+
265
+ [shortcut]
266
+ from=-4
267
+ activation=leaky
268
+
269
+ [convolutional]
270
+ batch_normalize=1
271
+ filters=256
272
+ size=1
273
+ stride=1
274
+ pad=1
275
+ activation=leaky
276
+
277
+ [convolutional]
278
+ batch_normalize=1
279
+ filters=256
280
+ size=3
281
+ stride=1
282
+ pad=1
283
+ activation=leaky
284
+
285
+ [convolutional]
286
+ batch_normalize=1
287
+ filters=1024
288
+ size=1
289
+ stride=1
290
+ pad=1
291
+ activation=linear
292
+
293
+ [shortcut]
294
+ from=-4
295
+ activation=leaky
296
+
297
+ [convolutional]
298
+ batch_normalize=1
299
+ filters=256
300
+ size=1
301
+ stride=1
302
+ pad=1
303
+ activation=leaky
304
+
305
+ [convolutional]
306
+ batch_normalize=1
307
+ filters=256
308
+ size=3
309
+ stride=1
310
+ pad=1
311
+ activation=leaky
312
+
313
+ [convolutional]
314
+ batch_normalize=1
315
+ filters=1024
316
+ size=1
317
+ stride=1
318
+ pad=1
319
+ activation=linear
320
+
321
+ [shortcut]
322
+ from=-4
323
+ activation=leaky
324
+
325
+ [convolutional]
326
+ batch_normalize=1
327
+ filters=256
328
+ size=1
329
+ stride=1
330
+ pad=1
331
+ activation=leaky
332
+
333
+ [convolutional]
334
+ batch_normalize=1
335
+ filters=256
336
+ size=3
337
+ stride=1
338
+ pad=1
339
+ activation=leaky
340
+
341
+ [convolutional]
342
+ batch_normalize=1
343
+ filters=1024
344
+ size=1
345
+ stride=1
346
+ pad=1
347
+ activation=linear
348
+
349
+ [shortcut]
350
+ from=-4
351
+ activation=leaky
352
+
353
+ [convolutional]
354
+ batch_normalize=1
355
+ filters=256
356
+ size=1
357
+ stride=1
358
+ pad=1
359
+ activation=leaky
360
+
361
+ [convolutional]
362
+ batch_normalize=1
363
+ filters=256
364
+ size=3
365
+ stride=1
366
+ pad=1
367
+ activation=leaky
368
+
369
+ [convolutional]
370
+ batch_normalize=1
371
+ filters=1024
372
+ size=1
373
+ stride=1
374
+ pad=1
375
+ activation=linear
376
+
377
+ [shortcut]
378
+ from=-4
379
+ activation=leaky
380
+
381
+ [convolutional]
382
+ batch_normalize=1
383
+ filters=256
384
+ size=1
385
+ stride=1
386
+ pad=1
387
+ activation=leaky
388
+
389
+ [convolutional]
390
+ batch_normalize=1
391
+ filters=256
392
+ size=3
393
+ stride=1
394
+ pad=1
395
+ activation=leaky
396
+
397
+ [convolutional]
398
+ batch_normalize=1
399
+ filters=1024
400
+ size=1
401
+ stride=1
402
+ pad=1
403
+ activation=linear
404
+
405
+ [shortcut]
406
+ from=-4
407
+ activation=leaky
408
+
409
+ #Conv 5
410
+ [convolutional]
411
+ batch_normalize=1
412
+ filters=512
413
+ size=1
414
+ stride=1
415
+ pad=1
416
+ activation=leaky
417
+
418
+ [convolutional]
419
+ batch_normalize=1
420
+ filters=512
421
+ size=3
422
+ stride=2
423
+ pad=1
424
+ activation=leaky
425
+
426
+ [convolutional]
427
+ batch_normalize=1
428
+ filters=2048
429
+ size=1
430
+ stride=1
431
+ pad=1
432
+ activation=linear
433
+
434
+ [shortcut]
435
+ from=-4
436
+ activation=leaky
437
+
438
+ [convolutional]
439
+ batch_normalize=1
440
+ filters=512
441
+ size=1
442
+ stride=1
443
+ pad=1
444
+ activation=leaky
445
+
446
+ [convolutional]
447
+ batch_normalize=1
448
+ filters=512
449
+ size=3
450
+ stride=1
451
+ pad=1
452
+ activation=leaky
453
+
454
+ [convolutional]
455
+ batch_normalize=1
456
+ filters=2048
457
+ size=1
458
+ stride=1
459
+ pad=1
460
+ activation=linear
461
+
462
+ [shortcut]
463
+ from=-4
464
+ activation=leaky
465
+
466
+ [convolutional]
467
+ batch_normalize=1
468
+ filters=512
469
+ size=1
470
+ stride=1
471
+ pad=1
472
+ activation=leaky
473
+
474
+ [convolutional]
475
+ batch_normalize=1
476
+ filters=512
477
+ size=3
478
+ stride=1
479
+ pad=1
480
+ activation=leaky
481
+
482
+ [convolutional]
483
+ batch_normalize=1
484
+ filters=2048
485
+ size=1
486
+ stride=1
487
+ pad=1
488
+ activation=linear
489
+
490
+ [shortcut]
491
+ from=-4
492
+ activation=leaky
493
+
494
+
495
+
496
+
497
+
498
+ [avgpool]
499
+
500
+ [convolutional]
501
+ filters=1000
502
+ size=1
503
+ stride=1
504
+ pad=1
505
+ activation=linear
506
+
507
+ [softmax]
508
+ groups=1
509
+
510
+
model/cfg/resnext101-32x4d.cfg ADDED
@@ -0,0 +1,1053 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [net]
2
+ # Training
3
+ # batch=128
4
+ # subdivisions=8
5
+
6
+ # Testing
7
+ batch=1
8
+ subdivisions=1
9
+
10
+ height=256
11
+ width=256
12
+ channels=3
13
+ min_crop=128
14
+ max_crop=448
15
+
16
+ burn_in=1000
17
+ learning_rate=0.1
18
+ policy=poly
19
+ power=4
20
+ max_batches=800000
21
+ momentum=0.9
22
+ decay=0.0005
23
+
24
+ angle=7
25
+ hue=.1
26
+ saturation=.75
27
+ exposure=.75
28
+ aspect=.75
29
+
30
+
31
+
32
+ [convolutional]
33
+ batch_normalize=1
34
+ filters=64
35
+ size=7
36
+ stride=2
37
+ pad=1
38
+ activation=leaky
39
+
40
+ [maxpool]
41
+ size=2
42
+ stride=2
43
+
44
+ [convolutional]
45
+ batch_normalize=1
46
+ filters=64
47
+ size=1
48
+ stride=1
49
+ pad=1
50
+ activation=leaky
51
+
52
+ [convolutional]
53
+ groups = 32
54
+ batch_normalize=1
55
+ filters=64
56
+ size=3
57
+ stride=1
58
+ pad=1
59
+ activation=leaky
60
+
61
+ [convolutional]
62
+ batch_normalize=1
63
+ filters=512
64
+ size=1
65
+ stride=1
66
+ pad=1
67
+ activation=linear
68
+
69
+ [shortcut]
70
+ from=-4
71
+ activation=leaky
72
+
73
+
74
+ [convolutional]
75
+ batch_normalize=1
76
+ filters=64
77
+ size=1
78
+ stride=1
79
+ pad=1
80
+ activation=leaky
81
+
82
+ [convolutional]
83
+ groups = 32
84
+ batch_normalize=1
85
+ filters=64
86
+ size=3
87
+ stride=1
88
+ pad=1
89
+ activation=leaky
90
+
91
+ [convolutional]
92
+ batch_normalize=1
93
+ filters=512
94
+ size=1
95
+ stride=1
96
+ pad=1
97
+ activation=linear
98
+
99
+ [shortcut]
100
+ from=-4
101
+ activation=leaky
102
+
103
+
104
+ [convolutional]
105
+ batch_normalize=1
106
+ filters=64
107
+ size=1
108
+ stride=1
109
+ pad=1
110
+ activation=leaky
111
+
112
+ [convolutional]
113
+ groups = 32
114
+ batch_normalize=1
115
+ filters=64
116
+ size=3
117
+ stride=1
118
+ pad=1
119
+ activation=leaky
120
+
121
+ [convolutional]
122
+ batch_normalize=1
123
+ filters=512
124
+ size=1
125
+ stride=1
126
+ pad=1
127
+ activation=linear
128
+
129
+ [shortcut]
130
+ from=-4
131
+ activation=leaky
132
+
133
+
134
+
135
+ [convolutional]
136
+ batch_normalize=1
137
+ filters=128
138
+ size=1
139
+ stride=1
140
+ pad=1
141
+ activation=leaky
142
+
143
+ [convolutional]
144
+ groups = 32
145
+ batch_normalize=1
146
+ filters=128
147
+ size=3
148
+ stride=2
149
+ pad=1
150
+ activation=leaky
151
+
152
+ [convolutional]
153
+ batch_normalize=1
154
+ filters=1024
155
+ size=1
156
+ stride=1
157
+ pad=1
158
+ activation=linear
159
+
160
+ [shortcut]
161
+ from=-4
162
+ activation=leaky
163
+
164
+
165
+
166
+ [convolutional]
167
+ batch_normalize=1
168
+ filters=128
169
+ size=1
170
+ stride=1
171
+ pad=1
172
+ activation=leaky
173
+
174
+ [convolutional]
175
+ groups = 32
176
+ batch_normalize=1
177
+ filters=128
178
+ size=3
179
+ stride=1
180
+ pad=1
181
+ activation=leaky
182
+
183
+ [convolutional]
184
+ batch_normalize=1
185
+ filters=1024
186
+ size=1
187
+ stride=1
188
+ pad=1
189
+ activation=linear
190
+
191
+ [shortcut]
192
+ from=-4
193
+ activation=leaky
194
+
195
+
196
+ [convolutional]
197
+ batch_normalize=1
198
+ filters=128
199
+ size=1
200
+ stride=1
201
+ pad=1
202
+ activation=leaky
203
+
204
+ [convolutional]
205
+ groups = 32
206
+ batch_normalize=1
207
+ filters=128
208
+ size=3
209
+ stride=1
210
+ pad=1
211
+ activation=leaky
212
+
213
+ [convolutional]
214
+ batch_normalize=1
215
+ filters=1024
216
+ size=1
217
+ stride=1
218
+ pad=1
219
+ activation=linear
220
+
221
+ [shortcut]
222
+ from=-4
223
+ activation=leaky
224
+
225
+
226
+ [convolutional]
227
+ batch_normalize=1
228
+ filters=128
229
+ size=1
230
+ stride=1
231
+ pad=1
232
+ activation=leaky
233
+
234
+ [convolutional]
235
+ groups = 32
236
+ batch_normalize=1
237
+ filters=128
238
+ size=3
239
+ stride=1
240
+ pad=1
241
+ activation=leaky
242
+
243
+ [convolutional]
244
+ batch_normalize=1
245
+ filters=1024
246
+ size=1
247
+ stride=1
248
+ pad=1
249
+ activation=linear
250
+
251
+ [shortcut]
252
+ from=-4
253
+ activation=leaky
254
+
255
+
256
+
257
+ [convolutional]
258
+ batch_normalize=1
259
+ filters=256
260
+ size=1
261
+ stride=1
262
+ pad=1
263
+ activation=leaky
264
+
265
+ [convolutional]
266
+ groups = 32
267
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274
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282
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287
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288
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296
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305
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313
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318
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326
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365
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373
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416
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485
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506
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566
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583
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588
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626
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635
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665
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686
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716
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720
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721
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725
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733
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737
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738
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741
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742
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746
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768
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776
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785
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793
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806
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815
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823
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827
