Created
April 6, 2023 13:58
-
-
Save DanHutsul/2ca523d26da129341972d627cd611c22 to your computer and use it in GitHub Desktop.
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
| [net] | |
| # Testing | |
| batch=1 | |
| subdivisions=4 | |
| # Training | |
| # batch=64 | |
| # subdivisions=16 | |
| 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=32 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| # Downsample | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=64 | |
| size=3 | |
| stride=2 | |
| pad=1 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=32 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=64 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| # Downsample | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=3 | |
| stride=2 | |
| pad=1 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=64 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=64 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| # Downsample | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=3 | |
| stride=2 | |
| pad=1 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| # Downsample | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=3 | |
| stride=2 | |
| 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 | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [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 | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [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 | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [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 | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [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 | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [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 | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [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 | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [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 | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| # Downsample | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=1024 | |
| size=3 | |
| stride=2 | |
| pad=1 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=1024 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=1024 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=1024 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=1024 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [shortcut] | |
| from=-3 | |
| activation=linear | |
| ###################### | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| filters=1024 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| filters=1024 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=512 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| filters=1024 | |
| activation=leaky | |
| [convolutional] | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| filters=24 | |
| activation=linear | |
| [yolo] | |
| mask = 6,7,8 | |
| anchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326 | |
| classes=3 | |
| num=9 | |
| jitter=.3 | |
| ignore_thresh = .5 | |
| truth_thresh = 1 | |
| random=1 | |
| [route] | |
| layers = -4 | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [upsample] | |
| stride=2 | |
| [route] | |
| layers = -1, 61 | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| filters=512 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| filters=512 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=256 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| filters=512 | |
| activation=leaky | |
| [convolutional] | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| filters=24 | |
| activation=linear | |
| [yolo] | |
| mask = 3,4,5 | |
| anchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326 | |
| classes=3 | |
| num=9 | |
| jitter=.3 | |
| ignore_thresh = .5 | |
| 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, 36 | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| filters=256 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| filters=256 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| filters=128 | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| activation=leaky | |
| [convolutional] | |
| batch_normalize=1 | |
| size=3 | |
| stride=1 | |
| pad=1 | |
| filters=256 | |
| activation=leaky | |
| [convolutional] | |
| size=1 | |
| stride=1 | |
| pad=1 | |
| filters=24 | |
| activation=linear | |
| [yolo] | |
| mask = 0,1,2 | |
| anchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326 | |
| classes=3 | |
| num=9 | |
| jitter=.3 | |
| ignore_thresh = .5 | |
| truth_thresh = 1 | |
| random=1 | |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment