Luis Braca's repositories
f1tenth_gym_ros
Containerized ROS communication bridge for F1TENTH gym environment.
visual-chatgpt
Official repo for the paper: Visual ChatGPT: Talking, Drawing and Editing with Visual Foundation Models
nerf
Code release for NeRF (Neural Radiance Fields)
turtlebot3
ROS packages for Turtlebot3
f1tenth_labs
F1TENTH ROS simulator and lab skeleton packages with corresponding handout latex files
3D-Machine-Learning
A resource repository for 3D machine learning
WOFT
Weighted Optical Flow Tracker
ChatGPT_Trading_Bot
This is the code for the "ChatGPT Trading Bot" Video by Siraj Raval on Youtube
turtlebot3_simulations
Simulations for TurtleBot3
turtlebot3_msgs
ROS msgs package for TurtleBot3
sdk-examples
Spectacular AI SDK examples
FCND-Estimation-CPP
C++ project for the FCND estimation.
path_planning
This repository contains path planning algorithms in C++ for a grid based search.
EasyMocap
Make human motion capture easier.
FCND-Controls-CPP
the C++ simulator and portion of the controls project
demo-github-actions
demo CI/CD pipeline using MLRun, Kubeflow and GitHub Actions
open3d_slam
Pointcloud-based graph SLAM written in C++ using open3D library.
LearnableOSG
Implementation of our paper Learnable Optimal Sequential Grouping for Video Scene Detection
uvadlc_notebooks
Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2021/Spring 2022
Pytorch-UNet
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
key_frame_extraction_public
This repository is for key frame extraction process.
lumibot
Backtesting and Trading Bots Made Easy for Crypto, Stocks, Options, Futures, FOREX and more
CoCa-pytorch
Implementation of CoCa, Contrastive Captioners are Image-Text Foundation Models, in Pytorch
instant-ngp
Instant neural graphics primitives: lightning fast NeRF and more
LoFTR
Code for "LoFTR: Detector-Free Local Feature Matching with Transformers", CVPR 2021
ros_autonomous_slam
ROS package which uses the Navigation Stack to autonomously explore an unknown environment with help of GMAPPING and constructs a map of the explored environment. Finally, a path planning algorithm from the Navigation stack is used in the newly generated map to reach the goal. The Gazebo simulator is used for the simulation of the Turtlebot3 Waffle Pi robot. Various algorithms have been integrated for Autonomously exploring the region and constructing the map with help of the 360-degree Lidar sensor. Different environments can be swapped within launch files to generate a map of the environment.