A CLI tool to convert Keras models to ONNX models and TensorRT engines
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Updated
Dec 23, 2022 - Python
A CLI tool to convert Keras models to ONNX models and TensorRT engines
C++/C TensorRT Inference Example for models created with Pytorch/JAX/TF
Convert popular Deep learning models to TensorRT using C++ API (preferably)
Experimenting with Cifar-10 dataset to understand and implement various Deep Learning Techniques and CNN Architectures for Image Classification.
不同backend的模型转换与推理代码
This project is a notebook of learning TensorRT.
Jetson TX2 compatible TensorFlow's ssd_mobilenet_v2_coco for TensorRT 6 / JetPack 4.3
Based on tensorrt v8.0+, deploy detect, pose, segment of YOLOv8 with C++ and python api.
TensorRT implementation with Tensorflow 2
TensorRT optimises any Deep Learning model by not only making it lightweight but also by accelerating its inference speed with an idea to extract every ounce of performance from the model, making it perfect to be deployed at the edge. This repository helps you convert any Deep Learning model from TensorFlow to TensorRT!
Convenient Convert CRAFT Text detection pretrain Pytorch model into TensorRT engine directly, without ONNX step between
Tools for Nvidia Jetson Nano, TX2, Xavier.
Dockerized TensorRT inference engine with ONNX model conversion tool and ResNet50 and Ultraface preprocess and postprocess C++ implementation
Export (from Onnx) and Inference TensorRT engine with Python
Based on TensorRT v8.2, build network for YOLOv5-v5.0 by myself, speed up YOLOv5-v5.0 inferencing
Simple tool for PyTorch >> ONNX >> TensorRT conversion
tensorrt-toy code
Advance inference performance using TensorRT for CRAFT Text detection. Implemented modules to convert Pytorch -> ONNX -> TensorRT, with dynamic shapes (multi-size input) inference.
Convert yolo models to ONNX, TensorRT add NMSBatched.
Base on tensorrt version 8.2.4, compare inference speed for different tensorrt api.
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