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828
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832
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833
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835
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836
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840
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841
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845
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849
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853
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861
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866
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870
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871
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875
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883
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896
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897
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898
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899
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900
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901
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902
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904
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905
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910
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913
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914
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916
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917
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918
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919
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920
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921
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922
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923
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924
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925
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926
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927
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928
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930
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931
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932
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933
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934
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935
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936
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939
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941
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943
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947
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948
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949
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953
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957
+ [convolutional]
958
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961
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962
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966
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971
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972
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973
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974
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975
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976
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977
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978
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979
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980
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981
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983
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985
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986
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988
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989
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992
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997
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998
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1000
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1001
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1003
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1004
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1005
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1009
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1010
+ [convolutional]
1011
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1012
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1013
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1014
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1015
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1016
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1017
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1018
+ [convolutional]
1019
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1020
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1021
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1022
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1023
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1024
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1025
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1026
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1027
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1028
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1029
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1030
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1031
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1032
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1033
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1034
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1035
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1036
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1037
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1038
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1039
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1040
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1041
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1042
+ [avgpool]
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1044
+ [convolutional]
1045
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1046
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1047
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1048
+ pad=1
1049
+ activation=linear
1050
+
1051
+ [softmax]
1052
+ groups=1
1053
+
model/cfg/resnext152-32x4d.cfg ADDED
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1544
+ [shortcut]
1545
+ from=-4
1546
+ activation=leaky
1547
+
1548
+
1549
+
1550
+
1551
+ [avgpool]
1552
+
1553
+ [convolutional]
1554
+ filters=1000
1555
+ size=1
1556
+ stride=1
1557
+ pad=1
1558
+ activation=linear
1559
+
1560
+ [softmax]
1561
+ groups=1
1562
+
model/cfg/resnext50.cfg ADDED
@@ -0,0 +1,523 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [net]
2
+ # Training
3
+ # batch=128
4
+ # subdivisions=4
5
+
6
+ # Testing
7
+ batch=1
8
+ subdivisions=1
9
+
10
+ height=256
11
+ width=256
12
+ channels=3
13
+ min_crop=128
14
+ max_crop=448
15
+
16
+ burn_in=1000
17
+ learning_rate=0.1
18
+ policy=poly
19
+ power=4
20
+ max_batches=800000
21
+ momentum=0.9
22
+ decay=0.0005
23
+
24
+ angle=7
25
+ hue=.1
26
+ saturation=.75
27
+ exposure=.75
28
+ aspect=.75
29
+
30
+
31
+
32
+ [convolutional]
33
+ batch_normalize=1
34
+ filters=64
35
+ size=7
36
+ stride=2
37
+ pad=1
38
+ activation=leaky
39
+
40
+ [maxpool]
41
+ size=2
42
+ stride=2
43
+
44
+ [convolutional]
45
+ batch_normalize=1
46
+ filters=128
47
+ size=1
48
+ stride=1
49
+ pad=1
50
+ activation=leaky
51
+
52
+ [convolutional]
53
+ batch_normalize=1
54
+ filters=128
55
+ size=3
56
+ groups=32
57
+ stride=1
58
+ pad=1
59
+ activation=leaky
60
+
61
+ [convolutional]
62
+ batch_normalize=1
63
+ filters=256
64
+ size=1
65
+ stride=1
66
+ pad=1
67
+ activation=linear
68
+
69
+ [shortcut]
70
+ from=-4
71
+ activation=leaky
72
+
73
+ [convolutional]
74
+ batch_normalize=1
75
+ filters=128
76
+ size=1
77
+ stride=1
78
+ pad=1
79
+ activation=leaky
80
+
81
+ [convolutional]
82
+ batch_normalize=1
83
+ filters=128
84
+ size=3
85
+ groups=32
86
+ stride=1
87
+ pad=1
88
+ activation=leaky
89
+
90
+ [convolutional]
91
+ batch_normalize=1
92
+ filters=256
93
+ size=1
94
+ stride=1
95
+ pad=1
96
+ activation=linear
97
+
98
+ [shortcut]
99
+ from=-4
100
+ activation=leaky
101
+
102
+ [convolutional]
103
+ batch_normalize=1
104
+ filters=128
105
+ size=1
106
+ stride=1
107
+ pad=1
108
+ activation=leaky
109
+
110
+ [convolutional]
111
+ batch_normalize=1
112
+ filters=128
113
+ size=3
114
+ groups=32
115
+ stride=1
116
+ pad=1
117
+ activation=leaky
118
+
119
+ [convolutional]
120
+ batch_normalize=1
121
+ filters=256
122
+ size=1
123
+ stride=1
124
+ pad=1
125
+ activation=linear
126
+
127
+ [shortcut]
128
+ from=-4
129
+ activation=leaky
130
+
131
+ [convolutional]
132
+ batch_normalize=1
133
+ filters=256
134
+ size=1
135
+ stride=1
136
+ pad=1
137
+ activation=leaky
138
+
139
+ [convolutional]
140
+ batch_normalize=1
141
+ filters=256
142
+ size=3
143
+ groups=32
144
+ stride=2
145
+ pad=1
146
+ activation=leaky
147
+
148
+ [convolutional]
149
+ batch_normalize=1
150
+ filters=512
151
+ size=1
152
+ stride=1
153
+ pad=1
154
+ activation=linear
155
+
156
+ [shortcut]
157
+ from=-4
158
+ activation=leaky
159
+
160
+ [convolutional]
161
+ batch_normalize=1
162
+ filters=256
163
+ size=1
164
+ stride=1
165
+ pad=1
166
+ activation=leaky
167
+
168
+ [convolutional]
169
+ batch_normalize=1
170
+ filters=256
171
+ size=3
172
+ groups=32
173
+ stride=1
174
+ pad=1
175
+ activation=leaky
176
+
177
+ [convolutional]
178
+ batch_normalize=1
179
+ filters=512
180
+ size=1
181
+ stride=1
182
+ pad=1
183
+ activation=linear
184
+
185
+ [shortcut]
186
+ from=-4
187
+ activation=leaky
188
+
189
