Converter: Scope of support

Compatible model

The input layer of the uploaded model should be as follows.

Only single-input models are supported.
The four-dimensional array structure of images should be organized Batch, Number of Channels, Height, and Width.

Batch size: The number of combined input datasets that the model processes simultaneously.

Channel: 3 for RGB or BGR and 1 for Grayscale.

Input size: In computer vision tasks, input size refers to the size of the input images.

Converting case

ONNX to TensorRT

Supported JetPack-ONNX version

Target Device	JetPack version	Input datatype	Batch size	Channel	Input size	Output datatype
NVIDIA Jetson Nano	4.6, 4.4.1	FP32	1~4 (Static), Dynamic	1~4	height, width	FP16
NVIDIA Jetson Xavier NX	5.0.2, 4.6	FP32	1~4 (Static), Dynamic	1~4	height, width	FP16
NVIDIA Jetson TX2	4.6	FP32	1~4 (Static), Dynamic	1~4	height, width	FP16
NVIDIA Jetson AGX Xavier	4.6	FP32	1~4 (Static), Dynamic	1~4	height, width	FP16
NVIDIA Jetson AGX Orin	5.0.1	FP32	1~4 (Static), Dynamic	1~4	height, width	FP16
NVIDIA Jetson Orin Nano	6.0	FP32	1~4 (Static), Dynamic	1~4	height, width	FP16
NVIDIA T4		FP32	1~4 (Static), Dynamic	1~4	height, width	FP16

ONNX to TFlite

Input datatype	Batch size	Channel	Input size	Output datatype
FP32	1~4 (Static), Dynamic	1~4	height, width	FP16 INT8

ONNX to OpenVino

Input datatype	Batch size	Channel	Input size	Output datatype
FP32	1~4 (Static), Dynamic	1~4	height, width	FP16

TensorFlow to TensorFlowLite

Input datatype	Batch size	Channel	Input size	Output datatype
FP32	1~4 (Static, Dynamic)	1~4	height, width	FP16 INT8