MankaranSingh

Auto-Birds-Eye. Bird's eye/Top Down view generation and mapping with deep learning.

Auto-Depth. 3D Reconstruction / Pseudo LiDAR via Deep Learning

AutoLabeler. Autolabel is a simple GUI tool to easily assign and verify *action labels* to individual frames of your self driving dataset.

IsaacLab. Unified framework for robot learning built on NVIDIA Isaac Sim

car-models. A car game to learn about simple vehicle dynamics in python

comma-scratch. train openpilot model from scratch

AQI-Management-System. Pollution is now a major problem, this project focuses on providing AQI data and visualisations for very precise locations so as to pinpoint the actual sources of pollution instead of providing data for large chunks of areas.

GSoC-2020. This repo works on developing proof of concepts for some tasks.

Ultra-Fast-Lane-Detection. Ultra Fast Structure-aware Deep Lane Detection (ECCV 2020)

Lane-Labeller. Python

AWD. Adverserial Waddle Dynamics

SuperDrive. A live deep neural network based lane/path detection system based on SuperCombo

lanenet-lane-detection. Unofficial implemention of lanenet model for real time lane detection using deep neural network model https://maybeshewill-cv.github.io/lanenet-lane-detection/

UPI-NLP. Python

Robotic-Arm. Jupyter Notebook

MiniRoboticArm_GestureRecognition. A Mini Robotic Arm that replicates with Hand Gestures

Algorithms-for-Automated-Driving. Each chapter of this (mini-)book guides you in programming one important software component for automated driving.

modeld. Self driving car lane and path detection

Machine-Learning-Notes. Contains notes for machine learning, code in general, not the math

Open_Duck_Mini_Runtime. Python

PythonRobotics. Python sample codes for robotics algorithms.

frenet. Transform Frenet (s,d) to local Cartesian (x,y) coordinates.

creative-computing-society.github.io. CSS

fleet_adapter_template. Python

ML-Research-Made-Easy. Link of ML papers to their blogs/ supplementary material

Kalman-and-Bayesian-Filters-in-Python. Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.