+ [convolutional]
190
+ batch_normalize=1
191
+ filters=256
192
+ size=1
193
+ stride=1
194
+ pad=1
195
+ activation=leaky
196
+
197
+ [convolutional]
198
+ batch_normalize=1
199
+ filters=256
200
+ size=3
201
+ groups=32
202
+ stride=1
203
+ pad=1
204
+ activation=leaky
205
+
206
+ [convolutional]
207
+ batch_normalize=1
208
+ filters=512
209
+ size=1
210
+ stride=1
211
+ pad=1
212
+ activation=linear
213
+
214
+ [shortcut]
215
+ from=-4
216
+ activation=leaky
217
+
218
+ [convolutional]
219
+ batch_normalize=1
220
+ filters=256
221
+ size=1
222
+ stride=1
223
+ pad=1
224
+ activation=leaky
225
+
226
+ [convolutional]
227
+ batch_normalize=1
228
+ filters=256
229
+ size=3
230
+ groups=32
231
+ stride=1
232
+ pad=1
233
+ activation=leaky
234
+
235
+ [convolutional]
236
+ batch_normalize=1
237
+ filters=512
238
+ size=1
239
+ stride=1
240
+ pad=1
241
+ activation=linear
242
+
243
+ [shortcut]
244
+ from=-4
245
+ activation=leaky
246
+
247
+
248
+ # Conv 4
249
+ [convolutional]
250
+ batch_normalize=1
251
+ filters=512
252
+ size=1
253
+ stride=1
254
+ pad=1
255
+ activation=leaky
256
+
257
+ [convolutional]
258
+ batch_normalize=1
259
+ filters=512
260
+ size=3
261
+ groups=32
262
+ stride=2
263
+ pad=1
264
+ activation=leaky
265
+
266
+ [convolutional]
267
+ batch_normalize=1
268
+ filters=1024
269
+ size=1
270
+ stride=1
271
+ pad=1
272
+ activation=linear
273
+
274
+ [shortcut]
275
+ from=-4
276
+ activation=leaky
277
+
278
+ [convolutional]
279
+ batch_normalize=1
280
+ filters=512
281
+ size=1
282
+ stride=1
283
+ pad=1
284
+ activation=leaky
285
+
286
+ [convolutional]
287
+ batch_normalize=1
288
+ filters=512
289
+ size=3
290
+ groups=32
291
+ stride=1
292
+ pad=1
293
+ activation=leaky
294
+
295
+ [convolutional]
296
+ batch_normalize=1
297
+ filters=1024
298
+ size=1
299
+ stride=1
300
+ pad=1
301
+ activation=linear
302
+
303
+ [shortcut]
304
+ from=-4
305
+ activation=leaky
306
+
307
+ [convolutional]
308
+ batch_normalize=1
309
+ filters=512
310
+ size=1
311
+ stride=1
312
+ pad=1
313
+ activation=leaky
314
+
315
+ [convolutional]
316
+ batch_normalize=1
317
+ filters=512
318
+ size=3
319
+ groups=32
320
+ stride=1
321
+ pad=1
322
+ activation=leaky
323
+
324
+ [convolutional]
325
+ batch_normalize=1
326
+ filters=1024
327
+ size=1
328
+ stride=1
329
+ pad=1
330
+ activation=linear
331
+
332
+ [shortcut]
333
+ from=-4
334
+ activation=leaky
335
+
336
+ [convolutional]
337
+ batch_normalize=1
338
+ filters=512
339
+ size=1
340
+ stride=1
341
+ pad=1
342
+ activation=leaky
343
+
344
+ [convolutional]
345
+ batch_normalize=1
346
+ filters=512
347
+ size=3
348
+ groups=32
349
+ stride=1
350
+ pad=1
351
+ activation=leaky
352
+
353
+ [convolutional]
354
+ batch_normalize=1
355
+ filters=1024
356
+ size=1
357
+ stride=1
358
+ pad=1
359
+ activation=linear
360
+
361
+ [shortcut]
362
+ from=-4
363
+ activation=leaky
364
+
365
+ [convolutional]
366
+ batch_normalize=1
367
+ filters=512
368
+ size=1
369
+ stride=1
370
+ pad=1
371
+ activation=leaky
372
+
373
+ [convolutional]
374
+ batch_normalize=1
375
+ filters=512
376
+ size=3
377
+ groups=32
378
+ stride=1
379
+ pad=1
380
+ activation=leaky
381
+
382
+ [convolutional]
383
+ batch_normalize=1
384
+ filters=1024
385
+ size=1
386
+ stride=1
387
+ pad=1
388
+ activation=linear
389
+
390
+ [shortcut]
391
+ from=-4
392
+ activation=leaky
393
+
394
+ [convolutional]
395
+ batch_normalize=1
396
+ filters=512
397
+ size=1
398
+ stride=1
399
+ pad=1
400
+ activation=leaky
401
+
402
+ [convolutional]
403
+ batch_normalize=1
404
+ filters=512
405
+ size=3
406
+ groups=32
407
+ stride=1
408
+ pad=1
409
+ activation=leaky
410
+
411
+ [convolutional]
412
+ batch_normalize=1
413
+ filters=1024
414
+ size=1
415
+ stride=1
416
+ pad=1
417
+ activation=linear
418
+
419
+ [shortcut]
420
+ from=-4
421
+ activation=leaky
422
+
423
+ #Conv 5
424
+ [convolutional]
425
+ batch_normalize=1
426
+ filters=1024
427
+ size=1
428
+ stride=1
429
+ pad=1
430
+ activation=leaky
431
+
432
+ [convolutional]
433
+ batch_normalize=1
434
+ filters=1024
435
+ size=3
436
+ groups=32
437
+ stride=2
438
+ pad=1
439
+ activation=leaky
440
+
441
+ [convolutional]
442
+ batch_normalize=1
443
+ filters=2048
444
+ size=1
445
+ stride=1
446
+ pad=1
447
+ activation=linear
448
+
449
+ [shortcut]
450
+ from=-4
451
+ activation=leaky
452
+
453
+ [convolutional]
454
+ batch_normalize=1
455
+ filters=1024
456
+ size=1
457
+ stride=1
458
+ pad=1
459
+ activation=leaky
460
+
461
+ [convolutional]
462
+ batch_normalize=1
463
+ filters=1024
464
+ size=3
465
+ groups=32
466
+ stride=1
467
+ pad=1
468
+ activation=leaky
469
+
470
+ [convolutional]
471
+ batch_normalize=1
472
+ filters=2048
473
+ size=1
474
+ stride=1
475
+ pad=1
476
+ activation=linear
477
+
478
+ [shortcut]
479
+ from=-4
480
+ activation=leaky
481
+
482
+ [convolutional]
483
+ batch_normalize=1
484
+ filters=1024
485
+ size=1
486
+ stride=1
487
+ pad=1
488
+ activation=leaky
489
+
490
+ [convolutional]
491
+ batch_normalize=1
492
+ filters=1024
493
+ size=3
494
+ groups=32
495
+ stride=1
496
+ pad=1
497
+ activation=leaky
498
+
499
+ [convolutional]
500
+ batch_normalize=1
501
+ filters=2048
502
+ size=1
503
+ stride=1
504
+ pad=1
505
+ activation=linear
506
+
507
+ [shortcut]
508
+ from=-4
509
+ activation=leaky
510
+
511
+ [avgpool]
512
+
513
+ [convolutional]
514
+ filters=1000
515
+ size=1
516
+ stride=1
517
+ pad=1
518
+ activation=linear
519
+
520
+ [softmax]
521
+ groups=1
522
+
523
+
model/cfg/rnn.cfg ADDED
@@ -0,0 +1,38 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [net]
2
+ subdivisions=1
3
+ inputs=256
4
+ batch = 1
5
+ momentum=0.9
6
+ decay=0.001
7
+ max_batches = 2000
8
+ time_steps=1
9
+ learning_rate=0.1
10
+ policy=steps
11
+ steps=1000,1500
12
+ scales=.1,.1
13
+
14
+ [rnn]
15
+ batch_normalize=1
16
+ output = 1024
17
+ hidden=1024
18
+ activation=leaky
19
+
20
+ [rnn]
21
+ batch_normalize=1
22
+ output = 1024
23
+ hidden=1024
24
+ activation=leaky
25
+
26
+ [rnn]
27
+ batch_normalize=1
28
+ output = 1024
29
+ hidden=1024
30
+ activation=leaky
31
+
32
+ [connected]
33
+ output=256
34
+ activation=leaky
35
+
36
+ [softmax]
37
+
38
+
model/cfg/rnn.train.cfg ADDED
@@ -0,0 +1,38 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [net]
2
+ subdivisions=1
3
+ inputs=256
4
+ batch = 128
5
+ momentum=0.9
6
+ decay=0.001
7
+ max_batches = 2000
8
+ time_steps=576
9
+ learning_rate=0.1
10
+ policy=steps
11
+ steps=1000,1500
12
+ scales=.1,.1
13
+
14
+ [rnn]
15
+ batch_normalize=1
16
+ output = 1024
17
+ hidden=1024
18
+ activation=leaky
19
+
20
+ [rnn]
21
+ batch_normalize=1
22
+ output = 1024
23
+ hidden=1024
24
+ activation=leaky
25
+
26
+ [rnn]
27
+ batch_normalize=1
28
+ output = 1024
29
+ hidden=1024
30
+ activation=leaky
31
+
32
+ [connected]
33
+ output=256
34
+ activation=leaky
35
+
36
+ [softmax]
37
+
38
+
model/cfg/strided.cfg ADDED
@@ -0,0 +1,182 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [net]
2
+ batch=128
3
+ subdivisions=4
4
+ height=256
5
+ width=256
6
+ channels=3
7
+ momentum=0.9
8
+ decay=0.0005
9
+
10
+ learning_rate=0.01
11
+ policy=steps
12
+ scales=.1,.1,.1
13
+ steps=200000,300000,400000
14
+ max_batches=800000
15
+
16
+
17
+ [crop]
18
+ crop_height=224
19
+ crop_width=224
20
+ flip=1
21
+ angle=0
22
+ saturation=1
23
+ exposure=1
24
+ shift=.2
25
+
26
+ [convolutional]
27
+ filters=64
28
+ size=7
29
+ stride=2
30
+ pad=1
31
+ activation=ramp
32
+
33
+ [convolutional]
34
+ filters=192
35
+ size=3
36
+ stride=2
37
+ pad=1
38
+ activation=ramp
39
+
40
+ [convolutional]
41
+ filters=128
42
+ size=1
43
+ stride=1
44
+ pad=1
45
+ activation=ramp
46
+
47
+ [convolutional]
48
+ filters=256
49
+ size=3
50
+ stride=2
51
+ pad=1
52
+ activation=ramp
53
+
54
+ [convolutional]
55
+ filters=128
56
+ size=1
57
+ stride=1
58
+ pad=1
59
+ activation=ramp
60
+
61
+ [convolutional]
62
+ filters=256
63
+ size=3
64
+ stride=1
65
+ pad=1
66
+ activation=ramp
67
+
68
+ [convolutional]
69
+ filters=128
70
+ size=1
71
+ stride=1
72
+ pad=1
73
+ activation=ramp
74
+
75
+ [convolutional]
76
+ filters=512
77
+ size=3
78
+ stride=2
79
+ pad=1
80
+ activation=ramp
81
+
82
+ [convolutional]
83
+ filters=256
84
+ size=1
85
+ stride=1
86
+ pad=1
87
+ activation=ramp
88
+
89
+ [convolutional]
90
+ filters=512
91
+ size=3
92
+ stride=1
93
+ pad=1
94
+ activation=ramp
95
+
96
+ [convolutional]
97
+ filters=256
98
+ size=1
99
+ stride=1
100
+ pad=1
101
+ activation=ramp
102
+
103
+ [convolutional]
104
+ filters=512
105
+ size=3
106
+ stride=1
107
+ pad=1
108
+ activation=ramp
109
+
110
+ [convolutional]
111
+ filters=256
112
+ size=1
113
+ stride=1
114
+ pad=1
115
+ activation=ramp
116
+
117
+ [convolutional]
118
+ filters=512
119
+ size=3
120
+ stride=1
121
+ pad=1
122
+ activation=ramp
123
+
124
+ [convolutional]
125
+ filters=256
126
+ size=1
127
+ stride=1
128
+ pad=1
129
+ activation=ramp
130
+
131
+ [convolutional]
132
+ filters=512
133
+ size=3
134
+ stride=1
135
+ pad=1
136
+ activation=ramp
137
+
138
+ [convolutional]
139
+ filters=256
140
+ size=1
141
+ stride=1
142
+ pad=1
143
+ activation=ramp
144
+
145
+ [convolutional]
146
+ filters=1024
147
+ size=3
148
+ stride=2
149
+ pad=1
150
+ activation=ramp
151
+
152
+ [convolutional]
153
+ filters=512
154
+ size=1
155
+ stride=1
156
+ pad=1
157
+ activation=ramp
158
+
159
+ [convolutional]
160
+ filters=1024
161
+ size=3
162
+ stride=1
163
+ pad=1
164
+ activation=ramp
165
+
166
+ [maxpool]
167
+ size=3
168
+ stride=2
169
+
170
+ [connected]
171
+ output=4096
172
+ activation=ramp
173
+
174
+ [dropout]
175
+ probability=0.5
176
+
177
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model/cfg/t1.test.cfg ADDED
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model/cfg/tiny.cfg ADDED
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1
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3
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174
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model/cfg/vgg-16.cfg ADDED
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model/cfg/vgg-conv.cfg ADDED
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118
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120
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model/cfg/voc.data ADDED
@@ -0,0 +1,6 @@
 
 
 
 
 
 
 
1
+ classes= 20
2
+ train = /home/pjreddie/data/voc/train.txt
3
+ valid = /home/pjreddie/data/voc/2007_test.txt
4
+ names = data/voc.names
5
