All useful sample codes of TensorRT models using ONNX
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Generation TensorRT Model by using ONNX
1.1 TensorRT CPP API
1.2 TensorRT Python API
1.3 Polygraphy -
Dynamic shapes for TensorRT
2.1 Dynamic batch
2.2 Dynamic input size
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Custom Plugin
3.1 Adding a pre-processing layer by cuda -
Modifying an ONNX graph by ONNX GraphSurgeon
4.1 Extracting a feature map of the last Conv for Grad-Cam
4.2 Generating a TensorRT model with a custom plugin and ONNX -
TensorRT Model Optimizer
5.1 Explict Quantization (PTQ)
5.2 Explict Quantization (QAT)
5.3 Sparsity (2:4 sparsity pattern)
- Super Resolution
6.1 Real-ESRGAN - Object Detection
- Instance Segmentation
- Semantic Segmentation
- Depth Estimation
10.1 Depth Pro ( "It is under repair due to an accuracy issue.")