Please provide the following information when requesting support.

• Hardware (T4/V100/Xavier/Nano/etc)
• Network Type (Detectnet_v2/Faster_rcnn/Yolo_v4/LPRnet/Mask_rcnn/Classification/etc)
UNET and SegFormer
• TLT Version (Please run “tlt info --verbose” and share “docker_tag” here)
TAO 3.22.05 and TAO 4.0
• 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 posted before about adapting UNET for multi-class segmentation, rather than semantic segmentation (UNET Training on Multi-Class Segmentation from Satellite Imagery (DSTL)).

I was wondering if there is a way to do the same for SegFormer? We have about 10+ classes and we are looking to segment the images.

Also, we would use MaskRCNN, but we want to use a more modern algorithm. Are there any plans on the roadmap to implement another SOTA Instance Segmentation algorithm?

Thank you for your time and help,


Yes, it is possible. Refer to SegFormer - NVIDIA Docs and also download latest notebook from TAO Toolkit Getting Started | NVIDIA NGC. More info can be also found in TAO 4 Segformer Input and output dimensions and tensors - #12 by Morganh.

Will sync internally for this feature request. Thanks.