+ backup = backup
6
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model/cfg/writing.cfg ADDED
@@ -0,0 +1,41 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
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2
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3
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39
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40
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41
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model/cfg/yolo9000.cfg ADDED
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1
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167
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175
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176
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183
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184
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191
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192
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198
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208
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213
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216
+
217
+ tree=data/9k.tree
218
+ map = data/coco9k.map
model/cfg/yolov1-tiny.cfg ADDED
@@ -0,0 +1,130 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [net]
2
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3
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4
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6
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7
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14
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112
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116
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126
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128
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129
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130
+
model/cfg/yolov1.cfg ADDED
@@ -0,0 +1,261 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
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2
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3
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4
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6
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7
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8
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107
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115
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116
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123
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124
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131
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132
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134
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137
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139
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140
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141
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142
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143
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146
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147
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148
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155
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156
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163
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167
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175
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176
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182
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183
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184
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185
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187
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188
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189
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190
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191
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192
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193
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194
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195
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196
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197
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198
+
199
+ #######
200
+
201
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202
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203
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204
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205
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206
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207
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208
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209
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210
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211
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212
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213
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214
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215
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216
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217
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218
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219
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220
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221
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222
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223
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224
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225
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226
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227
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228
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229
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230
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231
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232
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233
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234
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235
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237
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238
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239
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240
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241
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243
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244
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246
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247
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248
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249
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250
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251
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252
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253
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254
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255
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256
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257
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258
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259
+ class_scale=1
260
+ coord_scale=5
261
+
model/cfg/yolov2-tiny-voc.cfg ADDED
@@ -0,0 +1,138 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [net]
2
+ # Testing
3
+ batch=1
4
+ subdivisions=1
5
+ # Training
6
+ # batch=64
7
+ # subdivisions=2
8
+ width=416
9
+ height=416
10
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11
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12
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13
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14
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15
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16
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18
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22
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23
+
24
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25
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26
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27
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28
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29
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30
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31
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32
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33
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34
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35
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36
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37
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39
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40
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42
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44
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45
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46
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48
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51
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52
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54
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55
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56
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57
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58
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59
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60
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61
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62
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63
