Deep Learning API and Server in C++14 support for Caffe, PyTorch,TensorRT, Dlib, NCNN, Tensorflow, XGBoost and TSNE
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Updated
Jun 12, 2024 - C++
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
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
The real-time Instance Segmentation Algorithm SparseInst running on TensoRT and ONNX
Base on tensorrt version 8.2.4, compare inference speed for different tensorrt api.
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
Simple tool for PyTorch >> ONNX >> TensorRT conversion
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
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
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