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tao-train-segformer

Automate training, evaluation, export, and inference for NVIDIA TAO SegFormer models.

83|20|Updated Apr 16, 2026
Search Tags:#model training#model evaluation#model inference#model export#semantic segmentation#segformer
One-click install
npx skills add https://github.com/NVIDIA-TAO/tao-skill-bank --skill tao-train-segformer
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: tao-train-segformer
Source: https://github.com/NVIDIA-TAO/tao-skill-bank/tree/main/skills/models/tao-train-segformer
Command: npx skills add https://github.com/NVIDIA-TAO/tao-skill-bank --skill tao-train-segformer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires docker, nvidia-container-toolkit, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the training, evaluation, export, and inference processes for NVIDIA TAO SegFormer models, streamlining the workflow for semantic segmentation tasks.

Core Features & Use Cases

  • Model Training: Automates the training process for SegFormer models, including data augmentation, optimization, and checkpointing.
  • Evaluation: Evaluates trained models on a given dataset, providing metrics such as accuracy and MIoU.
  • Export: Exports trained models in various formats, including ONNX for inference.
  • Inference: Performs inference on new data using trained models.
  • Use Case: Suppose you need to train a SegFormer model for semantic segmentation on a custom dataset. This Skill allows you to define the dataset, configure the training parameters, and automatically perform the training, evaluation, and export of the model.

Quick Start

To train a SegFormer model on your dataset, use the tao-train-segformer skill with the following command:

tao-train-segformer train --dataset segment.root_dir <path_to_dataset> --num_epochs 10

Frequently Asked Questions about tao-train-segformer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I train a SegFormer model for semantic segmentation on a custom dataset?▼

To train a SegFormer model for semantic segmentation, you can use a dedicated Skill to define your dataset, configure parameters, and automate the training, evaluation, and export processes.

Does NVIDIA TAO SegFormer support exporting models to ONNX for inference?▼

Yes, NVIDIA TAO SegFormer supports exporting trained semantic segmentation models into various formats, including ONNX, to facilitate inference and model deployment.

Do I need Docker and NVIDIA Container Toolkit to run SegFormer training and evaluation?▼

Yes, executing the NVIDIA TAO SegFormer training, evaluation, and inference processes requires both Docker and the NVIDIA Container Toolkit to be installed in your environment.

What metrics are provided when evaluating a trained semantic segmentation model?▼

Evaluating a trained semantic segmentation model provides standard performance metrics such as accuracy and Mean Intersection over Union (MIoU) on the given dataset.

Can I use AutoML capabilities for semantic segmentation model training?▼

Yes, this approach supports model training with AutoML capabilities, allowing you to automate optimization and data augmentation while training SegFormer models for semantic segmentation.

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