Please provide the following information when requesting support.
• Hardware (T4/V100/Xavier/Nano/etc)
Ubuntu 20.04.3 LTS, Intel x64, RTX3090.
• Network Type
• TLT Version (Please run “tlt info --verbose” and share “docker_tag” here)
tao info :
Configuration of the TAO Toolkit Instance
dockers: [‘nvidia/tao/tao-toolkit-tf’, ‘nvidia/tao/tao-toolkit-pyt’, ‘nvidia/tao/tao-toolkit-lm’]
• 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’m using TAO for transfer learning for detect several classes of objects in my scenario:
- custom door sticker
I believe the
bicycle can be retrieved from public with sufficient amount, but the
custom door sticker is collected by myself and would be very limited (say 1000 pictures with 1 target in each).
so my question:
- Will imbalanced dataset impact precison in transfer liearning in
TAOhas build-in functions to help extract part of data from public big dataset to align with custom small dataset?
Say I have the
PASCAL VOCdataset with 20 classes (or any other well known dataset), I want only extract
bicyclefrom it, further more, for these 2 classes, only 1000 samples of each are extracted, by combined with my custom small dataset, to finaly form a balance dataset for re-training.