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filterpy icon filterpy

Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman filter, Unscented Kalman filter, g-h (alpha-beta), least squares, H Infinity, smoothers, and more. Has companion book 'Kalman and Bayesian Filters in Python'.

fusion-ukf icon fusion-ukf

An unscented Kalman Filter implementation in C++ for fusing lidar and radar sensor measurements.

hyperlpr icon hyperlpr

基于深度学习高性能中文车牌识别 High Performance Chinese License Plate Recognition Framework.

igcv3 icon igcv3

Code and Pretrained model for IGCV3

imageai icon imageai

A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities

interview_internal_reference icon interview_internal_reference

2019年最新总结，阿里，腾讯，百度，美团，头条等技术面试题目，以及答案，专家出题人分析汇总。

kalibr icon kalibr

The Kalibr visual-inertial calibration toolbox

kalman icon kalman

Header-only C++11 Kalman Filtering Library (EKF, UKF) based on Eigen3

kalman-1 icon kalman-1

Some Python Implementations of the Kalman Filter

kitti-pcl icon kitti-pcl

Code to use the KITTI (http://www.cvlibs.net/datasets/kitti) data set with PCL

leetcode icon leetcode

The optimum C++ solutions for the leetcode

leetcode-go icon leetcode-go

✅ Solutions to LeetCode by Go, 100% test coverage, runtime beats 100% / LeetCode 题解

leetcodeanimation icon leetcodeanimation

Demonstrate all the questions on LeetCode in the form of animation.（用动画的形式呈现解LeetCode题目的思路）

lift icon lift

Code release for the ECCV 2016 paper

lightnet icon lightnet

LightNet: Light-weight Networks for Semantic Image Segmentation (Cityscapes and Mapillary Vistas Dataset)

matterport icon matterport

Matterport3D is a pretty awesome dataset for RGB-D machine learning tasks :)

mdp_tracking icon mdp_tracking

Learning to Track: Online Multi-Object Tracking by Decision Making

models icon models

Models and examples built with TensorFlow

mono3d_plidar icon mono3d_plidar

Official PyTorch Implementation for "Monocular 3D Object Detection with Pseudo-LiDAR Point Cloud", ICCVW 2019

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