Step 2: Train a model

Range of Support

The model support range for NetsPresso's GUI is aligned with the scope supported by NetsPresso Trainer. The Trainer is organized into components of AI models, including Backbone, Neck, and Heads. For more detailed information, please refer to the NetsPresso Trainer documentation. (link)

The GUI supports options according to the table below.

Task	Model
Object Detection	YOLOX-S, YOLO-M, YOLO-L
Image Classification	EfficientFormer
Image Classification	MixNet-S, MixNet-M, MixNet-L
Image Classification	MobileNetV3-S, MobileNetV3-L
Image Classification	MobileViT-S
Image Classification	ResNet18, ResNet34, ResNet50
Image Classification	ViT-tiny
Semantic Segmentation	EfficientFormer
Semantic Segmentation	ResNet50
Semantic Segmentation	MobileNetV3-S
Semantic Segmentation	PIDNet
Semantic Segmentation	SegFormer-B0
Semantic Segmentation	MixNet-L, MixNet-M, MixNet-L

Sample Dataset

This section the explanation of training configurations. Once GUI is installed, three types of sample dataset is included. These dataset can be shown when you set your train experiments.

ℹ️
If you would like to upload your datasets, please upload your datasets under "datasets" directory.

Image Classification - Cifar100 (link)
Object Detection - Traffic Sign
Semantic Segmentation - VOC2012 (link)

Train Configuration

Output Model Name
Task/Model (Supported Model)
Dataset Directory
Image Size
Batch Size
Epochs
Optimizer (Supported Optimizer)
GPU option : Allows you to check the status of the installed GPU server.

Range of Support

Sample Dataset

ℹ️If you would like to upload your datasets, please upload your datasets under "datasets" directory.

Train Configuration

ℹ️
If you would like to upload your datasets, please upload your datasets under "datasets" directory.