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64
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65
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66
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67
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68
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70
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72
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76
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77
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78
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79
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80
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81
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82
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83
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84
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85
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86
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87
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88
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89
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90
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91
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92
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93
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94
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95
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96
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97
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98
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99
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100
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101
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102
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103
+
104
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105
+
106
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107
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108
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109
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110
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111
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112
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113
+
114
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115
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116
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117
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118
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119
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120
+
121
+ [region]
122
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123
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124
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125
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126
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127
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128
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131
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132
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133
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134
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135
+
136
+ absolute=1
137
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138
+ random=1
model/cfg/yolov2-tiny.cfg ADDED
@@ -0,0 +1,139 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [net]
2
+ # Testing
3
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4
+ subdivisions=1
5
+ # Training
6
+ # batch=64
7
+ # subdivisions=2
8
+ width=416
9
+ height=416
10
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11
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12
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13
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14
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15
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18
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24
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25
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26
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27
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28
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29
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30
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31
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32
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33
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34
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35
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36
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37
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38
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39
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40
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41
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42
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43
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44
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45
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46
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47
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48
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49
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50
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52
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53
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54
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55
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56
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57
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60
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61
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62
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63
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64
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65
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66
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67
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68
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69
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70
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71
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72
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73
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74
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77
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79
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81
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82
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83
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84
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85
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86
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87
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88
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89
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90
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91
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92
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93
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94
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95
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97
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98
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99
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101
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102
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103
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104
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105
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106
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107
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108
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109
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110
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111
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112
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113
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114
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115
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116
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117
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118
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119
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120
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121
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122
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123
+ anchors = 0.57273, 0.677385, 1.87446, 2.06253, 3.33843, 5.47434, 7.88282, 3.52778, 9.77052, 9.16828
124
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125
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126
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127
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128
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129
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130
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131
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132
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133
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134
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135
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136
+
137
+ absolute=1
138
+ thresh = .6
139
+ random=1
model/cfg/yolov2-voc.cfg ADDED
@@ -0,0 +1,258 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [net]
2
+ # Testing
3
+ batch=1
4
+ subdivisions=1
5
+ # Training
6
+ # batch=64
7
+ # subdivisions=8
8
+ height=416
9
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10
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11
