Compatibility range of conversion
You can use LaunchX converter to automatically convert the AI model's framework to the target framework.
Converting case
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Compatible model
The input layer of the uploaded model should be as follows.
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- 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.
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 |
Updated 10 months ago