How to train a customising OCDNET model in Tao

Please provide the following information when requesting support.
• Hardware :- RTX A4000
• Network Type :- OCD
• TLT Version (Please run “tlt info --verbose” and share “docker_tag” here) nvidia/tao/tao-toolkit: 5.0.0-tf2.11.0
• Training spec file(If have, please share here) default tao notabook of ocd

I have a ship container dataset. I want to train an OCD model for text detection in containers.
How to annotate and train in the Tao model

You can refer to and

morganh I’ve already read it as well as tried it.
cat ICDAR2015/test/gt/gt_img_14.txt
How did annotated this format? in my ship container images

Do you mean how to generate a label file?
Actually the format follows ICDAR2015 as below mentioned in

x1, y1, x2, y2, x3, y3, x4, y4, transcription

yes how to generate label file for custom datasets on x1, y1, x2, y2, x3, y3, x4, y4, transcription this format ?

To generate label file, firstly you need to label the object. You can use some label tools. For example, “labelme”.
Then draw bbox and save the coordinates and the transcription. The labelme will save to a json file, then you can do some conversion to change to expected format.


ok i will try it

Thanks issue has been resolve

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