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12
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15
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18
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101
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105
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113
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121
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129
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137
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145
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149
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157
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165
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173
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181
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189
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190
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191
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192
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193
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194
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195
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197
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200
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208
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211
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219
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222
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225
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227
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228
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229
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230
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233
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235
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237
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238
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239
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240
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241
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243
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251
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253
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254
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255
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256
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257
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258
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model/cfg/yolov2.cfg ADDED
@@ -0,0 +1,258 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
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2
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3
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4
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6
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7
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8
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18
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25
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26
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33
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37
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45
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49
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73
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77
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85
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121
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145
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149
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157
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181
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189
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190
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191
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192
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193
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200
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208
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211
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217
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219
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222
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225
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232
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233
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234
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235
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237
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239
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240
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241
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242
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243
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251
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252
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253
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254
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255
+
256
+ absolute=1
257
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258
+ random=1
model/cfg/yolov3-openimages.cfg ADDED
@@ -0,0 +1,789 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [net]
2
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3
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4
+ subdivisions=1
5
+ # Training
6
+ batch=64
7
+ subdivisions=16
8
+ width=608
9
+ height=608
10
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11
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12
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14
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15
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16
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18
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23
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25
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26
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27
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28
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29
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30
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31
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32
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33
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34
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35
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36
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37
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38
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39
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40
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43
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51
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52
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54
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55
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56
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57
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58
+
59
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60
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61
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62
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63
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64
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65
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66
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67
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68
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69
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70
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73
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81
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89
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93
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101
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106
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107
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108
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109
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110
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111
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112
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113
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114
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115
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116
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117
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119
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120
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123
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131
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139
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143
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151
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159
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163
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171
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179
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183
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191
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199
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203
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204
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212
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220
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224
