Bmoradi93

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

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.

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.

Face-detection-with-a-sliding-window

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.

ros2-lgsvl-bridge

Bmoradi93/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.

Bmoradi93/Face-detection-with-a-sliding-window

Bmoradi93/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.

Bmoradi93/ros2-lgsvl-bridge

Bmoradi93/apex

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

Bmoradi93/AutowareAuto-Dockerfile

Bmoradi93/CasADi-tutorial-examples

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

Bmoradi93/CNN-CIFAR10

Bmoradi93/CNN-MNIST

Bmoradi93/creating_hybrid_images_python

Bmoradi93/docker_images

Forked from zed-docker

Bmoradi93/FeedForward-Neural-Network-MNIST

Bmoradi93/handwritten_digit_classification-cnn

Bmoradi93/irobot_create_msgs

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

Bmoradi93/librealsense

Intel® RealSense™ SDK

Bmoradi93/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

Bmoradi93/Logistic-Regression-MNIST

Bmoradi93/logitech_f710_ros

ROS inteface for Logitech F710 wireless gamepad.

Bmoradi93/mmcv

OpenMMLab Computer Vision Foundation

Bmoradi93/mmdetection

OpenMMLab Detection Toolbox and Benchmark

Bmoradi93/mpc-local-planner-matlab-version-using-casadi

The overall aim of this project, was to develop an MPC controller for Donkey Car robot to avoid objects while it is operating inside a specific 2D environment. A Donkey Car robot was provided with Raspberry Pi 4 control unit running Raspbian Operating System. On the other hand, MATLAB support package for R-Pi was used to create connection between MATLAB and R-Pi. CasADi library was used in order to implement MPC controller in MATLAB with pre-defined constraints on control actions and also pre-defined objects inside the operation environment. Finally, a comprehensive algorithm was generated to control the actual robot from MATLAB simulation while avoiding static obstacles.

Bmoradi93/mpc_controller-inverted_pendulum-casadi

the main aim of this project is to design and implement an MPC controller to keep an inverted pendulum in upward position, while the whole system is subjected to physical constraint.

Bmoradi93/retinanet-examples

Fast and accurate object detection with end-to-end GPU optimization

Bmoradi93/ros_template_packages

Bmoradi93/rtk-sender-example

Example that connects to a GPS and sends RTCM RTK data via MAVLink using MAVSDK

Bmoradi93/Scene-recognition-with-bag-of-words

he goal of this repository is to introduce you to image recognition. Specifically, we will examine the task of scene recognition starting with very simple methods -- tiny images and nearest neighbor classification -- and then move on to more advanced methods -- bags of quantized local features and linear classifiers learned by support vector machines.

Bmoradi93/simulator

A ROS/ROS2 Multi-robot Simulator for Autonomous Vehicles

Bmoradi93/SSD-Object-Detection

Bmoradi93/torch2trt

An easy to use PyTorch to TensorRT converter

Bmoradi93/zed-opencv

ZED SDK interface sample for OpenCV