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yolov3-tiny_obj.cfg - is example for training custom objects
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,182 @@ | ||
| [net] | ||
| # Testing | ||
| #batch=1 | ||
| #subdivisions=1 | ||
| # Training | ||
| batch=64 | ||
| subdivisions=2 | ||
| width=416 | ||
| height=416 | ||
| channels=3 | ||
| momentum=0.9 | ||
| decay=0.0005 | ||
| angle=0 | ||
| saturation = 1.5 | ||
| exposure = 1.5 | ||
| hue=.1 | ||
|
|
||
| learning_rate=0.001 | ||
| burn_in=1000 | ||
| max_batches = 500200 | ||
| policy=steps | ||
| steps=400000,450000 | ||
| scales=.1,.1 | ||
|
|
||
| [convolutional] | ||
| batch_normalize=1 | ||
| filters=16 | ||
| size=3 | ||
| stride=1 | ||
| pad=1 | ||
| activation=leaky | ||
|
|
||
| [maxpool] | ||
| size=2 | ||
| stride=2 | ||
|
|
||
| [convolutional] | ||
| batch_normalize=1 | ||
| filters=32 | ||
| size=3 | ||
| stride=1 | ||
| pad=1 | ||
| activation=leaky | ||
|
|
||
| [maxpool] | ||
| size=2 | ||
| stride=2 | ||
|
|
||
| [convolutional] | ||
| batch_normalize=1 | ||
| filters=64 | ||
| size=3 | ||
| stride=1 | ||
| pad=1 | ||
| activation=leaky | ||
|
|
||
| [maxpool] | ||
| size=2 | ||
| stride=2 | ||
|
|
||
| [convolutional] | ||
| batch_normalize=1 | ||
| filters=128 | ||
| size=3 | ||
| stride=1 | ||
| pad=1 | ||
| activation=leaky | ||
|
|
||
| [maxpool] | ||
| size=2 | ||
| stride=2 | ||
|
|
||
| [convolutional] | ||
| batch_normalize=1 | ||
| filters=256 | ||
| size=3 | ||
| stride=1 | ||
| pad=1 | ||
| activation=leaky | ||
|
|
||
| [maxpool] | ||
| size=2 | ||
| stride=2 | ||
|
|
||
| [convolutional] | ||
| batch_normalize=1 | ||
| filters=512 | ||
| size=3 | ||
| stride=1 | ||
| pad=1 | ||
| activation=leaky | ||
|
|
||
| [maxpool] | ||
| size=2 | ||
| stride=1 | ||
|
|
||
| [convolutional] | ||
| batch_normalize=1 | ||
| filters=1024 | ||
| size=3 | ||
| stride=1 | ||
| pad=1 | ||
| activation=leaky | ||
|
|
||
| ########### | ||
|
|
||
| [convolutional] | ||
| batch_normalize=1 | ||
| filters=256 | ||
| size=1 | ||
| stride=1 | ||
| pad=1 | ||
| activation=leaky | ||
|
|
||
| [convolutional] | ||
| batch_normalize=1 | ||
| filters=512 | ||
| size=3 | ||
| stride=1 | ||
| pad=1 | ||
| activation=leaky | ||
|
|
||
| [convolutional] | ||
| size=1 | ||
| stride=1 | ||
| pad=1 | ||
| filters=255 | ||
| activation=linear | ||
|
|
||
|
|
||
|
|
||
| [yolo] | ||
| mask = 3,4,5 | ||
| anchors = 10,14, 23,27, 37,58, 81,82, 135,169, 344,319 | ||
| classes=80 | ||
| num=6 | ||
| jitter=.3 | ||
| ignore_thresh = .7 | ||
| truth_thresh = 1 | ||
| random=1 | ||
|
|
||
| [route] | ||
| layers = -4 | ||
|
|
||
| [convolutional] | ||
| batch_normalize=1 | ||
| filters=128 | ||
| size=1 | ||
| stride=1 | ||
| pad=1 | ||
| activation=leaky | ||
|
|
||
| [upsample] | ||
| stride=2 | ||
|
|
||
| [route] | ||
| layers = -1, 8 | ||
|
|
||
| [convolutional] | ||
| batch_normalize=1 | ||
| filters=256 | ||
| size=3 | ||
| stride=1 | ||
| pad=1 | ||
| activation=leaky | ||
|
|
||
| [convolutional] | ||
| size=1 | ||
| stride=1 | ||
| pad=1 | ||
| filters=255 | ||
| activation=linear | ||
|
|
||
| [yolo] | ||
| mask = 0,1,2 | ||
| anchors = 10,14, 23,27, 37,58, 81,82, 135,169, 344,319 | ||
| classes=80 | ||
| num=6 | ||
| jitter=.3 | ||