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240
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252
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280
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284
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285
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286
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459
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460
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461
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549
+ ######################
550
+
551
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606
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607
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608
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609
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610
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617
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621
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629
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692
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693
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696
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703
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719
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722
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723
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724
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772
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779
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780
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783
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+ random=1
789
+
model/cfg/yolov3-spp.cfg ADDED
@@ -0,0 +1,822 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [net]
2
+ # Testing
3
+ batch=1
4
+ subdivisions=1
5
+ # Training
6
+ # batch=64
7
+ # subdivisions=16
8
+ width=608
9
+ height=608
10
+ channels=3
11
+ momentum=0.9
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13
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14
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15
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16
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+
18
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+ burn_in=1000
20
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21
+ policy=steps
22
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23
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24
+
25
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26
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27
+ filters=32
28
+ size=3
29
+ stride=1
30
+ pad=1
31
+ activation=leaky
32
+
33
+ # Downsample
34
+
35
+ [convolutional]
36
+ batch_normalize=1
37
+ filters=64
38
+ size=3
39
+ stride=2
40
+ pad=1
41
+ activation=leaky
42
+
43
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44
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45
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46
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47
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48
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49
+ activation=leaky
50
+
51
+ [convolutional]
52
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53
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54
+ size=3
55
+ stride=1
56
+ pad=1
57
+ activation=leaky
58
+
59
+ [shortcut]
60
+ from=-3
61
+ activation=linear
62
+
63
+ # Downsample
64
+
65
+ [convolutional]
66
+ batch_normalize=1
67
+ filters=128
68
+ size=3
69
+ stride=2
70
+ pad=1
71
+ activation=leaky
72
+
73
+ [convolutional]
74
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75
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76
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77
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78
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79
+ activation=leaky
80
+
81
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82
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83
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84
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85
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86
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87
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88
+
89
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90
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91
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92
+
93
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94
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95
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96
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97
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98
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99
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100
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101
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102
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103
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104
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105
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106
+ pad=1
107
+ activation=leaky
108
+
109
+ [shortcut]
110
+ from=-3
111
+ activation=linear
112
+
113
+ # Downsample
114
+
115
+ [convolutional]
116
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117
+ filters=256
118
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119
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120
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121
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122
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123
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124
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125
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126
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127
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128
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129
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130
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131
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132
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133
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134
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135
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136
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137
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138
+
139
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140
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141
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142
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143
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144
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145
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146
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147
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148
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149
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150
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151
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152
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153
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154
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155
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156
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157
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158
+
159
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160
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161
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162
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163
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164
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165
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166
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167
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168
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169
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171
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172
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173
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174
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175
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179
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183
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184
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185
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186
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187
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188
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189
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+
191
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192
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194
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195
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196
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+
199
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202
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203
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204
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205
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206
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207
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208
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209
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210
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211
+
212
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213
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214
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215
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216
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217
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218
