There are 17 repositories under tensorrt topic.
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/
Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.
TensorRT is a C++ library for high performance inference on NVIDIA GPUs and deep learning accelerators.
Implementation of popular deep learning networks with TensorRT network definition API
PyTorch ,ONNX and TensorRT implementation of YOLOv4
Tengine is a lite, high performance, modular inference engine for embedded device
TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework.
An easy to use PyTorch to TensorRT converter
Deep Learning API and Server in C++14 support for Caffe, PyTorch,TensorRT, Dlib, NCNN, Tensorflow, XGBoost and TSNE
YOLOv4, YOLOv4-tiny, YOLOv3, YOLOv3-tiny Implemented in Tensorflow 2.0, Android. Convert YOLO v4 .weights tensorflow, tensorrt and tflite
micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、Low-Bit(≤2b)/Ternary and Binary(TWN/BNN/XNOR-Net); post-training-quantization(PTQ), 8-bit(tensorrt); 2、 pruning: normal、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization fuse for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape
Deep learning gateway on Raspberry Pi and other edge devices
TensorRT MODNet, YOLOv4, YOLOv3, SSD, MTCNN, and GoogLeNet
PyTorch/TorchScript compiler for NVIDIA GPUs using TensorRT
Library for Fast and Flexible Human Pose Estimation
Easy-to-use library to boost AI inference leveraging state-of-the-art optimization techniques.
YOLO5Face: Why Reinventing a Face Detector (https://arxiv.org/abs/2105.12931)
🍅🍅🍅YOLOv5-Lite: lighter, faster and easier to deploy. Evolved from yolov5 and the size of model is only 930+kb (int8) and 1.7M (fp16). It can reach 10+ FPS on the Raspberry Pi 4B when the input size is 320×320~
Add bisenetv2. My implementation of BiSeNet
🔥🔥🔥🔥 YOLO with Transformers and Instance Segmentation, with TensorRT acceleration! 🔥🔥🔥
C++ library based on tensorrt integration
OpenMMLab Model Deployment Framework
High-performance multiple object tracking based on YOLO, Deep SORT, and KLT 🚀
Fast and accurate object detection with end-to-end GPU optimization
Real-time pose estimation accelerated with NVIDIA TensorRT
TensorFlow models accelerated with NVIDIA TensorRT
Deploy your model with TensorRT quickly. 快速使用TensorRT来部署模型
Adlik: Toolkit for Accelerating Deep Learning Inference
This repo is implemented based on detectron2 and centernet
convert mmdetection model to tensorrt, support fp16, int8, batch input, dynamic shape etc.
NVIDIA DeepStream SDK 6.0.1 configuration for YOLO models
A library for high performance deep learning inference on NVIDIA GPUs.
[ICLR 2020] "FasterSeg: Searching for Faster Real-time Semantic Segmentation" by Wuyang Chen, Xinyu Gong, Xianming Liu, Qian Zhang, Yuan Li, Zhangyang Wang
YOLOv3 implementation in TensorFlow 2.3.1
TensorRT-7 Network Lib 包括常用目标检测、关键点检测、人脸检测、OCR等 可训练自己数据