Please provide the following information when requesting support.
• Hardware (T4/V100/Xavier/Nano/etc) : A40
• Network Type (Detectnet_v2/Faster_rcnn/Yolo_v4/LPRnet/Mask_rcnn/Classification/etc) : Detectnet_v2
• TLT Version (Please run “tlt info --verbose” and share “docker_tag” here): nvidia/tao/tao-toolkit: 5.5.0-pyt
• Training spec file(If have, please share here)
• How to reproduce the issue ? (This is for errors. Please share the command line and the detailed log here.)
I have question regarding data augementation techniques availabel in tao.
Basically I have three questions:
a.) Available Data Augmentation techniques in Tao
b.)How we can select/configure Data Augmentation techniques while training a model using Tao .
c.) How can we integrate custom data Augmentation technique to tao that is not available in tao by default.
The default Augmentation config I can see for DetectNet V2 is as below:
augmentation_config {
preprocessing {
output_image_width: 1248
output_image_height: 384
min_bbox_width: 1.0
min_bbox_height: 1.0
output_image_channel: 3
}
spatial_augmentation {
hflip_probability: 0.5
zoom_min: 1.0
zoom_max: 1.0
translate_max_x: 8.0
translate_max_y: 8.0
}
color_augmentation {
hue_rotation_max: 25.0
saturation_shift_max: 0.20000000298
contrast_scale_max: 0.10000000149
contrast_center: 0.5
}
}
This is also specified here in the DetectnetV2 Docs: DetectNet_v2 - NVIDIA Docs
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