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+
220
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224
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226
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227
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228
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229
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230
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232
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233
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234
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235
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236
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240
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244
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245
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246
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247
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248
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249
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250
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251
+
252
+ [convolutional]
253
+ batch_normalize=1
254
+ filters=256
255
+ size=3
256
+ stride=1
257
+ pad=1
258
+ activation=leaky
259
+
260
+ [shortcut]
261
+ from=-3
262
+ activation=linear
263
+
264
+ [convolutional]
265
+ batch_normalize=1
266
+ filters=128
267
+ size=1
268
+ stride=1
269
+ pad=1
270
+ activation=leaky
271
+
272
+ [convolutional]
273
+ batch_normalize=1
274
+ filters=256
275
+ size=3
276
+ stride=1
277
+ pad=1
278
+ activation=leaky
279
+
280
+ [shortcut]
281
+ from=-3
282
+ activation=linear
283
+
284
+ # Downsample
285
+
286
+ [convolutional]
287
+ batch_normalize=1
288
+ filters=512
289
+ size=3
290
+ stride=2
291
+ pad=1
292
+ activation=leaky
293
+
294
+ [convolutional]
295
+ batch_normalize=1
296
+ filters=256
297
+ size=1
298
+ stride=1
299
+ pad=1
300
+ activation=leaky
301
+
302
+ [convolutional]
303
+ batch_normalize=1
304
+ filters=512
305
+ size=3
306
+ stride=1
307
+ pad=1
308
+ activation=leaky
309
+
310
+ [shortcut]
311
+ from=-3
312
+ activation=linear
313
+
314
+
315
+ [convolutional]
316
+ batch_normalize=1
317
+ filters=256
318
+ size=1
319
+ stride=1
320
+ pad=1
321
+ activation=leaky
322
+
323
+ [convolutional]
324
+ batch_normalize=1
325
+ filters=512
326
+ size=3
327
+ stride=1
328
+ pad=1
329
+ activation=leaky
330
+
331
+ [shortcut]
332
+ from=-3
333
+ activation=linear
334
+
335
+
336
+ [convolutional]
337
+ batch_normalize=1
338
+ filters=256
339
+ size=1
340
+ stride=1
341
+ pad=1
342
+ activation=leaky
343
+
344
+ [convolutional]
345
+ batch_normalize=1
346
+ filters=512
347
+ size=3
348
+ stride=1
349
+ pad=1
350
+ activation=leaky
351
+
352
+ [shortcut]
353
+ from=-3
354
+ activation=linear
355
+
356
+
357
+ [convolutional]
358
+ batch_normalize=1
359
+ filters=256
360
+ size=1
361
+ stride=1
362
+ pad=1
363
+ activation=leaky
364
+
365
+ [convolutional]
366
+ batch_normalize=1
367
+ filters=512
368
+ size=3
369
+ stride=1
370
+ pad=1
371
+ activation=leaky
372
+
373
+ [shortcut]
374
+ from=-3
375
+ activation=linear
376
+
377
+ [convolutional]
378
+ batch_normalize=1
379
+ filters=256
380
+ size=1
381
+ stride=1
382
+ pad=1
383
+ activation=leaky
384
+
385
+ [convolutional]
386
+ batch_normalize=1
387
+ filters=512
388
+ size=3
389
+ stride=1
390
+ pad=1
391
+ activation=leaky
392
+
393
+ [shortcut]
394
+ from=-3
395
+ activation=linear
396
+
397
+
398
+ [convolutional]
399
+ batch_normalize=1
400
+ filters=256
401
+ size=1
402
+ stride=1
403
+ pad=1
404
+ activation=leaky
405
+
406
+ [convolutional]
407
+ batch_normalize=1
408
+ filters=512
409
+ size=3
410
+ stride=1
411
+ pad=1
412
+ activation=leaky
413
+
414
+ [shortcut]
415
+ from=-3
416
+ activation=linear
417
+
418
+
419
+ [convolutional]
420
+ batch_normalize=1
421
+ filters=256
422
+ size=1
423
+ stride=1
424
+ pad=1
425
+ activation=leaky
426
+
427
+ [convolutional]
428
+ batch_normalize=1
429
+ filters=512
430
+ size=3
431
+ stride=1
432
+ pad=1
433
+ activation=leaky
434
+
435
+ [shortcut]
436
+ from=-3
437
+ activation=linear
438
+
439
+ [convolutional]
440
+ batch_normalize=1
441
+ filters=256
442
+ size=1
443
+ stride=1
444
+ pad=1
445
+ activation=leaky
446
+
447
+ [convolutional]
448
+ batch_normalize=1
449
+ filters=512
450
+ size=3
451
+ stride=1
452
+ pad=1
453
+ activation=leaky
454
+
455
+ [shortcut]
456
+ from=-3
457
+ activation=linear
458
+
459
+ # Downsample
460
+
461
+ [convolutional]
462
+ batch_normalize=1
463
+ filters=1024
464
+ size=3
465
+ stride=2
466
+ pad=1
467
+ activation=leaky
468
+
469
+ [convolutional]
470
+ batch_normalize=1
471
+ filters=512
472
+ size=1
473
+ stride=1
474
+ pad=1
475
+ activation=leaky
476
+
477
+ [convolutional]
478
+ batch_normalize=1
479
+ filters=1024
480
+ size=3
481
+ stride=1
482
+ pad=1
483
+ activation=leaky
484
+
485
+ [shortcut]
486
+ from=-3
487
+ activation=linear
488
+
489
+ [convolutional]
490
+ batch_normalize=1
491
+ filters=512
492
+ size=1
493
+ stride=1
494
+ pad=1
495
+ activation=leaky
496
+
497
+ [convolutional]
498
+ batch_normalize=1
499
+ filters=1024
500
+ size=3
501
+ stride=1
502
+ pad=1
503
+ activation=leaky
504
+
505
+ [shortcut]
506
+ from=-3
507
+ activation=linear
508
+
509
+ [convolutional]
510
+ batch_normalize=1
511
+ filters=512
512
+ size=1
513
+ stride=1
514
+ pad=1
515
+ activation=leaky
516
+
517
+ [convolutional]
518
+ batch_normalize=1
519
+ filters=1024
520
+ size=3
521
+ stride=1
522
+ pad=1
523
+ activation=leaky
524
+
525
+ [shortcut]
526
+ from=-3
527
+ activation=linear
528
+
529
+ [convolutional]
530
+ batch_normalize=1
531
+ filters=512
532
+ size=1
533
+ stride=1
534
+ pad=1
535
+ activation=leaky
536
+
537
+ [convolutional]
538
+ batch_normalize=1
539
+ filters=1024
540
+ size=3
541
+ stride=1
542
+ pad=1
543
+ activation=leaky
544
+
545
+ [shortcut]
546
+ from=-3
547
+ activation=linear
548
+
549
+ ######################
550
+
551
+ [convolutional]
552
+ batch_normalize=1
553
+ filters=512
554
+ size=1
555
+ stride=1
556
+ pad=1
557
+ activation=leaky
558
+
559
+ [convolutional]
560
+ batch_normalize=1
561
+ size=3
562
+ stride=1
563
+ pad=1
564
+ filters=1024
565
+ activation=leaky
566
+
567
+ [convolutional]
568
+ batch_normalize=1
569
+ filters=512
570
+ size=1
571
+ stride=1
572
+ pad=1
573
+ activation=leaky
574
+
575
+ ### SPP ###
576
+ [maxpool]
577
+ stride=1
578
+ size=5
579
+
580
+ [route]
581
+ layers=-2
582
+
583
+ [maxpool]
584
+ stride=1
585
+ size=9
586
+
587
+ [route]
588
+ layers=-4
589
+
590
+ [maxpool]
591
+ stride=1
592
+ size=13
593
+
594
+ [route]
595
+ layers=-1,-3,-5,-6
596
+
597
+ ### End SPP ###
598
+
599
+ [convolutional]
600
+ batch_normalize=1
601
+ filters=512
602
+ size=1
603
+ stride=1
604
+ pad=1
605
+ activation=leaky
606
+
607
+
608
+ [convolutional]
609
+ batch_normalize=1
610
+ size=3
611
+ stride=1
612
+ pad=1
613
+ filters=1024
614
+ activation=leaky
615
+
616
+ [convolutional]
617
+ batch_normalize=1
618
+ filters=512
619
+ size=1
620
+ stride=1
621
+ pad=1
622
+ activation=leaky
623
+
624
+ [convolutional]
625
+ batch_normalize=1
626
+ size=3
627
+ stride=1
628
+ pad=1
629
+ filters=1024
630
+ activation=leaky
631
+
632
+ [convolutional]
633
+ size=1
634
+ stride=1
635
+ pad=1
636
+ filters=255
637
+ activation=linear
638
+
639
+
640
+ [yolo]
641
+ mask = 6,7,8
642
+ anchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326
643
+ classes=80
644
+ num=9
645
+ jitter=.3
646
+ ignore_thresh = .7
647
+ truth_thresh = 1
648
+ random=1
649
+
650
+
651
+ [route]
652
+ layers = -4
653
+
654
+ [convolutional]
655
+ batch_normalize=1
656
+ filters=256
657
+ size=1
658
+ stride=1
659
+ pad=1
660
+ activation=leaky
661
+
662
+ [upsample]
663
+ stride=2
664
+
665
+ [route]
666
+ layers = -1, 61
667
+
668
+
669
+
670
+ [convolutional]
671
+ batch_normalize=1
672
+ filters=256
673
+ size=1
674
+ stride=1
675
+ pad=1
676
+ activation=leaky
677
+
678
+ [convolutional]
679
+ batch_normalize=1
680
+ size=3
681
+ stride=1
682
+ pad=1
683
+ filters=512
684
+ activation=leaky
685
+
686
+ [convolutional]
687
+ batch_normalize=1
688
+ filters=256
689
+ size=1
690
+ stride=1
691
+ pad=1
692
+ activation=leaky
693
+
694
+ [convolutional]
695
+ batch_normalize=1
696
+ size=3
697
+ stride=1
698
+ pad=1
699
+ filters=512
700
+ activation=leaky
701
+
702
+ [convolutional]
703
+ batch_normalize=1
704
+ filters=256
705
+ size=1
706
+ stride=1
707
+ pad=1
708
+ activation=leaky
709
+
710
+ [convolutional]
711
+ batch_normalize=1
712
+ size=3
713
+ stride=1
714
+ pad=1
715
+ filters=512
716
+ activation=leaky
717
+
718
+ [convolutional]
719
+ size=1
720
+ stride=1
721
+ pad=1
722
+ filters=255
723
+ activation=linear
724
+
725
+
726
+ [yolo]
727
+ mask = 3,4,5
728
+ anchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326
729
+ classes=80
730
+ num=9
731
+ jitter=.3
732
+ ignore_thresh = .7
733
+ truth_thresh = 1
734
+ random=1
735
+
736
+
737
+
738
+ [route]
739
+ layers = -4
740
+
741
+ [convolutional]
742
+ batch_normalize=1
743
+ filters=128
744
+ size=1
745
+ stride=1
746
+ pad=1
747
+ activation=leaky
748
+
749
+ [upsample]
750
+ stride=2
751
+
752
+ [route]
753
+ layers = -1, 36
754
+
755
+
756
+
757
+ [convolutional]
758
+ batch_normalize=1
759
+ filters=128
760
+ size=1
761
+ stride=1
762
+ pad=1
763
+ activation=leaky
764
+
765
+ [convolutional]
766
+ batch_normalize=1
767
+ size=3
768
+ stride=1
769
+ pad=1
770
+ filters=256
771
+ activation=leaky
772
+
773
+ [convolutional]
774
+ batch_normalize=1
775
+ filters=128
776
+ size=1
777
+ stride=1
778
+ pad=1
779
+ activation=leaky
780
+
781
+ [convolutional]
782
+ batch_normalize=1
783
+ size=3
784
+ stride=1
785
+ pad=1
786
+ filters=256
787
+ activation=leaky
788
+
789
+ [convolutional]
790
+ batch_normalize=1
791
+ filters=128
792
+ size=1
793
+ stride=1
794
+ pad=1
795
+ activation=leaky
796
+
797
+ [convolutional]
798
+ batch_normalize=1
799
+ size=3
800
+ stride=1
801
+ pad=1
802
+ filters=256
803
+ activation=leaky
804
+
805
+ [convolutional]
806
+ size=1
807
+ stride=1
808
+ pad=1
809
+ filters=255
810
+ activation=linear
811
+
812
+
813
+ [yolo]
814
+ mask = 0,1,2
815
+ anchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326
816
+ classes=80
817
+ num=9
818
+ jitter=.3
819
+ ignore_thresh = .7
820
+ truth_thresh = 1
821
+ random=1
822
+