ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

Header-only C++ library for low precision floating point type emulation.

[ECCV'24] Online Vectorized HD Map Construction using Geometry

[ICCV 2023] StreamPETR: Exploring Object-Centric Temporal Modeling for Efficient Multi-View 3D Object Detection

[ECCV2022] PETR: Position Embedding Transformation for Multi-View 3D Object Detection & [ICCV2023] PETRv2: A Unified Framework for 3D Perception from Multi-Camera Images

An open source light-weight and high performance inference framework for Hailo devices

half float library for C and for z80

Conversion to/from half-precision floating point formats

🔥🔥🔥🔥 (Earlier YOLOv7 not official one) YOLO with Transformers and Instance Segmentation, with TensorRT acceleration! 🔥🔥🔥

Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

yolov5 + csl_label.(Oriented Object Detection)（Rotation Detection）（Rotated BBox）基于yolov5的旋转目标检测

mmdetection最小学习版

The pytorch re-implement of the official efficientdet with SOTA performance in real time and pretrained weights.

TensorRT Accelerate Mask_RCNN

基于TensorRT加速faster-rcnn模型

A massively spiffy yet delicately unobtrusive compression library.

Khronos OpenCL-Headers

A pure pytorch implemented ocr project including text detection and recognition

Convolutional recurrent network in pytorch

TensorRT8.Support Yolov5n,s,m,l,x .darknet -> tensorrt. Yolov4 Yolov3 use raw darknet *.weights and *.cfg fils. If the wrapper is useful to you,please Star it.

High quality, fast, modular reference implementation of SSD in PyTorch

Here is a pytorch implementation of deeplabv3+ supporting ResNet(79.155%) and Xception(79.945%). Multi-scale & flip test and COCO dataset interface has been finished.

Pretrained DeepLabv3 and DeepLabv3+ for Pascal VOC & Cityscapes

Mirror of CMake upstream repository

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

PyTorch implementation of SENet

MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, …

Caffe on both Linux and Windows

Convert PyTorch model to Caffemodel

GoogleTest - Google Testing and Mocking Framework