Is it possible to generate .tfrecorfs for tlt training directly without using intermediate kitti format?

Hi,

I followed TLT Started Guide (https://docs.nvidia.com/metropolis/TLT/tlt-getting-started-guide/index.html) to prepare custom dataset for training object detection model using SSD MobileNet V1. Training and evaluation went well.

Now I have a question - is it possible to directly generate .tfrecord files for training without using tlt-dataset-convert tool? Is there any description of .tfrecord entries format for tlt, so I can generate these .tfrecord files directly from our dataset format without converting our dataset into kitti format and using tlt-dataset-convert tool as an intemediate step?

Thanks!

Actually you can. But seems that you will need more effort. Firstly, you can write script to dump the tfrecords you have generated in order to see its feature. Then based on your data, you should generate the new tfrecords which contain the same feature.
So, suggest you using tlt-dataset-convert.
The effort for you is just converting your label to kitti format. And the TLT training pipe supports training only for class and bbox coordinates. That means, take below typical KITTI format as an example,
car 0.00 0 0.00 587.01 173.33 614.12 200.12 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Only car, x1, y1,x2, y2 are needed when you write script to convert to KITTI format.
For example,

with open(new_label, ‘a’) as j:
j.write("{} 0.0 0 0.0 {:.5f} {:.5f} {:.5f} {:.5f} 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n".format(class_name,x1, y1,x2,y2))