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commit yolo configures without weight

master
Jeong Geol Kim 4 лет назад
Родитель
Сommit
b65039a79f
3 измененных файлов: 800 добавлений и 0 удалений
  1. 793
    0
      cfg.cfg
  2. 5
    0
      data.data
  3. 2
    0
      names.names

+ 793
- 0
cfg.cfg Просмотреть файл

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+[net]
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+# Testing
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+# batch=1
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+# subdivisions=1
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+# Training
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+#Created: 2019-10-08 20:16
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+#Changes:
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+#In Line 721 stride=2 to 4
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+#In Line 724 layers= to -1,11
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+batch=64
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+subdivisions=32
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+width=960
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+height=540
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+channels=3
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+momentum=0.9
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+decay=0.0005
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+angle=0
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+saturation = 1.5
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+exposure = 1.5
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+hue=.1
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+
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+learning_rate=0.001
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+burn_in=1000
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+max_batches = 500200
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+policy=steps
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+steps=400000,450000
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+scales=.1,.1
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+
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+[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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+pad=1
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+activation=leaky
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+
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+# Downsample
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+
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+[convolutional]
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+batch_normalize=1
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+filters=64
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+size=3
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+stride=2
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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=32
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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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+
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+[convolutional]
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+batch_normalize=1
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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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+
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+[shortcut]
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+from=-3
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+activation=linear
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+
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+# Downsample
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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=2
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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=64
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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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+
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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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+[shortcut]
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+from=-3
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+activation=linear
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+
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+[convolutional]
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+batch_normalize=1
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+filters=64
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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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+
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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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+[shortcut]
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+from=-3
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+activation=linear
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+
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+# Downsample
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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=2
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+pad=1
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+activation=leaky
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+
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+[convolutional]
128
+batch_normalize=1
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+filters=128
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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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+
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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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+
143
+[shortcut]
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+from=-3
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+activation=linear
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+
147
+[convolutional]
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+batch_normalize=1
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+filters=128
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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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+
155
+[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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+
163
+[shortcut]
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+from=-3
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+activation=linear
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+
167
+[convolutional]
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+batch_normalize=1
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+filters=128
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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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+
175
+[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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+
183
