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Deep Learning API and Server in C++14 support for Caffe, PyTorch,TensorRT, Dlib, NCNN, Tensorflow, XGBoost and TSNE
InsightFace REST API for easy deployment of face recognition services with TensorRT in Docker.
针对pytorch模型的自动化模型结构分析和修改工具集,包含自动分析模型结构的模型压缩算法库
Yolov5 TensorRT Implementations
Using TensorRT for Inference Model Deployment.
this is a tensorrt version unet, inspired by tensorrtx
Based on tensorrt v8.0+, deploy detect, pose, segment, tracking of YOLOv8 with C++ and python api.
Advanced inference pipeline using NVIDIA Triton Inference Server for CRAFT Text detection (Pytorch), included converter from Pytorch -> ONNX -> TensorRT, Inference pipelines (TensorRT, Triton server - multi-format). Supported model format for Triton inference: TensorRT engine, Torchscript, ONNX
VitPose without MMCV dependencies
Base on tensorrt version 8.2.4, compare inference speed for different tensorrt api.
The real-time Instance Segmentation Algorithm SparseInst running on TensoRT and ONNX
End2EndPerception deployment solution based on vision sparse transformer paradigm is open sourced.
Convert yolo models to ONNX, TensorRT add NMSBatched.
Advance inference performance using TensorRT for CRAFT Text detection. Implemented modules to convert Pytorch -> ONNX -> TensorRT, with dynamic shapes (multi-size input) inference.
tensorrt-toy code
Based on TensorRT v8.2, build network for YOLOv5-v5.0 by myself, speed up YOLOv5-v5.0 inferencing
Export (from Onnx) and Inference TensorRT engine with Python
Dockerized TensorRT inference engine with ONNX model conversion tool and ResNet50 and Ultraface preprocess and postprocess C++ implementation
Tools for Nvidia Jetson Nano, TX2, Xavier.
Convenient Convert CRAFT Text detection pretrain Pytorch model into TensorRT engine directly, without ONNX step between
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!
C++/C TensorRT Inference Example for models created with Pytorch/JAX/TF
This project provides a comprehensive Python script to convert a PyTorch model to an ONNX model and then to a TensorRT engine for NVIDIA GPUs, followed by performing inference using the TensorRT engine. This script is designed to handle the entire conversion process seamlessly.
Jetson TX2 compatible TensorFlow's ssd_mobilenet_v2_coco for TensorRT 6 / JetPack 4.3
Experimenting with Cifar-10 dataset to understand and implement various Deep Learning Techniques and CNN Architectures for Image Classification.
A CLI tool to convert Keras models to ONNX models and TensorRT engines
不同backend的模型转换与推理代码
This project is a notebook of learning TensorRT.
Convert popular Deep learning models to TensorRT using C++ API (preferably)