RARA: Zero-shot Sim2Real Visual Navigation with Following Foreground Cues

Related tags

Deep Learningfgbg
Overview

RARA: Zero-shot Sim2Real Visual Navigation with Following Foreground Cues

FGBG (foreground-background) pytorch package for defining and training models. For a demo, please watch: https://youtu.be/nnnhLXBl8J8

Install Imitation-learning codebase for data collection and evaluation in simulation

See instruction here: https://github.com/kkelchte/imitation-learning-codebase. If the installation went fluently you should be able to create a dataset from within your sourced singularity environment:

python3.8 src/sim/ros/src/data_collection_fg_bg.py

This will create a json and hdf5 file of a number of flewn trajectories in the line world.

Install FGBG in a conda environment

conda create --yes --name venv python=3.6
conda activate venv
conda install --yes --file requirements-conda
conda install --yes pytorch torchvision cudatoolkit=11.0 -c pytorch 
python -m pip install -r requirements-pip

Train your models for extracting the foreground and background

Pretrain a model with bg augmentation from MITplaces stored in data/datasets/places

python run.py --config_file configs/deep_supervision_triplet.json --texture_directory data/datasets/places --target line --output_dir data/mymodel

Finetune the final layers for waypoint prediction with

python run.py --config_file configs/deep_supervision_triplet.json --texture_directory data/datasets/places --target line --encoder_ckpt_dir data/mymodel --output_dir data/mymodel/waypoints --task waypoints

Evaluate neural network on both simulated and real bebop drone

From within the singularity environment, you can run the following files. Make sure you adjust each file to the correct task (waypoints) and the correct checkpoint directory (data/mymodel/waypoints).

For evaluation in simulation:

python3.8 src/sim/ros/src/online_evaluation_fgbg.py

For evaluation on the real bebop drone, make sure you connect to the wifi of the drone before launching:

python3.8 src/sim/ros/src/online_evaluation_fgbg_real.py
rosrun imitation-learning-ros-package fgbg_actor.py

If everything goes according to plan, a console view should pop up with the life mask predictions as well as the waypoints. In order to start the autonomous flight, you can either use the keyboard or the joystick interface to publish an emtpy message on the '/go' topic. You can over take the experiments with publishing an empty message on the '/overtake' topic.

Troubleshoot

Just email me on kkelchtermans AT gmail.com. Thanks!

Owner
Klaas Kelchtermans
I was born as Klaas Kelchtermans
Klaas Kelchtermans
This porject is intented to build the most accurate model for predicting the porbability of loan default

Estimating-Loan-Default-Probability IBA ML2 Mid-project / Kaggle Competition This porject is intented to build the most accurate model for predicting

Adil Gahramanov 1 Jan 24, 2022
code for Fast Point Cloud Registration with Optimal Transport

robot This is the repository for the paper "Accurate Point Cloud Registration with Robust Optimal Transport". We are in the process of refactoring the

28 Jan 04, 2023
PyTorch implementation of HDN(Homography Decomposition Networks) for planar object tracking

Homography Decomposition Networks for Planar Object Tracking This project is the offical PyTorch implementation of HDN(Homography Decomposition Networ

CaptainHook 48 Dec 15, 2022
Source code for our CVPR 2019 paper - PPGNet: Learning Point-Pair Graph for Line Segment Detection

PPGNet: Learning Point-Pair Graph for Line Segment Detection PyTorch implementation of our CVPR 2019 paper: PPGNet: Learning Point-Pair Graph for Line

SVIP Lab 170 Oct 25, 2022
NHL 94 AI contests

nhl94-ai The end goals of this project is to: Train Models that play NHL 94 Support AI vs AI contests in NHL 94 Provide an improved AI opponent for NH

Mathieu Poliquin 2 Dec 06, 2021
A tensorflow=1.13 implementation of Deconvolutional Networks on Graph Data (NeurIPS 2021)

GDN A tensorflow=1.13 implementation of Deconvolutional Networks on Graph Data (NeurIPS 2021) Abstract In this paper, we consider an inverse problem i

4 Sep 13, 2022
Pytorch implementation of "ARM: Any-Time Super-Resolution Method"

ARM-Net Dependencies Python 3.6 Pytorch 1.7 Results Train Data preprocessing cd data_scripts python extract_subimages_test.py python data_augmentation

Bohong Chen 55 Nov 24, 2022
TriMap: Large-scale Dimensionality Reduction Using Triplets

TriMap TriMap is a dimensionality reduction method that uses triplet constraints to form a low-dimensional embedding of a set of points. The triplet c

Ehsan Amid 235 Dec 24, 2022
A denoising autoencoder + adversarial losses and attention mechanisms for face swapping.

faceswap-GAN Adding Adversarial loss and perceptual loss (VGGface) to deepfakes'(reddit user) auto-encoder architecture. Updates Date Update 2018-08-2

3.2k Dec 30, 2022
Pytorch implementations of popular off-policy multi-agent reinforcement learning algorithms, including QMix, VDN, MADDPG, and MATD3.

Off-Policy Multi-Agent Reinforcement Learning (MARL) Algorithms This repository contains implementations of various off-policy multi-agent reinforceme

183 Dec 28, 2022
Machine learning algorithms for many-body quantum systems

NetKet NetKet is an open-source project delivering cutting-edge methods for the study of many-body quantum systems with artificial neural networks and

NetKet 413 Dec 31, 2022
571 Dec 25, 2022
Analysis of Antarctica sequencing samples contaminated with SARS-CoV-2

Analysis of SARS-CoV-2 reads in sequencing of 2018-2019 Antarctica samples in PRJNA692319 The samples analyzed here are described in this preprint, wh

Jesse Bloom 4 Feb 09, 2022
Text to image synthesis using thought vectors

Text To Image Synthesis Using Thought Vectors This is an experimental tensorflow implementation of synthesizing images from captions using Skip Though

Paarth Neekhara 2.1k Jan 05, 2023
Random Forests for Regression with Missing Entries

Random Forests for Regression with Missing Entries These are specific codes used in the article: On the Consistency of a Random Forest Algorithm in th

Irving Gómez-Méndez 1 Nov 15, 2021
An NLP library with Awesome pre-trained Transformer models and easy-to-use interface, supporting wide-range of NLP tasks from research to industrial applications.

简体中文 | English News [2021-10-12] PaddleNLP 2.1版本已发布!新增开箱即用的NLP任务能力、Prompt Tuning应用示例与生成任务的高性能推理! 🎉 更多详细升级信息请查看Release Note。 [2021-08-22]《千言:面向事实一致性的生

6.9k Jan 01, 2023
Implementation of ResMLP, an all MLP solution to image classification, in Pytorch

ResMLP - Pytorch Implementation of ResMLP, an all MLP solution to image classification out of Facebook AI, in Pytorch Install $ pip install res-mlp-py

Phil Wang 178 Dec 02, 2022
Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning

We challenge a common assumption underlying most supervised deep learning: that a model makes a prediction depending only on its parameters and the features of a single input. To this end, we introdu

OATML 360 Dec 28, 2022
A Vision Transformer approach that uses concatenated query and reference images to learn the relationship between query and reference images directly.

A Vision Transformer approach that uses concatenated query and reference images to learn the relationship between query and reference images directly.

24 Dec 13, 2022
Seeing if I can put together an interactive version of 3b1b's Manim in Streamlit

streamlit-manim Seeing if I can put together an interactive version of 3b1b's Manim in Streamlit Installation I had to install pango with sudo apt-get

Adrien Treuille 6 Aug 03, 2022