+[shortcut]
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+from=-3
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+activation=linear
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+
187
+[convolutional]
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+batch_normalize=1
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+filters=128
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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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+
195
+[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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+
203
+[shortcut]
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+from=-3
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+activation=linear
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+
207
+
208
+[convolutional]
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+batch_normalize=1
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+filters=128
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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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+
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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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+
224
+[shortcut]
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+from=-3
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+activation=linear
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+
228
+[convolutional]
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+batch_normalize=1
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+filters=128
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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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+
236
+[convolutional]
237
+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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+
244
+[shortcut]
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+from=-3
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+activation=linear
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+
248
+[convolutional]
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+batch_normalize=1
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+filters=128
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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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+
256
+[convolutional]
257
+batch_normalize=1
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+filters=256
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+size=3
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+stride=1
261
+pad=1
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+activation=leaky
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+
264
+[shortcut]
265
+from=-3
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+activation=linear
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+
268
+[convolutional]
269
+batch_normalize=1
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+filters=128
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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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+
276
+[convolutional]
277
+batch_normalize=1
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+filters=256
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+size=3
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+stride=1
281
+pad=1
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+activation=leaky
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+
284
+[shortcut]
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+from=-3
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+activation=linear
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+
288
+# Downsample
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+
290
+[convolutional]
291
+batch_normalize=1
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+filters=512
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+size=3
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+stride=2
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+pad=1
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+activation=leaky
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+
298
+[convolutional]
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+batch_normalize=1
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+filters=256
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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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+
306
+[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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+
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+[shortcut]
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+from=-3
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+activation=linear
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+
318
+
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+[convolutional]
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+batch_normalize=1
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+filters=256
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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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+
327
+[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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+
335
+[shortcut]
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+from=-3
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+activation=linear
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+
339
+
340
+[convolutional]
341
+batch_normalize=1
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+filters=256
343
+size=1
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+stride=1
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+pad=1
346
+activation=leaky
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+
348
+[convolutional]
349
+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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+
356
+[shortcut]
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+from=-3
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+activation=linear
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+
360
+
361
+[convolutional]
362
+batch_normalize=1
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+filters=256
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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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+
369
+[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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+
377
+[shortcut]
378
+from=-3
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+activation=linear
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+
381
+[convolutional]
382
+batch_normalize=1
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+filters=256
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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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+
389
+[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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+
397
+[shortcut]
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+from=-3
