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advanced-cplusplus

airsim

Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research

apex

A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch

apollo

An open autonomous driving platform

autowareauto-dockerfile

behaviortree.cpp

Behavior Trees Library in C++. Batteries included.

bmoradi93.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

camera-calibration-and-fundamental-matrix-estimation-with-ransac

The goal of this repository is to introduce you to camera and scene geometry. Specifically I will estimate the camera projection matrix, which maps 3D world coordinates to image coordinates, as well as the fundamental matrix, which relates points in one scene to epipolar lines in another. The camera projection matrix and the fundamental matrix can each be estimated using point correspondences. To estimate the projection matrix (camera calibration), the input is corresponding 3d and 2d points. To estimate the fundamental matrix the input is corresponding 2d points across two images. I will start out by estimating the projection matrix and the fundamental matrix for a scene with ground truth correspondences. Then I'll move on to estimating the fundamental matrix using point correspondences from ORB, which is an alternative to SIFT.

casadi-tutorial-examples

Bsed on the CasADi original paper: "CasADi: a software framework for nonlinear optimization and optimal control"

cnn-cifar10

cnn-mnist

coding-interview-university

A complete computer science study plan to become a software engineer.

cplusplus-beginners

create3_sim

ROS 2 Simulation for the iRobot® Create® 3 Educational Robot

creating_hybrid_images_python

dc-motor-speed-control-pid-tuning-ziegler-nichols-method

In this repository, I will be providing step by step instructions to design and tune a PID controller using Ziegler–Nichols Method to control the output speed of a DC motor. I will be using Matlab and Arduino in this projects.

docker_images

Forked from zed-docker

face-detection-with-a-sliding-window

feedforward-neural-network-mnist

googletest

GoogleTest - Google Testing and Mocking Framework

groot

Graphical Editor to create BehaviorTrees. Compliant with BehaviorTree.CPP

handwritten_digit_classification-cnn

irobot_create_msgs

Action, message and service definitions used by the iRobot® Create® Platform

jetson-inference

Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.

joystick_ros2

Joystick driver for ROS2, support all platforms: Linux, OS X, Windows

jsk_visualization

jsk visualization ros packages

knn_image_classification

KNN classification algorithm is one of the well known classification methods in data engineering and image processing. This algorithm is basically a start point to use ML algorithms in the world of image processing. In this project, the KNN algorithm has been used to classify 3 kinds of animals namely, cat, dog, and panda. The animal dataset including 3000 images(1000 images per animal) has been used. The KNN algorithm has been written in python3. The results show that the KNN performance in image classification can be improved by increasing the number of nearest neighbors K to a specific number. Having said the performance cannot be improved by increasing K beyond the extracted criteria. Having said that the performance has a direct relation with the data quality.

librealsense

Intel® RealSense™ SDK

local_feature_mapping_python

In this repository I'm supposed to come up with written-from-scratch algorithms to perform the following computer vision tasks specifically in python: Feature detectors - Identify the interest points Feature descriptors - Extract feature vector descriptor surrounding each interest point Feature matching - Determine correspondence between descriptors in 2 views

logistic-regression-mnist