mirror of
https://github.com/pjreddie/darknet.git
synced 2023-08-10 21:13:14 +03:00
Updated cfg-files for new weights-files
This commit is contained in:
@ -1,6 +1,6 @@
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darknet.exe detector test data/voc.data yolo-voc.cfg yolo-voc.weights -i 0 -thresh 0.1
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darknet.exe detector test data/voc.data yolo-voc.cfg yolo-voc.weights -i 0 -thresh 0.2
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pause
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@ -12,7 +12,7 @@ exposure = 1.5
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hue=.1
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learning_rate=0.001
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max_batches = 40100
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max_batches = 40200
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policy=steps
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steps=-1,100,20000,30000
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scales=.1,10,.1,.1
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@ -1,6 +1,10 @@
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[net]
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batch=64
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subdivisions=8
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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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# batch=64
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# subdivisions=8
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height=416
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width=416
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channels=3
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@ -11,11 +15,12 @@ saturation = 1.5
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exposure = 1.5
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hue=.1
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learning_rate=0.0001
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max_batches = 45000
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learning_rate=0.001
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burn_in=1000
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max_batches = 80200
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policy=steps
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steps=100,25000,35000
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scales=10,.1,.1
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steps=40000,60000
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scales=.1,.1
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[convolutional]
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batch_normalize=1
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@ -203,11 +208,19 @@ activation=leaky
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[route]
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layers=-9
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[convolutional]
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batch_normalize=1
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size=1
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stride=1
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pad=1
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filters=64
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activation=leaky
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[reorg]
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stride=2
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[route]
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layers=-1,-3
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layers=-1,-4
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[convolutional]
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batch_normalize=1
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@ -224,14 +237,15 @@ pad=1
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filters=125
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activation=linear
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[region]
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anchors = 1.08,1.19, 3.42,4.41, 6.63,11.38, 9.42,5.11, 16.62,10.52
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anchors = 1.3221, 1.73145, 3.19275, 4.00944, 5.05587, 8.09892, 9.47112, 4.84053, 11.2364, 10.0071
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bias_match=1
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classes=20
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coords=4
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num=5
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softmax=1
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jitter=.2
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jitter=.3
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rescore=1
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object_scale=5
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@ -241,4 +255,4 @@ coord_scale=1
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absolute=1
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thresh = .6
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random=0
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random=1
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@ -1,8 +1,12 @@
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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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width=416
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# Training
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# batch=64
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# subdivisions=8
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height=416
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width=416
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channels=3
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momentum=0.9
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decay=0.0005
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@ -12,10 +16,11 @@ exposure = 1.5
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hue=.1
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learning_rate=0.001
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max_batches = 120000
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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=-1,100,80000,100000
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scales=.1,10,.1,.1
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steps=400000,450000
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scales=.1,.1
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[convolutional]
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batch_normalize=1
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@ -203,11 +208,19 @@ activation=leaky
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[route]
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layers=-9
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[convolutional]
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batch_normalize=1
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size=1
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stride=1
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pad=1
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filters=64
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activation=leaky
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[reorg]
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stride=2
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[route]
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layers=-1,-3
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layers=-1,-4
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[convolutional]
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batch_normalize=1
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@ -224,14 +237,15 @@ pad=1
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filters=425
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activation=linear
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[region]
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anchors = 0.738768,0.874946, 2.42204,2.65704, 4.30971,7.04493, 10.246,4.59428, 12.6868,11.8741
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anchors = 0.57273, 0.677385, 1.87446, 2.06253, 3.33843, 5.47434, 7.88282, 3.52778, 9.77052, 9.16828
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bias_match=1
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classes=80
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coords=4
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num=5
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softmax=1
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jitter=.2
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jitter=.3
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rescore=1
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object_scale=5
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@ -241,4 +255,4 @@ coord_scale=1
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absolute=1
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thresh = .6
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random=0
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random=1
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@ -12,7 +12,7 @@ exposure = 1.5
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hue=.1
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learning_rate=0.001
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max_batches = 40100
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max_batches = 40200
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policy=steps
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steps=-1,100,20000,30000
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scales=.1,10,.1,.1
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@ -1,6 +1,10 @@
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[net]
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batch=64
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subdivisions=8
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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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# batch=64
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# subdivisions=8
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height=416
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width=416
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channels=3
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@ -11,11 +15,12 @@ saturation = 1.5
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exposure = 1.5
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hue=.1
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learning_rate=0.0001
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max_batches = 45000
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learning_rate=0.001
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burn_in=1000
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max_batches = 80200
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policy=steps
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steps=100,25000,35000
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scales=10,.1,.1
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steps=40000,60000
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scales=.1,.1
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[convolutional]
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batch_normalize=1
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@ -203,11 +208,19 @@ activation=leaky
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[route]
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layers=-9
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[convolutional]
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batch_normalize=1
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size=1
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stride=1
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pad=1
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filters=64
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activation=leaky
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[reorg]
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stride=2
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[route]
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layers=-1,-3
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layers=-1,-4
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[convolutional]
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batch_normalize=1
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@ -224,14 +237,15 @@ pad=1
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filters=125
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activation=linear
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[region]
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anchors = 1.08,1.19, 3.42,4.41, 6.63,11.38, 9.42,5.11, 16.62,10.52
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anchors = 1.3221, 1.73145, 3.19275, 4.00944, 5.05587, 8.09892, 9.47112, 4.84053, 11.2364, 10.0071
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bias_match=1
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classes=20
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coords=4
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num=5
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softmax=1
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jitter=.2
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jitter=.3
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rescore=1
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object_scale=5
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@ -241,4 +255,4 @@ coord_scale=1
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absolute=1
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thresh = .6
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random=0
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random=1
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30
cfg/yolo.cfg
30
cfg/yolo.cfg
@ -1,8 +1,12 @@
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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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width=416
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# Training
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# batch=64
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# subdivisions=8
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height=416
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width=416
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channels=3
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momentum=0.9
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decay=0.0005
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@ -12,10 +16,11 @@ exposure = 1.5
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hue=.1
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learning_rate=0.001
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max_batches = 120000
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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=-1,100,80000,100000
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scales=.1,10,.1,.1
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steps=400000,450000
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scales=.1,.1
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[convolutional]
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batch_normalize=1
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@ -203,11 +208,19 @@ activation=leaky
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[route]
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layers=-9
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[convolutional]
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batch_normalize=1
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size=1
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stride=1
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pad=1
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filters=64
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activation=leaky
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[reorg]
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stride=2
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[route]
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layers=-1,-3
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layers=-1,-4
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[convolutional]
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batch_normalize=1
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@ -224,14 +237,15 @@ pad=1
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filters=425
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activation=linear
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[region]
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anchors = 0.738768,0.874946, 2.42204,2.65704, 4.30971,7.04493, 10.246,4.59428, 12.6868,11.8741
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anchors = 0.57273, 0.677385, 1.87446, 2.06253, 3.33843, 5.47434, 7.88282, 3.52778, 9.77052, 9.16828
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bias_match=1
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classes=80
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coords=4
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num=5
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softmax=1
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jitter=.2
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jitter=.3
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rescore=1
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object_scale=5
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@ -241,4 +255,4 @@ coord_scale=1
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absolute=1
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thresh = .6
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random=0
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random=1
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