Hello,
We are trying to do Data augmentation for Unet-Model but it looks like we are only limited to only a few methods on it
- spatial_augmentation
- brightness_augmentation
But I come across this https://docs.nvidia.com/tao/tao-toolkit/text/offline_data_augmentation.html#id2 the
page which has an extensive range of Augmentation functions but looks like these are only functional with KITTI Dataset can Somone help me if is there any prospect that I can use these functions with my UnetModel As well. Thanks in Advance !!!
• Hardware (T4]
• Network Type (Unet)
• TLT Version
Configuration of the TAO Toolkit Instance
dockers:
nvidia/tao/tao-toolkit-tf:
v3.21.11-tf1.15.5-py3:
docker_registry: nvcr.io
tasks:
1. augment
2. bpnet
v3.21.11-tf1.15.4-py3:
docker_registry: nvcr.io
tasks:
1. detectnet_v2
2. faster_rcnn
nvidia/tao/tao-toolkit-pyt:
v3.21.11-py3:
docker_registry: nvcr.io
tasks:
1. speech_to_text
2. speech_to_text_citrinet
3. text_classification
4. question_answering
5. token_classification
6. intent_slot_classification
7. punctuation_and_capitalization
8. spectro_gen
9. vocoder
10. action_recognition
nvidia/tao/tao-toolkit-lm:
v3.21.08-py3:
docker_registry: nvcr.io
tasks:
1. n_gram
format_version: 2.0
toolkit_version: 3.21.11
published_date: 11/08/2021
• Augmentation spec But its not working with UnetModel
spatial_config{
rotation_config{
angle: 5.0
units: "degrees"
}
shear_config{
shear_ratio_x: 0.3
}
translation_config{
translate_x: 8
}
}
color_config{
hue_saturation_config{
hue_rotation_angle: 25.0
saturation_shift: 1.0
}
}
dataset_config {
image_path: "/workspace/tao-experiments/Delivery2/*****/test/******_clip4.mp4.frame.33985.png"
label_path: "/workspace/tao-experiments/Delivery2/*****/testannot/*****_clip4.mp4.frame.33985.png"
}
output_image_width: 1920
output_image_height: 1080
output_image_channel: 3
image_extension: ".png"