| ignore_thresh = .7 | ||
| truth_thresh = 1 | ||
| random=1 |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,182 @@ | ||
| [net] | ||
| # Testing | ||
| #batch=1 | ||
| #subdivisions=1 | ||
| # Training | ||
| batch=64 | ||
| subdivisions=2 | ||
| width=416 | ||
| height=416 | ||
| channels=3 | ||
| momentum=0.9 | ||
| decay=0.0005 | ||
| angle=0 | ||
| saturation = 1.5 | ||
| exposure = 1.5 | ||
| hue=.1 | ||
|
|
||
| learning_rate=0.001 | ||
| burn_in=1000 | ||
| max_batches = 500200 | ||
| policy=steps | ||
| steps=400000,450000 | ||
| scales=.1,.1 | ||
|
|
||
| [convolutional] | ||
| batch_normalize=1 | ||
| filters=16 | ||
| size=3 | ||
| stride=1 | ||
| pad=1 | ||
| activation=leaky | ||
|
|
||
| [maxpool] | ||
| size=2 | ||
| stride=2 | ||
|
|
||
| [convolutional] | ||
| batch_normalize=1 | ||
| filters=32 | ||
| size=3 | ||
| stride=1 | ||
| pad=1 | ||
| activation=leaky | ||
|
|
||
| [maxpool] | ||
| size=2 | ||
| stride=2 | ||
|
|
||
| [convolutional] | ||
| batch_normalize=1 | ||
| filters=64 | ||
| size=3 | ||
| stride=1 | ||
| pad=1 | ||
| activation=leaky | ||
|
|
||
| [maxpool] | ||
| size=2 | ||
| stride=2 | ||
|
|
||
| [convolutional] | ||
| batch_normalize=1 | ||
| filters=128 | ||
| size=3 | ||
| stride=1 | ||
| pad=1 | ||
| activation=leaky | ||
|
|
||
| [maxpool] | ||
| size=2 | ||
| stride=2 | ||
|
|
||
| [convolutional] | ||
| batch_normalize=1 | ||
| filters=256 | ||
| size=3 | ||
| stride=1 | ||
| pad=1 | ||
| activation=leaky | ||
|
|
||
| [maxpool] | ||
| size=2 | ||
| stride=2 | ||
|
|
||
| [convolutional] | ||
| batch_normalize=1 | ||
| filters=512 | ||
| size=3 | ||
| stride=1 | ||
| pad=1 | ||
| activation=leaky | ||
|
|
||
| [maxpool] | ||
| size=2 | ||
| stride=1 | ||
|
|
||
| [convolutional] | ||
| batch_normalize=1 | ||
| filters=1024 | ||
| size=3 | ||
| stride=1 | ||
| pad=1 | ||
| activation=leaky | ||
|
|
||
| ########### | ||
|
|
||
| [convolutional] | ||
| batch_normalize=1 | ||
| filters=256 | ||
| size=1 | ||
| stride=1 | ||
| pad=1 | ||
| activation=leaky | ||
|
|
||
| [convolutional] | ||
| batch_normalize=1 | ||
| filters=512 | ||
| size=3 | ||
| stride=1 | ||
| pad=1 | ||
| activation=leaky | ||
|
|
||
| [convolutional] | ||
| size=1 | ||
| stride=1 | ||
| pad=1 | ||
| filters=255 | ||
| activation=linear | ||
|
|
||
|
|
||
|
|
||
| [yolo] | ||
| mask = 3,4,5 | ||
| anchors = 10,14, 23,27, 37,58, 81,82, 135,169, 344,319 | ||
| classes=80 | ||
| num=6 | ||
| jitter=.3 | ||
| ignore_thresh = .7 | ||
| truth_thresh = 1 | ||
| random=1 | ||
|
|
||
| [route] | ||
| layers = -4 | ||
|
|
||
| [convolutional] | ||
| batch_normalize=1 | ||
| filters=128 | ||
| size=1 | ||
| stride=1 | ||
| pad=1 | ||
| activation=leaky | ||
|
|
||
| [upsample] | ||
| stride=2 | ||
|
|
||
| [route] | ||
| layers = -1, 8 | ||
|
|
||
| [convolutional] | ||
| batch_normalize=1 | ||
| filters=256 | ||
| size=3 | ||
| stride=1 | ||
| pad=1 | ||
| activation=leaky | ||
|
|
||
| [convolutional] | ||
| size=1 | ||
| stride=1 | ||
| pad=1 | ||
| filters=255 | ||
| activation=linear | ||
|
|
||
| [yolo] | ||
| mask = 0,1,2 | ||
| anchors = 10,14, 23,27, 37,58, 81,82, 135,169, 344,319 | ||
| classes=80 | ||
| num=6 | ||
| jitter=.3 | ||
| ignore_thresh = .7 | ||
| truth_thresh = 1 | ||
| random=1 |