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+activation=linear
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+
401
+
402
+[convolutional]
403
+batch_normalize=1
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+filters=256
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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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+
410
+[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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+
418
+[shortcut]
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+from=-3
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+activation=linear
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+
422
+
423
+[convolutional]
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+batch_normalize=1
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+filters=256
426
+size=1
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+stride=1
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+pad=1
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+activation=leaky
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+
431
+[convolutional]
432
+batch_normalize=1
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+filters=512
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+size=3
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+stride=1
436
+pad=1
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+activation=leaky
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+
439
+[shortcut]
440
+from=-3
441
+activation=linear
442
+
443
+[convolutional]
444
+batch_normalize=1
445
+filters=256
446
+size=1
447
+stride=1
448
+pad=1
449
+activation=leaky
450
+
451
+[convolutional]
452
+batch_normalize=1
453
+filters=512
454
+size=3
455
+stride=1
456
+pad=1
457
+activation=leaky
458
+
459
+[shortcut]
460
+from=-3
461
+activation=linear
462
+
463
+# Downsample
464
+
465
+[convolutional]
466
+batch_normalize=1
467
+filters=1024
468
+size=3
469
+stride=2
470
+pad=1
471
+activation=leaky
472
+
473
+[convolutional]
474
+batch_normalize=1
475
+filters=512
476
+size=1
477
+stride=1
478
+pad=1
479
+activation=leaky
480
+
481
+[convolutional]
482
+batch_normalize=1
483
+filters=1024
484
+size=3
485
+stride=1
486
+pad=1
487
+activation=leaky
488
+
489
+[shortcut]
490
+from=-3
491
+activation=linear
492
+
493
+[convolutional]
494
+batch_normalize=1
495
+filters=512
496
+size=1
497
+stride=1
498
+pad=1
499
+activation=leaky
500
+
501
+[convolutional]
502
+batch_normalize=1
503
+filters=1024
504
+size=3
505
+stride=1
506
+pad=1
507
+activation=leaky
508
+
509
+[shortcut]
510
+from=-3
511
+activation=linear
512
+
513
+[convolutional]
514
+batch_normalize=1
515
+filters=512
516
+size=1
517
+stride=1
518
+pad=1
519
+activation=leaky
520
+
521
+[convolutional]
522
+batch_normalize=1
523
+filters=1024
524
+size=3
525
+stride=1
526
+pad=1
527
+activation=leaky
528
+
529
+[shortcut]
530
+from=-3
531
+activation=linear
532
+
533
+[convolutional]
534
+batch_normalize=1
535
+filters=512
536
+size=1
537
+stride=1
538
+pad=1
539
+activation=leaky
540
+
541
+[convolutional]
542
+batch_normalize=1
543
+filters=1024
544
+size=3
545
+stride=1
546
+pad=1
547
+activation=leaky
548
+
549
+[shortcut]
550
+from=-3
551
+activation=linear
552
+
553
+######################
554
+
555
+[convolutional]
556
+batch_normalize=1
557
+filters=512
558
+size=1
559
+stride=1
560
+pad=1
561
+activation=leaky
562
+
563
+[convolutional]
564
+batch_normalize=1
565
+size=3
566
+stride=1
567
+pad=1
568
+filters=1024
569
+activation=leaky
570
+
571
+[convolutional]
572
+batch_normalize=1
573
+filters=512
574
+size=1
575
+stride=1
576
+pad=1
577
+activation=leaky
578
+
579
+[convolutional]
580
+batch_normalize=1
581
+size=3
582
+stride=1
583
+pad=1
584
+filters=1024
585
+activation=leaky
586
+
587
+[convolutional]
588
+batch_normalize=1
589
+filters=512
590
+size=1
591
+stride=1
592
+pad=1
593
+activation=leaky
594
+
595
+[convolutional]
596
+batch_normalize=1
597
+size=3
598
+stride=1
599
+pad=1
600
+filters=1024
601
+activation=leaky
602
+
603
+[convolutional]
604
+size=1
605
+stride=1
606
+pad=1
607
+filters=21
608
+activation=linear
609
+
610
+
611
+[yolo]
612
+mask = 6,7,8
613
+anchors = 10,13,  16,30,  33,23,  30,61,  62,45,  59,119,  116,90,  156,198,  373,326
614
+classes=2
615
+num=9
616
+jitter=.3
617
+ignore_thresh = .7
618
+truth_thresh = 1
619
+random=1
620
+
621
+
622
+[route]
623
+layers = -4
624
+
625
+[convolutional]
626
+batch_normalize=1
627
+filters=256
628
+size=1
629
+stride=1
630
+pad=1
631
+activation=leaky
632
+
633
+[upsample]
634
+stride=2
635
+
636
+[route]
637
+layers = -1, 61
638
+
639
+
640
+
641
+[convolutional]
642
+batch_normalize=1
643
+filters=256
644
+size=1
645
+stride=1
646
+pad=1
647
+activation=leaky
648
+
649
+[convolutional]
650
+batch_normalize=1
651
+size=3
652
+stride=1
653
+pad=1
654
+filters=512
655
+activation=leaky
656
+
657
+[convolutional]
658
+batch_normalize=1
659
+filters=256
660
+size=1
661
+stride=1
662
+pad=1
663
+activation=leaky
664
+
665
+[convolutional]
666
+batch_normalize=1
667
+size=3
668
+stride=1
669
+pad=1
670
+filters=512
671
+activation=leaky
672
+
673
+[convolutional]
674
+batch_normalize=1
675
+filters=256
676
+size=1
677
+stride=1
678
+pad=1
679
+activation=leaky
680
+
681
+[convolutional]
682
+batch_normalize=1
683
+size=3
684
+stride=1
685
+pad=1
686
+filters=512
687
+activation=leaky
688
+
689
+[convolutional]
690
+size=1
691
+stride=1
692
+pad=1
693
+filters=21
694
+activation=linear
695
+
696
+
697
+[yolo]
698
+mask = 3,4,5
699
+anchors = 10,13,  16,30,  33,23,  30,61,  62,45,  59,119,  116,90,  156,198,  373,326
700
+classes=2
701
+num=9
702
+jitter=.3
703
+ignore_thresh = .7
704
+truth_thresh = 1
705
+random=1
706
+
707
+
708
+
709
+[route]
710
+layers = -4
711
+
712
+[convolutional]
713
+batch_normalize=1
714
+filters=128
715
+size=1
716
+stride=1
717
+pad=1
718
+activation=leaky
719
+
720
+[upsample]
721
+stride=2
722
+
723
+[route]
724
+layers = -1, 36
725
+
726
+
727
+
728
+[convolutional]
729
+batch_normalize=1
730
+filters=128
731
+size=1
732
+stride=1
733
+pad=1
734
+activation=leaky
735
+
736
+[convolutional]
737
+batch_normalize=1
738
+size=3
739
+stride=1
740
+pad=1
741
+filters=256
742
+activation=leaky
743
+
744
+[convolutional]
745
+batch_normalize=1
746
+filters=128
747
+size=1
748
+stride=1
749
+pad=1
750
+activation=leaky
751
+
752
+[convolutional]
753
+batch_normalize=1
754
+size=3
755
+stride=1
756
+pad=1
757
+filters=256
758
+activation=leaky
759
+
760
+[convolutional]
761
+batch_normalize=1
762
+filters=128
763
+size=1
764
+stride=1
765
+pad=1
766
+activation=leaky
767
+
768
+[convolutional]
769
+batch_normalize=1
770
+size=3
771
+stride=1
772
+pad=1
773
+filters=256
774
+activation=leaky
775
+
776
+[convolutional]
777
+size=1
778
+stride=1
779
+pad=1
780
+filters=21
781
+activation=linear
782
+
783
+
784
+[yolo]
785
+mask = 0,1,2
786
+anchors = 10,13,  16,30,  33,23,  30,61,  62,45,  59,119,  116,90,  156,198,  373,326
787
+classes=2
788
+num=9
789
+jitter=.3
790
+ignore_thresh = .7
791
+truth_thresh = 1
792
+random=1
793
+

+ 5
- 0
data.data Просмотреть файл

@@ -0,0 +1,5 @@
1
+classes=2
2
+train=/tmp/darknet/365mc/dataset_v4/train.txt
3
+valid=/tmp/darknet/365mc/dataset_v4/valid.txt
4
+names=/sources/names.names
5
+backup=/tmp/darknet/365mc/dataset_v4/backup

+ 2
- 0
names.names Просмотреть файл

@@ -0,0 +1,2 @@
1
+bind	
2
+point

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